Laura Dabos

Carlos H Rodriguez

Marcela Nastro

Laurent Dortet

Rémy Bonnin

Angela Famiglietti

Bogdan I Iorga

Carlos Vay

Thierry Naas
email: thierry.naas@aphp.fr

LMB-1 producing Citrobacter freundii from Argentina, a novel player in the field of MBLs

Keywords: Class B3 MBL, carbapenemase, Metallo-beta-lactamase, CPE 3, Figures:4, number of references: 26

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Introduction

Gram-negative bacteria (GNB), especially Enterobacterales, Pseudomonas aeruginosa and Acinetobacter baumannii, have re-emerged as major players in antimicrobial resistance worldwide. In these species, resistance may affect all major classes of anti-gram-negative agents, the multidrug resistance (MDR) being relatively common. Currently, β-lactamase-mediated resistance does not spare even the newest and most powerful β-lactams (carbapenems), whose activity is challenged by carbapenemases [START_REF] Patel | Stormy waters ahead": global emergence of carbapenemases[END_REF].

Carbapenem-hydrolyzing -lactamases encountered in Enterobacterales belong either to (i) the Ambler class A including KPC, IMI and GES enzymes, (ii) Ambler class B metallo--lactamases (or MBL) of NDM-, VIM-and IMP-type, and (iii) Ambler class D enzymes including OXA-48 and its variants (mostly OXA-181, OXA-204 and OXA-232) [START_REF] Patel | Stormy waters ahead": global emergence of carbapenemases[END_REF]. Even though described for a few class C enzymes, carbapenem-hydrolysis is very rare and weak [2,[START_REF] Jousset | False-Positive Carbapenem-Hydrolyzing Confirmatory Tests Due to ACT-28, a Chromosomally Encoded AmpC with Weak Carbapenemase Activity from Enterobacter kobei[END_REF].

MBLs are by far the most worrisome β-lactamases since their prevalence is increasing worldwide, their broad substrate profile (including all β-lactams, except monobactams), and the lack of clinicallyuseful inhibitors. The MBLs are divided into three subclasses (B1, B2, B3) based on primary amino acid sequence homology [START_REF] Palzkill | Metallo-β-lactamase structure and function[END_REF]. There is relatively low sequence identity (< 20%) between the subclasses. Within a subclass the sequence identity is higher and this, along with distinctive structural characteristics within the active sites of B1, B2, and B3 enzymes, is the basis for the establishment of the three subclasses. The B1 and B3 subclasses have a broad-spectrum substrate profile that includes penicillins, cephalosporins, and carbapenems and contain two Zn 2+ ions in their active site, while the B2 enzymes exhibit a narrow-spectrum profile that includes carbapenems and contain only one Zn 2+ ion.

MBLs of subclass B1, such as NDM, VIM, and IMP-like are the clinically-most relevant enzymes in Enterobacterales, but sporadic isolations of other class B1 MBLs such as GIM, FIM, KHM, have also be reported [START_REF] Palzkill | Metallo-β-lactamase structure and function[END_REF]. Subclass B2 contains only two enzymes that possess a narrow-spectrum of hydrolysis.

The Subclass B3 is a larger group of enzymes, of which the genes are mostly chromosomally-encoded, and display a broad-spectrum of ß-lactam hydrolysis. In this subclass only AIM, found in P. aeruginosa, and SMB-1 in Serratia marcescens have been reported acquired [START_REF] Yong | Genetic and biochemical characterization of an acquired subgroup B3 metallo-β-lactamase gene, blaAIM-1, and its unique genetic context in Pseudomonas aeruginosa from Australia[END_REF][START_REF] Wachino | SMB-1, a novel subclass B3 metallo-beta-lactamase, associated with ISCR1 and a class 1 integron, from a carbapenem-resistant Serratia marcescens clinical isolate[END_REF].

While the increasing availability of commercial qPCR systems allows for the detection of the most prevalent MBL families, molecular diagnostics clearly overlooks MBLs that belong to less prevalent MBL-families. Furthermore, novel MBLs have recently been identified in clinical isolates: TMB-1 in Enterobacter hormaechei and Citrobacter freundii from Tunisia [START_REF] Gauthier | Molecular characterization of plasmid-encoded Tripoli MBL 1 (TMB-1) in Enterobacteriaceae[END_REF] and LMB-1 in Enterobacter cloacae from Austria [START_REF] Lange | LMB-1, a novel subclass B3 metallo-beta-lactamase from a carbapenem-resistant Enterobacter cloacae isolate[END_REF]. In this work, we have characterized a novel chromosomallyencoded CMY-variant: CMY-150 and the second clinical LMB-1-producing Enterobacterales, a C. freundii clinical isolate recovered from a Hospital in Buenos Aires, Argentina.

Materials and Methods

PCR, cloning experiments, and sequencing.

Whole-cell DNAs of Cf164 isolates were extracted using the QIAamp DNA minikit (Qiagen, Les Ulis, France) and were used as templates for PCR with the following primers: preCMY-150-A (5'-ATGATGAAAAAATCGAT-3') and preCMY-150-B (5'-TCTGTCAGTTATTGCAGT-3') and preLMB-1-A (5'-ATGACGTTAGCTAAAAGTTTT -3') and preLMB-1-B (5'-TACTGCGTTGTTTCCTTTATTAAA-3') from amplifying blaCMY-150, and blaLMB-1, respectively. The amplicon obtained was then cloned into the pCR®-Blunt II-TOPO® plasmid (Qiagen) after quality trimming (Qs ≥ 20) according the manufacturer's recommendations (Qiagen, Courtaboeuf, France). C. freundii Cf164 total DNA was also sequenced using PacBio long read technology (Macrogen, Seoul, South Korea). PacBio subreads were assembled with both Canu [START_REF] Berlin | Assembling large genomes with single-molecule sequencing and locality-sensitive hashing[END_REF] and the RS_HGAP_Assembly.3 protocol from the SMRT analysis toolkit v2.3, while consensus accuracy was further polished using Quiver [START_REF] Chin | Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data[END_REF] as was previously described [START_REF] Almeida | Persistence of a dominant bovine lineage of group B Streptococcus reveals genomic signatures of host adaptation[END_REF]. The acquired antimicrobial resistance genes were identified by uploading assembled genomes to the Resfinder server v2.1 that uses BLAST for identification of acquired antimicrobial resistance genes and chromosomal mutations in whole-genome data (http://cge.cbs.dtu.dk/services/ResFinder-2.1) [START_REF] Zankari | Identification of acquired antimicrobial resistance genes[END_REF]. Additionally, the whole genome sequence of Cf164 was also uploaded to an in-house developed software, ResMiner (BI Iorga, pers. comm.), that searches for flags specific of the four molecular classes of β-lactamases.

For the reconstruction of pCf164_LMB-1 and pCf164_CTX-M-8 gaps were filled by PCR amplification and Sanger sequencing. Open reading frames (ORFs) were annotated using the RAST server (rast.nmpdr.org) followed by manual comparative curation and determination of sequence similarity using the BLAST web server. Alignments were performed by using the BRIG tool [START_REF] Alikhan | BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons[END_REF] 2.6. Plasmid characterization and conjugation assay. Plasmid DNA of the clinical isolates Cf164 was extracted using the Kieser method [START_REF] Kieser | Factors affecting the isolation of CCC DNA from Streptomyces lividans and Escherichia coli[END_REF]. The Kieser extract was used to transform E. coli TOP10 strain by electroporation. The electroporants were plated on a TSA plate containing 100 µg/ml ampicillin. Transformants were analyzed by PCR using the primers pre-LMB-1A and pre-LMB-1B.

From the transformants harboring the blaLMB-1 gene, plasmid DNA extraction was done using the Kieser's method and subsequently analyzed on 0.7% agarose gel stained with ethidium bromide. Plasmids of ca. 154, 66, 48, and 7 kb of E. coli NCTC 50192 were used as plasmid size markers [START_REF] Dortet | Genetic and biochemical characterization of OXA-405, an OXA-48-type extended-spectrum β-lactamase without significant carbapenemase activity[END_REF].

To perform the quantitative filter mating-out assay, the clinical isolates Cf164 was used as donor and E. coli J53 as recipient. Both isolates were each grown overnight in brain heart infusion (BHI) (BioMérieux). A 0.25 ml of each donor and recipient donor culture were diluted in 4.75 ml BHI broth and incubated at 37°C for 5 h without shaking. Subsequently, 0.25 ml of the donor culture was gently mixed with 2.5 ml of the recipient culture, and 200 µl of this mating mix was spotted on a 0.45µm filter (Millipore, Paris, France) placed on a prewarmed MH plates and incubated at 37°C for 2 h.

The mating assays were terminated by placing the filters in 4 ml of an ice-cold 0.9% NaCl solution, followed by vigorous agitation for 30 s. The number of transconjugants per donor cell was determined by plating dilutions of the mating mixture onto plates containing antibiotics. Strain donor cells were selected with 100µg /ml ampicillin. Transconjugants were selected with 100µg/ml ampicillin and 100µg/ml azide. Transfer frequencies were calculated by dividing the number of transconjugants by the number of donor cells.

β-Lactamase purification.

An overnight culture of E. coli strain BL21 (DE3) harboring pET41b-CMY-150, pET41b-LMB-1 and pET28a-LMB-1 were used to inoculate 2 L of LB broth containing 50 µg/ml kanamycin. The bacteria were cultured at 37ºC until reaching an OD of 0.6 at 600 nm. Expression of both enzymes was induced overnight at 25ºC with 0.2 mM IPTG, as previously described [START_REF] Dabos | Genetic and Biochemical Characterization of OXA-519, a Novel OXA-48-Like β-Lactamase[END_REF]. For pET41b-LMB-1 additional induction conditions were tested (temperature: 16°, 25°, 37°; IPTG: 0.2mM, 0.5mM, 1.0mM; cells: E. coli BL21 (DE3), E. coli BL21 (DE3) pLysS, E. coli Rosetta™ (DE3)). Cultures were centrifuged at 6000 g for 15 min and the pellets were resuspended in 10 mL of Buffer A (20 mM phosphate buffer, 175 mM potassium sulfate (K2SO4), 40mM Imidazol, pH 7.40). The cells were disrupted by sonication and bacterial debris was removed by two consecutive centrifugation steps: at 10.000 g for 1 h at 4ºC, and at 48.000 g for 1 h at 4ºC. CMY-150 and LMB-1 were purified in one step pseudo-affinity chromatography using a NTA-Ni column (GE Healthcare, Les Ulis, France) [START_REF] Dabos | Genetic and Biochemical Characterization of OXA-519, a Novel OXA-48-Like β-Lactamase[END_REF]. Protein purity was estimated by SDS-PAGE, pure fractions were pooled and dialyzed against 20mM Hepes, K2SO4 50mM buffer (pH 7) and concentrated using Vivaspin® columns (GE Healthcare). Protein concentration was determined by Bradford Protein assay (Bio-Rad) [START_REF] Dabos | Genetic and Biochemical Characterization of OXA-519, a Novel OXA-48-Like β-Lactamase[END_REF].

Steady-state kinetic parameters.

Kinetic parameters of purified CMY-150 were determined at 30ºC in 100mM sodium phosphate buffer (pH 7). The kcat and Km values were determined by analyzing hydrolysis of β-lactams under initial-rate conditions with an ULTROSPEC 2000 model UV spectrophotometer (GE Healthcare) using the Eadie-Hoffstee linearization of the Michaelis-Menten equation, as previously described [START_REF] Dabos | Genetic and Biochemical Characterization of OXA-519, a Novel OXA-48-Like β-Lactamase[END_REF]. The different β-lactams were purchased from Sigma-Aldrich (Saint-Quentin-Fallavier, France).

The specific activities of the -lactamase LMB-1 for β-lactams were determined on the supernatant of a whole cell crude extract obtained from an overnight culture of pTOPO-LMB-1 in E. coli TOP 10 as previously described [START_REF] Dortet | Genetic and biochemical characterization of OXA-405, an OXA-48-type extended-spectrum β-lactamase without significant carbapenemase activity[END_REF].

Results and discussion

Clinical case.

A 68-year-old patient with Non-Hodgkin lymphoma, type l diabetes and history of previous myocardial infarction, was admitted in a tertiary care hospital in Buenos Aires. After 12 days of the hospitalization, he presented febrile neutropenia and a catheter-related bacteraemia due to a methicillin resistant Staphylococcus haemolyticus. At the same time, the urine culture revealed a bacterial count of 10 5 CFU/ml of a C. freundii isolate. The patient was treated with vancomycin and amikacin that led to the resolution of the urinary tract infection and the bacteraemia.

Characteristics of C. freundii 164. Routine antibiogram and MIC values of Cf164

revealed penicillins, aztreonam, expanded-spectrum cephalosporin resistance and reduced susceptibility to imipenem (Table 1). As the MIC for imipenem was 0.5 µg/ml and even though the MIC for meropenem was below 0.125 µg/ml, which is the EUCAST screening cut off for carbapenemases, the blue carba carbapenemase confirmatory test was performed. The latter gave a weak positive result suggesting the presence of a carbapenem-hydrolyzing β-lactamase. These results were confirmed using different biochemical confirmatory tests based on imipenem hydrolysis (β Carba, rCIM and MBT STAR-Carba TM tests) which were consistently positive except for the Carba NP that remained repeatedly negative. PCRs detecting the five most prevalent carbapenemases (blaOXA-48, blaKPC, blaNDM, blaVIM, blaIMP) and the immunochromatographic NG Carba5 test were negative, suggesting the presence of a minor carbapenemase. WGS data of Cf164 was analyzed using CLC genomic workbench (Qiagen) and revealed a genome of 5,229,602 bp, with an average 50 X coverage (NZ_QCWX01000001).

Resistome was analyzed by searching acquired genes using Resfinder and point mutations involved in chromosomal resistance. Four β-lactamase genes were identified, a novel chromosomal and natural blaCMY-2-like gene, blaCTX-M-8 and blaPER-2 coding for two ESBLs, and blaTEM-1, coding for a broadspectrum penicillinase. The isolate harbored also two qnr resistance genes (qnrE and qnrB38), a rifampicin resistance gene (aar-3), a sulfonamide resistant gene (sul1) and a trimethoprim resistance gene (dfrA27). The finding of these genes matched well with the resistance phenotype of Cf164 to trimethoprim and to nalidixic acid. Mutations in the QRDR, known to confer fluoroquinolone resistance were not found explaining the susceptibility to fluoroquinolones. CMY-150 and CMY-2 were cloned into the pCR®-Blunt II-TOPO® plasmid (pTOPO-CMY-150, and pTOPO-CMY-2) and transformed into E. coli TOP10. CMY-150 conferred a higher level of resistance to cefotaxime (>256 µg/ml vs 8 µg/ml for CMY-2), ceftazidime (>256 µg/ml vs 24 µg/ml for CMY-2) and aztreonam (32 µg/ml vs 3 µg/ml for CMY-2) (Table 1). MICs for carbapenems were heterogeneous, with imipenem being the highest (MIC 0.38 µg/ml), meropenem (MIC 0.047 µg/ml) and ertapenem (MIC 0.047 µg/ml) remaining in the susceptibility range. The MICs for carbapenems conferred by pTOPO-CMY-150, even though in the susceptibility range, were slightly higher than those conferred by CMY-2 (Table 1). In front of these results, MICs for imipenem for Cf164 was performed on cloxacillin-containing (250 µg/ml) MH plates and revealed the exact same value, suggesting that another enzyme capable of hydrolyzing carbapenems might be present in these bacteria.

Characterization of β-lactamase

To compare the kinetic properties of CMY-2 and the new CMY-150, the steady state parameters of the pure proteins were determined (Table2). Overall, the catalytic efficiencies were very similar between the two enzymes, except for ampicillin (40-fold higher for CMY-2). The kinetic parameters for aztreonam could not be obtained since no hydrolysis was observed. For this reason, we determined the IC50 values for CMY-2 and CMY-150, revealing similar results for both enzymes (0.2 µM for CMY-2 and 0.31 µM for CMY-150). These results cannot explain the difference observed in the MIC values obtained and although further analysis are required to understand this phenotype, we suggest that the CMY-150 could present a higher affinity for aztreonam than CMY-2. Regarding the kinetic parameters for imipenem, in both enzymes the Km values were highly similar as well as the activity, further suggesting that another enzyme capable of hydrolyzing carbapenems might be present in Cf164.

Identification of blaLMB-1 gene in the WGS of Cf164.

Using an in-house developed software, ResMiner (BI Iorga, pers. comm.), that searches for flags specific of the four molecular classes of β-lactamases, found in addition to blaCMY-150, blaCTX-M-8, blaPER-2 and blaTEM-1 genes, an additional gene coding for a putative MBL of sub class B3. Blast searches revealed that this MBL had 100 % sequence identity with LMB-1, a MBL found only once if an E. cloacae isolate from Linz in Austria (Accession number KU646836) [START_REF] Lange | LMB-1, a novel subclass B3 metallo-beta-lactamase from a carbapenem-resistant Enterobacter cloacae isolate[END_REF].

Susceptibility of LMB-1-producing isolates and kinetic properties of LMB-1.

The expression of LMB-1 in E. coli Top10 resulted in increased MICs of penicillins, cephalosporins and carbapenems, but not of aztreonam (Table 1). A slight inhibition of β-lactamase inhibitors on the MICs could be detected. Of note, the MIC of cefepime was lower than that of ceftazidime and MICs of aztreonam were comparable to that of E. coli TOP 10, confirming the MBL behavior of LMB-1.

As purification of LMB-1 failed despite repeated attempts in different conditions, crude lysates of E. coli TOP10 pTOPO-LMB-1 were used to determine β-lactam specific activities. It revealed strong specific activity against carbapenems, oxyimino cephalosporins and aminopenicillins (Table 3). No specific activity against aztreonam nor cefepime, as previously reported [START_REF] Lange | LMB-1, a novel subclass B3 metallo-beta-lactamase from a carbapenem-resistant Enterobacter cloacae isolate[END_REF], could be detected. When compared to NDM-1 expressed in the same conditions, LMB-1 had slightly higher (2-fold) activity against cefoxitin, whereas the activity against carbapenems was c.a. 8-fold lower (Table3). It is important to highlight that the MIC values for carbapenems in Cf164 were lower than those obtained with E. coli Top10 carrying the natural plasmid pCf164_LMB-1 and with E. coli Top10 carrying pTOPO-LMB-1. The latter results, together with the low specific activities against carbapenems as compared to NDM-1, may explain the negative results obtained with NP Carba test, a test based on imipenem hydrolysis.

Most of these results correlate well with the results of the comparative MIC studies confirming activity of LMB-1 against aminopenicillins, ceftazidime, cefotaxime and carbapenems. However, in the comparative MIC studies, expression of LMB-1 accounted for an 8-fold increase in the MIC of cefepime, which indicates that LMB-1 does indeed present activity against cefepime. The fact that no specific activity could be detected against cefepime within 10 min may indicate that the hydrolysis rates of LMB-1 for this substrate may be very low yet the hydrolysis rate appears to have been sufficiently high to account for a substantial increase in the MIC of cefepime, or the affinity of LMB-1 for cefepime may be high enough to trap the antibiotic, which is reflected in the raise of the MIC value.

Characterization of plasmids and genetic environments.

PacBio assembly analysis revealed 12 contigs, two of them belonging to plasmidic DNA. The presence of two plasmids was confirmed by Kieser extraction (Figure 1). blaLMB-1 gene was inserted onto a conjugative IncA/C type plasmid of 175,712bp, pCf164_LMB-1 (accession number MH475146.1) (Figure 1), that also carried blaPER-2 gene. pCf164_LMB-1 was different from the IncFIB(K)-type pNRZ-10170-LMB-1 plasmid found in E. cloacae NRZ-10170 from Austria (accession number MH056209.1) [START_REF] Lange | LMB-1, a novel subclass B3 metallo-beta-lactamase from a carbapenem-resistant Enterobacter cloacae isolate[END_REF] except for the immediate genetic environment of blaLMB-1 gene.

The comparison of the immediate genetic environment of blaLMB-1 in pNRZ-10170-LMB-1 and in pCf164_LMB-1 revealed an identical area between a qacG gene upstream of blaLMB-1 gene and sul1 gene downstream of blaLMB-1 gene (Figure 2). This genetic organization is similar to a complex class 1 integron with the presence of ISCR1 element. Toleman et al. reported the mobilization of class 1 integrons by ISCR1 through the transposition of ISCR1 next to the 3' end of the class 1 integron (qac/sul genes) and the transposase misreading of the terIS sequence [START_REF] Toleman | Common regions e.g. orf513 and antibiotic resistance: IS91-like elements evolving complex class 1 integrons[END_REF]. The segment of DNA involving the 3' end of the class 1 integron and the 5' end of the ISCR1 is deleted erasing the normal termination site, terIS and thereby creating and integron-ISCR1 fusion. From this point on, ISCR1 is able to mobilize the integron [START_REF] Toleman | Common regions e.g. orf513 and antibiotic resistance: IS91-like elements evolving complex class 1 integrons[END_REF]. It is likely that the similarities observed in the genetic environment of blaLMB-1, in pNRZ-10170-LMB-1 and in pCf164_LMB-1, might be the result of blaLMB-1 gene mobilization mediated by an ISCR1, among other events. LMB-1 shares 99% sequence identity with a predicted MBL (SEI10464) from the marine bacterium R. pacifica, as previously shown [START_REF] Lange | LMB-1, a novel subclass B3 metallo-beta-lactamase from a carbapenem-resistant Enterobacter cloacae isolate[END_REF].

IncA/C plasmids were among the earliest antimicrobial resistance-encoding plasmids identified in Gram-negative bacteria and have received attention due to their broad host range and their association with the emergence of multidrug resistance in enteric pathogens of humans and animals [START_REF] Han | Impact of co-carriage of IncA/C plasmids with additional plasmids on the transfer of antimicrobial resistance in Salmonella enterica isolates[END_REF]. IncA/C plasmids are of high-molecular-weight low-copy-number and are considered responsible for the dissemination of the clinically-relevant ß-lactamase genes e.g. blaCTX-M, blaCMY, blaNDM, blaIMP, blaVIM, and blaKPC genes, among others [START_REF] Hancock | Identification of IncA/C plasmid replication and maintenance genes and development of a plasmid multilocus sequence typing scheme[END_REF][START_REF] Papagiannitsis | Characterization of the complete nucleotide sequence of IncA/C2 plasmids carrying In809-like integrons from Enterobacteriaceae of wildlife origin[END_REF]. In a nucleotide BLAST search for closely related plasmids to pCf164_LMB-1, two IncA/C plasmids were found, namely in, Salmonella enterica strain CFSAN064034 plasmid pGMI17-002_1 (CP028170) and in Vibrio cholerae genome assembly V. cholerae 116-17a plasmid pNDM-116-17 both isolated in India (LN831185). In addition, plasmid pCf587 harboring PER-2 (MG053108) recovered in Argentina from C. freundii 33587, also belongs to IncA/C type plasmids and is related to pCf164_LMB-1 [START_REF] Ruggiero | Complete sequence of the IncA/C1 plasmid pCf587 carrying blaPER-2 from Citrobacter freundii[END_REF]. PER-2 has been the second most prevalent ESBL, after the pandemic CTX-Ms, in Argentina, accounting for nearly 10% and 5% of the oxyiminocephalosporin resistance in K. pneumoniae and E. coli, respectively [START_REF] Ruggiero | Complete sequence of the IncA/C1 plasmid pCf587 carrying blaPER-2 from Citrobacter freundii[END_REF]. Comparative sequence analysis revealed a conserved backbone length and similar overall genetic arrangements (Figure 3). pNRZ-10170-LMB-1 was also included in the analysis, showing similarities only in the immediate environment of blaLMB-1 gene (Figure 3).

The second plasmid carried by Cf164, pCf164_CTX-M-8 (accession number MN187903), was fully sequence by PacBio as a single contig. This 68,453 bp plasmid belonged to the IncM incompatibility group and encoded plasmid replication, maintenance, and transfer genes and two resistance gene regions (Figure 4). The first one contained the blaTEM-1A penicillinase and the second one of 3,560 bp, contained the blaCTX-M-8 gene bracketed by two copies of IS26 likely forming a composite transposon [2]. Overall, the nucleotide sequence of pCf164_CTX-M-8 was extremely similar to that of pKp145-11b recovered from a K. pneumoniae clinical isolate from Brazil (GenBank accession number KX118608) [START_REF] Cunha | Complete DNA Sequence of an IncM1 Plasmid Bearing the Novel qnrE1 Plasmid-Mediated Quinolone Resistance Variant and blaCTX-M-8 from Klebsiella pneumoniae Sequence Type 147[END_REF]. The differences between these two plasmids are based on the resistance genes present next to the blaTEM-1A gene. Indeed, pKp145-11b harbored a Tn1331-like element, that carried in addition to blaTEM-1A gene, three other resistance genes blaOXA-9 gene, ant(3')-Ia gene and aac(6')-Ib gene [START_REF] Cunha | Complete DNA Sequence of an IncM1 Plasmid Bearing the Novel qnrE1 Plasmid-Mediated Quinolone Resistance Variant and blaCTX-M-8 from Klebsiella pneumoniae Sequence Type 147[END_REF], as previously described [27]. Finally, as reported pKp145-11b had high nucleotide sequence identity with plasmid pKp41M (accession number KY781949), another IncM plasmid carried by a K. pneumoniae isolate recovered from a parrot in Brazil [START_REF] Cunha | Complete DNA Sequence of an IncM1 Plasmid Bearing the Novel qnrE1 Plasmid-Mediated Quinolone Resistance Variant and blaCTX-M-8 from Klebsiella pneumoniae Sequence Type 147[END_REF]. To the best of our knowledge, this is the first report of blaCTX-M-8 gene carried by an IncM type plasmid reported in Argentina, suggesting that this epidemic plasmid is not only circulating amongst human and animal in Brazil, but is now also spreading to the south of the continent.

Conclusion

In conclusion, this is the first report of LMB-1, a novel MBL of sub class B3, carried by a IncA/C type plasmid. Our data suggests that R. pacifica is likely the progenitor of LMB-1, and that two independent mobilization events have occurred on two different plasmids, in two different species, and on two distantly located continents. The dissemination of the conjugative pCf164_LMB-1 represents a public health threat as it combines a prevalent ESBL gene (blaPER-2) with a difficult to detect carbapenemase gene and that both genes are harbored by a broad-spectrum and conjugative IncA/C plasmid that may spread to many human pathogens.

LMB-1 displays hydrolytic activities against most ß-lactams, especially carbapenems and cephalosporins, that are important antimicrobial agents for the treatment of severe nosocomial infections caused by Enterobacterales. Even tough in the susceptibility range, animal models of infections are required to evaluate whether carbapenems may be a suitable therapeutic option. The fact that molecular assays, nor ResFinder, nor immunochromatography tests failed to identify this novel MBLs, and that biochemical tests gave inconsistent results may lead to silent spread of this type of enzyme. Thus, epidemiological studies to evaluate the extend of the dispersion of LMB-1 in Europe and the Americas should be undertaken.

2. 1 . 2 . 2 . 2 . 3 .

 12223 Bacterial strains. C. freundii 164 (Cf164) was identified with matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MALDI Biotyper CA system, Bruker Daltonics, Billerica, MA, USA). Escherichia coli TOP10 (Invitrogen, Saint-Aubin, France) was used for cloning experiments and E. coli BL21 was used for over-expression of ß-lactamases. Antimicrobial agents, susceptibility testing. Antimicrobial susceptibilities were determined by disk diffusion on Mueller-Hinton agar (Bio-Rad, Marnes-La-Coquette, France) and interpreted according to the EUCAST breakpoints, updated in 2018 (http://www.eucast.org). Minimal inhibitory concentration (MIC) values were determined using the Etest technique (BioMérieux, Marcyl'Etoile, France). Confirmatory tests for carbapenemase-producing Enterobacteria. Carbapenemase activity was investigated using the in house Carba NP test, Blue Carba, Modified Hodge test, β Carba Test (BioRad, Marnes-la-Coquette, France), rCIM, Maldi-TOF (MBT STAR-Carba TM , Brucker), PCRs and NG Carba5 (NG Biotech, Rennes, France) tests were performed following the manufacturer's recommendations or as previously published [9-12].

2. 9 .

 9 Nucleotide sequence accession number. The whole genome sequence of Cf164 generated in the study have been submitted to the Genbank nucleotide sequence database, under the accession number of NZ_QCWX01000001. The nucleotide sequence of blaCMY-150 genes along with plasmid pCf164_LMB-1 and pCf164_CTX-M-8 have been submitted to the EMBL/Genbank nucleotide sequence database under the accession numbers NG_060513, MH475146 and MN187903, respectively.

  CMY-150. CMY-150 differs from CMY-2 by 15 aminoacid substitutions (L6I, V52I, Q55E, Q122R, R125S, R146T, A150E, H153R, A182V, P185H, N214S, D218N, H262L, A273E, V368A) and for CMY-65 by two amino-acid substitutions (P185H, H262L).

Figure 1 .

 1 Figure 1. Plasmid extraction. Migration of the extracted pCf164_LMB-1 from the Cf164 (WT) and

Figure 2 .

 2 Figure 2. Genetic environment of blaLMB-1. Comparison of the genetic environment of blaLMB-1 gene

Figure 3 .

 3 Figure 3. Comparative genome analyses of several IncA/C group plasmids. Structural comparison of

Figure 4 .

 4 Figure 4. Plasmid sequence schematic representation. Major structural features of the plasmids

Table 1

 1 MIC values of β-lactams for C. freundii 164, E. coli TOP10 pTOPO-CMY-150, E. coli TOP10 pTOPO-CMY-2, E. coli TOP10 pN-LMB-1, E. coli TOP10 pTOPO-LMB-1 and E. coli

	TOP10.
				MIC (µg/mL)
				E. coli TOP10
		C. freundii					E.coli
	Antibiotic		(pTOPO-	(pTOPO-	(pCf164_	(pTOPO-
		164					TOP10
			CMY-150)	CMY-2)	LMB-1)	LMB-1)
	Amoxicillin	>256	>256	>256	>256	>256	2
	Amoxicillin + CLA a	64	64	32	>256	24	2
	Cefotaxime	>32	>32	8	>32	4	0.06
	Ceftazidime	128	>256	24	>256	48	0.12
	Cefepime	2	0.5	0.125	8	0.38	0.023
	Imipenem	0.5	0.38	0.24	1.5	0.75	0.25
	Meropenem	0.094	0.047	0.023	0.8	0.25	0.016
	Ertapenem	0.064	0.047	0.012	0.5	0.19	0.003
	Temocillin	64	24	16	>1024	512	4
	Aztreonam	32	32	3	>256	0.064	0.047

a CLA, clavulanic acid (2 µg/ml)

Table 2 .

 2 Kinetic parameters of CMY-150 and CMY-2.

		Km(µM)	kcat(s -1 )		kcat/Km (mM -1 s -1 )
	Substrate
		CMY-150 CMY-2	CMY-150	CMY-2	CMY-150	CMY-2
	Ampicillin	55	16	0.30	3.2	5.4	204
	Ceftazidime	13	15	0.04	0.05	3.1	3.3
	Imipenem	3.7	2.5	0.02	0.02	5.8	9.6
	Aztreonam	NH a	NH	NH	NH	-	-

a No hydrolysis

[START_REF] Dabos | Genetic and Biochemical Characterization of OXA-519, a Novel OXA-48-Like β-Lactamase[END_REF]

Table 3 .

 3 Specific activities for β-lactamases NDM-1 and LMB-1.

		Specific Activity (mU/mg)
	Antibiotic
		NDM-1	LMB-1
	Cefalotine	0.41	0.44
	Cefoxitine	0.44	0.81
	Ceftazidime	0.38	0.24
	Imipenem	7.42	0.88
	Meropenem	5.95	0.88
	Ertapenem	6.55	0.66
	Experiments were done in triplicate. Error rates were within 10%

Acknowledgements

We want to thank Pasteur International Bioressources Networking for providing whole genome sequencing facilities and the PacBio sequencing platform of the Pasteur Institute (Paris, France)

Funding

This work was supported by the Assistance Publique -Hôpitaux de Paris (AP-HP), the University Paris-Sud, the Laboratory of Excellence in Research on Medication and Innovative Therapeutics (LERMIT) supported by a grant from the French National Research Agency [ANR-10-LABX-33] and by the Joint 14 Programming Initiative on Antimicrobial Resistance (JPIAMR) DesInMBL [ANR-14-JAMR-002], and by DIM Malinf, Ile de France, for LD's PhD fellowship.

Conflict of interest

LD is co-inventor of the Carba NP Test, which patent has been licensed to bioMérieux (La Balmes les Grottes, France).


Ben Sahar
email: sahar_by_ing@live.fr

Yaala

Fabrice Théoleyre
email: theoleyre@unistra.fr

Ridha Bouallegue
email: ridha.bouallegue@supcom.tn

Performance Study of Co-Located IEEE 802.15.4-TSCH Networks: Interference and Coexistence

Keywords: IEEE802.15.4e-TSCH, interference, dense deployments, co-existence, synchronization, IoT, experiments

With the large deployment of smart and heterogeneous devices, interest of researchers to define new protocols to meet Internet of Things (IoT) requirements is growing. A particular interest was accorded to define a robust MAC layer for wireless sensor networks, in order to reduce interference caused by other co-located networks and applications using the ISM band. This paper gives a comprehensive study of the Time Slotted channel Hopping IEEE802.15.4, part of the 6TiSCH stack and explains how its TDMA approach improves the reliability with performance guarantees. We also investigate analytically and experimentally the impact of the scheduling algorithm on the reliability. Then, we provide an experimental evaluation of colocated WSN using the FiT-IoT LAB testbed and the OpenWSN Stack. Performance analysis of IEEE802.15.4e-TSCH is achieved with a variable number of co-located synchronized or unsynchronized instances. While this standard is robust for lightly loaded networks, new mechanisms have to be proposed when we have too much traffic or too many interfering networks.

I. INTRODUCTION

Our society is facing an unprecedented massive usage of numerical applications. The Internet of Things aims at making the environment smarter: smart buildings may comprise hundreds of sensors which report their measure (e.g. temperature, humidity) to a central controller [START_REF] Schor | Towards a zeroconfiguration wireless sensor network architecture for smart buildings[END_REF]. Smart decisions may then be computed, triggering some actuators (e.g. HVAC).

Body Area Networks (BAN) expect to see similarly a wide adoption. In particular, wearable devices play a key role in eldercare, healthcare or sportswear applications. Smart objects push their measures to a communicating hub, possibly connected to the Internet.

Recently, IEEE802.15.4-TSCH was proposed to set up an industrial wireless sensor network [START_REF]IEEE Standard for Local and metropolitan area networks-Part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs) Amendment 1: MAC sublayer. IEEE Std[END_REF]. An FTDMA schedule is adopted, where each transmitter receives an amount of bandwidth during which it is authorized to transmit. The schedule may be constructed to avoid any interfering transmissions so that the transmitters just have to transmit their frames, without any contention resolution mechanism. Besides, TSCH uses slow channel hopping to make the transmissions more reliable and robust to extern interference. TSCH is consequently able to guarantee a schedule-free collision, and to maximize the sleeping time of each device. This standard is particularly accurate for many M2M applications in low power lossy networks.

Because of the very large variety of applications, we will surely face with very dense deployments of independent networks. Unfortunately, most of the standards use the unlicensed ISM band: these interfering deployments will possibly create many collisions, wasting bandwidth and energy. We have on the contrary to propose cooperative protocols, able to harmoniously and fairly distribute the bandwidth among each other.

While most of the protocols are evaluated individually, their performance in isolation may be very different when many networks interfere. Thus, we have to identify the pathological situations and to predict the performance decrease. Interference among different technologies have been already studied in the past [START_REF] Liang | Surviving wi-fi interference in low power ZigBee networks[END_REF], [START_REF] Hermans | Sonic: classifying interference in 802.15. 4 sensor networks[END_REF]. In particular, a survey presented the different strategies to deal with co-existing networks [START_REF] Hayajneh | A survey of wireless technologies coexistence in WBAN: analysis and open research issues[END_REF].

To the best of our knowledge, we present here the first paper to study quantitatively the impact of interfering IEEE802.15.4-TSCH networks. The channel hopping approach, paired with a deterministic TDMA schedule makes these networks particular: because a node does not sense the medium before its transmission, an interfering node cannot even be detected. We propose consequently to adopt a systematical approach to quantify the impact of co-located networks, and to give insights on the solutions to re-compute the schedules to limit the number of collisions.

The contributions of this paper are threefold: 1) we provide a theoretical analysis to quantify the amount of collisions, depending on the clock drifts and the load pressure. This analysis allows to predict the performance decrease, depending on the number of networks, and the traffic pressure; 2) we experimentally characterize the impact on the reliability when several networks are able to operate synchronously. This represents an optimistic case, where colocated networks are able to cooperate; 3) we experimentally study the impact on performance when several networks are not synchronized and use a random or a static assignment, depicting the classical scenario of different un-cooperating instances.

II. RELATED WORK AND TECHNICAL BACKGROUND

Since many technologies use unlicensed bands, co-located networks must share fairly the bandwidth. In particular, Body Area Networks require to have co-existing and interfering single hop networks [START_REF] Hayajneh | A survey of wireless technologies coexistence in WBAN: analysis and open research issues[END_REF].

A. Multi-Technology Coexistence

Several papers focused on the co-existence between Wifi and IEEE 802.15.4 (Zigbee). Petrova et al. studied the impact of the packet size, the packet rate and the SINR on the packet losses for co-located IEEE 802.11 and Bluetooth networks [START_REF] Petrova | Performance study of ieee 802.15.4 using measurements and simulations[END_REF] Angrisani et al. adopted a similar approach to study the coexistence between IEEE 802.11 and IEEE 8021.5.4 [START_REF] Angrisani | Experimental study of coexistence issues between ieee 802.11b and ieee 802.15.4 wireless networks. Instrumentation and Measurement[END_REF]. Liang et al. [START_REF] Liang | Surviving wi-fi interference in low power ZigBee networks[END_REF] studied experimentally the localization of errors when Wifi and Zigbee interfere. They remarked that most colliding bits occur at the beginning of the frame, and propose to use error codes to make the transmissions more reliable.

Hermans et al. classified the source of interference for a IEEE802.15.4 network [START_REF] Hermans | Sonic: classifying interference in 802.15. 4 sensor networks[END_REF]. The authors proposed a method to identify the source of interference to adopt an accurate countermeasure strategy.

In this paper, we focused rather on the co-existence of multiple networks using the IEEE802. [START_REF] Iraqi | Prevention of collisions among two Wireless Personal Area Networks[END_REF].

To reduce this impact, Sun et al. proposed to listen beacons from neighboring BANs and to adapt the schedule to limit the number of collisions [START_REF] Sun | A lightweight inter-user interference mitigation method in body sensor networks[END_REF]. DynMAC proposes to have a central controller which computes a centralized schedule [START_REF] Luiz | DynMAC: A resistant MAC protocol to coexistence in wireless sensor networks[END_REF]. The authors assume all the instances are owned by the same entity, and that interferences are a priori known. All these solutions assume implicitly the different networks are synchronized, else the different schedule may suffer from clock drifts and may create collisions.

C. IEEE 802.15.4-TSCH IEEE802.15.4e has proposed the TSCH mode for industrial wireless sensor networks [START_REF]IEEE Standard for Local and metropolitan area networks-Part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs) Amendment 1: MAC sublayer. IEEE Std[END_REF]. To improve the reliability while maximizing energy savings, the network maintains a schedule, repeated periodically.

TSCH uses a slotframe structure, constituted by a collection of timeslots. The slotframe length is configurable. The obtention of the schedule is out of the scope of the standard.

Since TSCH adopts a TDMA approach, all the nodes must be synchronized. Actually, a node computes the difference between the actual and the expected transmission time of its synchronizing parent. Thus, it can readjust its clock for each transmission, maintaining a sufficiently tight synchronization.

At the beginning of each slot, a node knows if it has to stay awake to receive or transmit a packet or if it may sleep to save its energy. A slot can be either dedicated (without contention) or shared (with a CSMA-CA mechanism to solve the conflicts between the contenders).

To improve the reliability, TSCH proposes to implement a channel hopping scheme. To each transmission opportunity is attached a channel offset. In the TSCH jargon, a cell is a pair of timeslot and channel offset. The channel offset is translated into a frequency to actually use at the beginning of each timeslot:

f req = (ASN + ch of f set) mod 16 ( 1
)
where ASN is the absolute sequence number, ch of f set is the channel offset assigned to this cell in the node's schedule, and mod is the modulo operator. If the number of channels and the slotframe length are mutually prime, we guarantee the same cell will use different frequencies in consecutive slotframes. Let's consider 3 nodes (B, C, D) which transmit data to the border router (A) (cf. Fig. 1). Some shared slots (in orange) are dedicated for control packets on the channel offset 0 at the beginning of the slotframe. Because of the half duplex condition, all the links must be scheduled during different timeslots since they have a node in common (A). For instance, two cells are reserved for the transmissions from B to A.

While the common schedule avoids the collisions among the nodes inside a given TSCH network, co-located TSCH networks may collide with each other. We propose here to quantify this problem.

D. 6tisch

6tisch [START_REF] Palattella | Standardized protocol stack for the internet of (important) things[END_REF] proposes a set of protocols to make the glue between IPv6 (6LoWPAN, CoAP, RPL) and TSCH. It relies on RPL to bootstrap the network, constructing a bidirectional route to the border router (i.e. the sink).

On the Fly Scheduling (OTF) is in charge of monitoring the flows forwarded by a node, and to ask 6top to reserve more cells if the bandwidth is not sufficient. Then, 6top either asks a central controller (the PCE) for a new cell or negotiate directly with the given neighbor.

III. THEORETICAL ANALYSIS OF THE IMPACT ON RELIABILITY WITH A RANDOM SCHEDULING

We aim here at quantifying analytically the collisions created by colocated networks. We consider the cells are assigned randomly to each device by the Path Computation Element (PCE) to minimize the probability of collision. When having co-located networks, a random strategy is more efficient to avoid repetitive collisions. Since both instances adopt the same strategy, they should avoid assigning the same colliding cells.

For the sake of simplicity, we assume the networks are colocated: any pair of transmitters (from any TSCH instance) collides for sure. We also assume that a collision occurs if the timeslots of the transmitters overlap, even partly, e.g. packets with the largest length are transmitted and fill the timeslot.

We consider the following scenarios: Synchronized networks represent the most optimistic scenario.

We assume we have an extern source of synchronization, and both TSCH instances use the same slotframe structure (i.e. length, number of shared cells). We may obtain this performance if we are able to introduce cooperation between these instances (i.e. implicit or explicit resynchronization); Asynchronous networks represent the most common scenario, where several instances are colocated but don't cooperate with each other. They have not the same ASN, and present clock drifts between the different instances. In particular, some cells may collide only in some of the slotframes (depending on their clock drifts).

A. Synchronized Instances

Let's consider two TSCH networks are co-located but they are synchronized. This means that if they use the same cells, they will collide in every slotframe.

We consider a set S coloc of colocated TSCH instances (cf. Table . I for the notation). The instance i has a set C(i) of dedicated cells allocated for its unicast transmissions.

We focus on the collisions among dedicated cells. Let's consider a cell c randomly chosen. Because the cells are assigned randomly, the collisions may occur during the dedicated part (shared cells have not to be considered). Thus, the probability that the instance i chose it for any of its unicast transmissions is:

P sel sync (i) = |C(i)| (SLength -N shared ) * N chof f set (2)
Let's now compute the collision probability. We consider the TSCH instance i. The probability that one of its cells was also chosen by any interfering instance is consequently:

P coll sync (i) = 1 - k∈S coloc -{i} (1 -P sel sync (k)) (3)
Finally the number of wasted cells for the instance i is: This waste represents actually the amount of energy wasted by collisions (and the loss of radio spectrum).

Loss sync (i) = P coll sync * |C(i)| (4)
a) Numerical Results: In Figure 2, we evaluated analytically the impact of dense deployment and duty cycle on the network performance. We can remark that if the number of networks exceeds 15 and we use more then 50 dedicated cells, half of the packets will be lost. Thus, collisions and interference may arise mainly among very dense deployments and for large duty cycle ratio.

B. Asynchronous Instances

We now consider the case of several TSCH instances, which behave independently, i.e. not synchronized. Since the different instances derive in time, the collisions are time-variant. If initially two cells from two different instances are not sufficiently separated, the clock drifts may be sufficient to provoke a collision.

Let's denote by ∆ clock-max the maximum clock drift per second. Two instances derive after the time T by:

T * ∆ clock-max (5)
The crystal oscillator of MSP430 motes presents a typical accuracy of 30ppm [START_REF] Chang | Adaptive synchronization in multi-hop {TSCH} networks[END_REF]. Thus, ∆ clock is at most 30 µs The actual time difference between two instances will be comprised after e.g. 10 minutes between -36ms and +36ms (i.e. approx. 2 timeslots by default). The probability of collision compared to the synchronous case (eq. 3) must consequently take into account this clock drift.

Without loss of generality, we fix now the reference clock as the clock of the first TSCH instance. The instance i after the time T has a timeslot difference compared to the reference clock:

∆ tslot (i, T ) ≤ 1+ M in N dedicated , T * ∆ clock-max T tslot (6)
By definition, ∆ tslot (1, * ) = 0 Let's consider a cell c randomly chosen. The probability that this cell collides during the time T for at least one transmission of the instance i depends on the clock drifts. More precisely, it depends on the number of timeslots swept by this clock drift. Besides, since the slotframes are not required to be aligned, a collision may arise with any cell of the slotframe. Thus, the probability that at least one cell of the instance i collides with the cell c is:

P sel async (i, T ) = 1 -1 - ∆ tslot (i, T ) N dedicated * N chof f set |C(i)| (7)
The collision probability is consequently similar to the eq. 3 and 4, replacing just P sel sync (k) by P sel async (k). of collisions for the asynchronous case. The collision probability (Fig. 3) is clearly larger than in the synchronous case. These collisions have a strong impact on the reliability: many packets are dropped. Worse, packet drops occur in consecutive slotframes (until the clock drift is superior than the timeslot duration). Thus, an application may suffer from temporary blackouts, very prejudicial for many applications.

IV. EXPERIMENTAL SETUP TO EVALUATE THE IMPACT OF INTERFERENCE

A. Experimental platform:

We used for our experiments the FIT-IoT lab platform (https://www.iot-lab.info/), and in particular the Grenoble indoor testbed, where motes are placed in corridors (false ceiling and floor). The testbed comprises motes based on a STM32 (ARM Cortex M3) micro-controller (ST2M32F103REY). Each mote embeds a AT86RF231 radio chipset, offering an IEEE 802.15.4 compliant PHY layer.

We used the openWSN (https://openwsn.atlassian.net/) implementation of the 6tisch stack. It provides an open-source implementation of IEEE802.15.4e-TSCH, 6top, otf, 6LoWPAN, RPL.

B. 6tisch Configuration and Scenarios

The control packets (Enhanced Beacons, DIO and DAO for RPL, and 6top frames) use the shared cells at the beginning of the slotframe, with contention. In particular, unicast frames are retransmitted when no acknowledgement is received. Besides, the shared cells are lightly loaded: DIO are for instance transmitted every 30 seconds, and do not create a high load pressure during the shared cells.

The sensitive traffic uses rather the dedicated cells. We modified the 6tisch protocols to evaluate two scheduling functions: Static scheduling: we mimic a saturated network (i.e. a dedicated cell is always filled by a frame). We implement consequently a backlogged traffic, a packet is generated as soon as the previous one is transmitted. We also deactivated the link-layer retransmissions to have a precise measure of the reliability. Finally, we use a hard-coded schedule (computed offline) to evaluate the impact of repetitive collisions, very prejudicial to industrial applications with high reliability requirements. Dynamic scheduling: each node generates a CBR traffic, with the default value depicted in table II. We use the autonomous distributed version described in [START_REF] Theoleyre | A distributed version of 6tisch for high reliability in self-configured low power lossy networks[END_REF]. To evaluate the robustness of such approach, we authorize the packets to be retransmitted. OTF is in charge of overprovisionning cells to deal with retransmissions. We use the default parameters value as depicted in table II

C. Performance criteria

We instrumented openWSN so that each node reports through its serial port some events. In particular, a node reports when a packet is generated, its destination, its sequence number, etc. We proceed in the same way for each packet received / forwarded by a node. We are consequently able to compute statistics easily, based on all these measures.

We instrumented OpenWSN so that each node reports through its serial port some events. In particular, a node reports when a packet is generated, its destination, its sequence number, etc. We proceed in the same way for each packet received / forwarded by a node. We are consequently able to compute statistics easily, based on all these measures.

We mainly focus on the following metrics of performance: Packet Delivery Ratio (PDR): ratio of the packets received correctly by the border router and the packets generated by the source. Number of dedicated cells: we measure for the dynamic scheduling scenario the number of dedicated cells reserved by OTF. A large number of cells means that more retransmissions are sometimes required, reflecting a large number of collisions. Mechanically, the energy consumption is increased and the network capacity is reduced. We systematically plot the 95% confidence intervals.

V. SYNCHRONIZED NETWORKS

We first mimic several co-located networks which are mutually synchronized (i.e. a single root serves as time reference). We aim here at evaluating the impact of interference when we are able to make the networks cooperate, with an explicit or implicit synchronization: this represents an ideal scenario; All the instances use the same slotframe size, and the shared cells are aligned.

A. Static scheduling -2 concurrent interfering instances

We simulate here a scenario where two interfering nodes reserved the same dedicated cells and their instances are synchronized. Since we have backlogged traffic, we aim here at measuring the ability of the system to capture the strongest signal.

We measured first the packet delivery ratio when the source and the sink are progressively separated (Fig. 4). We disabled here the retransmission mechanism to interpret more easily the results. The capture effect allows some packets to be received correctly: when the transmitter is very close to the sink, the number of received packets is maximized, its signal is stronger [START_REF] Gezer | Capture effect in ieee 802.15.4 networks: Modelling and experimentation[END_REF]. When the distance increases, the packet losses also increase. Since the transmissions with the interfering node are synchronized, a large majority of the packets cannot be

B. Random Scheduling -Concurrent Instances

We now measure the packet delivery ratio when we increase the number of TSCH instances, and we let each instance negotiates autonomously the dedicated cells (Fig. 5a)). Retransmissions are here authorized. Even when each instance assigns autonomously the cells, the number of collisions is limited, and the reliability is high. We achieve an almost 100% delivery ratio even with 4 interfering instances. Unfortunately, the PDR significantly falls when more than 12 nodes are interfering: too many collisions occur, even with 16 different channels. More collisions means also that the packets tend to stay longer in the buffers, triggering the reservations of additional dedicated cells for the retransmissions (Fig. 5b).

In conclusion, random scheduling is efficient only when a limited number of contenders exist. Else, the TSCH network becomes quickly unreliable, unable to fulfill its task.

VI. ASYNCHRONOUS NETWORKS

We now focus on inter-WSN interference: several IEEE802.15.4e-TSCH networks are deployed and may interfere with each other. They have distinct border routers, and are not synchronized. We aim here at investigating how co-deployments without cooperation may affect the performance of the TSCH schedule.

A. Static Scheduling

We first simulate dense deployments (e.g. Body Area Networks), and fixed the distance from each transmitter to its border router to 2 meters. We hard-coded the schedule and deactivated the retransmissions to study more accurately the reliability by controlling finely the reserved bandwidth. Since the networks are not synchronized, a pair of dedicated may collide in some of the slotframes, depending on the clock drifts. We first measured the packet delivery ratio (fig. 7). When one interfering network is present, the number of collisions is very reduced, almost 100% of the packets are correctly delivered. However, the reliability decreases very quickly when more than 2 interfering networks exist. For instance, 4 interfering TSCH instances create many collisions, even if each of them has one unique dedicated cell to transmit data packets. In that case, only 70% of the packets are delivered correctly. We can verify that the packet delivery ratio is significantly reduced compared to the cooperative scenario where the TSCH instances are synchronized (Fig. 5a). Indeed, the collisions may arise between a pair of interfering networks even if the cells partially overlap. Besides, the number of collisions for a given cell varies over the time. Thus, a dedicated cell may suffer from a temporary blackout because of an interfering network.

In conclusion, dense deployments are only acceptable for very low duty cycles, with a very small quantity of traffic to forward. Else, the collisions become predominant.

B. Random Scheduling

We mesure in this scenario the performance obtained when several instances operate entirely independently (i.e. not synchronized), and reserve on-demand the dedicated cells autonomously. To limit the impact of the signal strength, all the transmitters are placed 2 meters far from their border router (sink). Figure 6a illustrates the packet delivery ratio: The reliability quickly decreases, and is much lower than when the instances are synchronized with each other. In the same way, the number of cells to reserve is much higher (fig. 6b). With 8 instances, we need on average 6 dedicated cells when the instances are synchronized, and 9 cells (+50%) when they operate asynchronously.

We also measured the dynamic of the network, by reporting the packet losses during time intervals along the experiments (fig. 8). We fix the inter packet time to the slotframe length (1.515 s) and forbid any retransmission to be able to track accurately the packet losses. We can verify that the network spends much time to find an accurate schedule: after an ASN of 14,000, the schedule is now correct and no cell is colliding. Unfortunately, clock drifts quickly make other cells collide, and packets are dropped. In conclusion, adapting the schedule is expensive and useless in unsynchronized TSCH instances.

VII. CONCLUSION

In this paper, we investigated analytically and experimentally the impact of several co-located instances of IEEE802.15.4e-TSCH networks. The collisions may be very prejudicial since they are repetitive: a node doesn't execute any contention resolution mechanism, and all the packets which are transmitted during a colliding cell are lost. If the different networks are able to be synchronized, the collisions are unfrequent. The networks are able to provide a vey high reliability, even when the cells are randomly and autonomously allocated. When the different TSCH networks are not able to be synchronized, the number of collisions is significantly larger. Indeed, clock drifts make the collisions time-variant: one cell may be colliding only during some slotframes. Besides, it is sufficient to have partially overlapping cells to make them collide. As soon as the deployment becomes dense (more than 7 nodes), collisions begin to be predominant. In the future work, we plan to propose mechanisms to detect co-located networks. We aim at proposing a mechanism to re-synchronize either explicitly or implicitly several instances to avoid clock drifts and maintain the performance predictable. We will also propose mechanisms to detect and solve the collisions, without an explicit coordination between the different PCE.

Fig. 1 :

 1 Fig. 1: Schedule in a IEEE802.15.4-TSCH network -illustration with 3 nodes and one border router

1Fig. 2 :1Fig. 3 :

 23 Fig. 2: Collisions among different synchronized instances

  amount

Fig. 4 :

 4 Fig. 4: PDR using synchronized networks with static scheduling -illustration with two interferers separated by 2 meters

Fig. 5 :

 5 Fig.5: Performance of synchronized networks with random Scheduling -each node is separated by two meters to its sink

Fig. 6 :Fig. 7 :

 67 Fig.6: Performance of unsynchronized networks with random Scheduling-distance between co-located networks=2m

Fig. 8 :

 8 Fig. 8: Loss distribution considering two co-located networks with Random Scheduling -illustration for an experience (15 minutes) with 2 networks of 1 node and 1 sink

  15.4-TSCH standard, which does not use CSMA-CA for all the transmissions.

	B. Coexistence of IEEE802.15.4 networks
	While IEEE802.15.4-2006 proposed two different modes,
	only the beacon-enabled mode enables energy savings in
	low power lossy networks. In this mode, beacons maintain
	the synchronization. However, collisions are very frequent,
	even with one single IEEE802.15.4-2006 instance [8]. Iraqi
	et al. also evaluated the number of collisions when different
	IEEE802.15.4-2006 networks use different parameters (super-
	frame duration, and beacon periods)

TABLE I :

 I Notation

	S coloc	set of co-located TSCH instances
	C(i)	set of dedicated cells assigned to the instance i
	N chof f set	number of channel offsets
	N shared	number of shared cells at the beginning of the slotframe
	N dedicated	number of dedicated cells
		(=SlotF rame Length -N shared )
	SLength	slotframe length (by default 101 in 6Tisch)
	∆ clock-max	maximum clock drift
	∆ tslot (i, j)	the drift in timeslots between two instances i and j
	T tslot	Timeslot duration (by default 15ms)

ACKNOWLEDGMENT

This research was supported by the ICube (University of Strasbourg) project SemSeN .


Inès Hosni
email: ines.hosni@hotmail.fr

Fabrice Théoleyre
email: theoleyre@unistra.fr

Noureddine Hamdi
email: noureddine.hamdi@ept.rnu.tn

Localized Scheduling for End-to-End Delay Constrained Low Power Lossy Networks with 6TiSCH

Keywords: distributed scheduling, end-to-end delay, IEEE 802.15.4e-TSCH, 6TiSCH

The IoT expects to exploit IEEE802.15.4e-TSCH, designed for wireless industrial sensor networks. This standard relies on techniques such as channel hopping and bandwidth reservation to ensure both energy savings and reliable transmissions. The 6TiSCH working group currently proposes to exploit the RPL routing protocol on top of the IEEE802.15.4-2012-TSCH layer. Since many applications may require low end-to-end delay (e.g. alarms), we propose here a distributed algorithm to schedule the transmissions while upper bounding the end-to-end delay. Our strategy is based on stratums to reserve time-bands for each depth in the routing structure constructed by RPL. By allocating a sufficient number of timeslots for the possible retransmissions, we guarantee that any packet is delivered during one single slotframe, wherever the source is located. Experiments on a large scale testbed prove the relevance of this approach to reduce the end-to-end delay while minimizing the number of collisions, prejudicial to the reliability in multihop networks.

I. INTRODUCTION

The IEEE802.15 working group has proposed the IEEE802.15.4e amendment [1]. In particular, the TSCH mode aims at improving the reliability for industrial sensor networks in noisy environments. A common schedule aims at reserving a certain amount of bandwidth for each flow, and channel hopping aims at defeating narrow band noise. This standard is particularly accurate for the Internet of Things, where devices transmit periodically their measures to the Internet, through a border router [START_REF] Palattella | Standardized protocol stack for the internet of (important) things[END_REF].

Nodes maintain a slotframe structure, i.e. a sequence of timeslots which repeats over time. Then, the schedule specifies the action of each node during each timeslot. At the beginning of a slot, a node either sleeps or turns its radio on to receive or transmit a frame. By appropriately selecting the set of active nodes during a timeslot, we can avoid the collisions.

However, the current stack of protocols for the Internet was not designed initially to cope with a MAC layer based on reservations. Thus, the 6TiSCH [START_REF]6tisch: Ipv6 over the tsch mode of ieee[END_REF] working group aims at defining a set of protocols to fill the gap between the Link and Network layers. While RPL [START_REF] Winter | Rpl: Ipv6 routing protocol for low-power and lossy networks[END_REF] constructs the end to end routes and maintains the control plane, 6top [START_REF] Wang | 6tisch operation sublayer (6top) interface. draft[END_REF] reserves the transmission opportunities between a pair of neighbors.

To assign the resource for each packet is currently a very challenging objective: 6top has to define which cell has to be used for each flow, along each hop from the source to the border router. Scheduling in multihop wireless networks has already been widely studied in the literature [START_REF] Pister | Tsmp: Time synchronized mesh protocol[END_REF], [START_REF] Tsitsiklis | On the power of (even a little) centralization in distributed processing[END_REF], [START_REF] Palattella | On optimal scheduling in duty-cycled industrial iot applications using IEEE802.15.4e[END_REF]. Some solutions also proposed distributed algorithms adapted for channel hopping [START_REF] Tinka | A decentralized scheduling algorithm for time synchronized channel hopping[END_REF] or TSCH networks [START_REF] Accettura | Decentralized traffic aware scheduling for multi-hop low power lossy networks in the internet of things[END_REF].

In this paper, we present a distributed scheduling solution to reduce the end-to-end delay. Intuitively, we should select consecutive timeslots along the route to reduce the end-toend delay. However, we must also take into account the link reliability: retransmissions may impact negatively the delay if they are not properly scheduled.

We propose here a distributed scheduling based on stratums: all the nodes for a given depth own to the same stratum, and all their transmissions are scheduled in the same time-frequency block (a band). These bands should be carefully dimensioned to avoid the funneling effect [START_REF] Wan | Siphon: Overload traffic management using multi-radio virtual sinks in sensor networks[END_REF]. Besides, we propose to reuse the On The Fly scheduling (OTF) mechanism [START_REF] Dujovne | 6tisch onthe-fly scheduling[END_REF]. When a node has too much traffic to forward, it negotiates with its parent additional timeslots, picked in the accurate band. Scheduling all the retransmissions in the same band allows the end-to-end delay to be contained.

To the best of our knowledge, we propose the first algorithm to assign reactively the cells in 6TiSCH, with uniquely localized information, and upper-bounding the end-to-end delay.

The contribution of this paper is threefold: 1) we present a distributed scheduling algorithm which reduces the end-to-end delay by organizing the network in stratums. A packet should be delivered before the end of the slotframe; 2) we explain how to implement this scheduling algorithm in the 6TiSCH stack, reserving new cells when a low link quality is measured locally. Our solution is entirely decentralized and reactive; 3) we provide experimental results conducted on the FIT-IoT Lab platform to validate our approach. At the beginning of each timeslot, a device examines the schedule to know if it has to wake-up to transmit or receive a packet. A timeslot can be either dedicated (without contention) or shared (with a slotted CSMA-CA mechanism to solve the conflicts between the contenders). During an incoming cell, a node waits for a reception, while it is in transmission mode during the outgoing cell. When a node is neither receiver nor transmitter, it turns its radio off.

To improve the reliability, TSCH proposes to implement channel hopping. In the TSCH jargon, a cell is a pair of timeslot and channel offset. The channel offset is translated into a frequency to actually use during a given timeslot:

freq = (ASN + ch of f set)%16 (1)
where ASN (absolute sequence number) counts the number of timeslots since the beginning, and ch of f set is the channel offset assigned to this cell in the schedule. Let's consider the schedule illustrated in figure 1. We have 1 shared cell at the beginning of the slotframe, using the channel offset 0. The shared cell is typically used for control traffic (i.e. new reservations, routing control packets, etc.). The other cells are dedicated: only the owners of a cell can transmit a packet, without contention. Each DODAG link has one or several cells to forward the packets to its parent. The link A !B (pink) reserved for instance two dedicated cells either because it has many packets to forward, or because retransmissions are expected.

B. 6TiSCH

The 6TiSCH IETF working group designs the protocols to operate IPv6 (6LoWPAN) over a reservation based MAC layer (IEEE802.15.4-TSCH). 6TiSCH introduces the concept of track to reserve an amount of dedicated cells for a particular flow [START_REF] Chen | Use cases and requirements for using track in 6tisch networks[END_REF]. Hop by hop, each intermediary node inserts in its schedule some cells for each non best effort flow (i.e. track instance 6 = 0). Label switching is implicit: a node knows the track associated to an incoming cell, extracted directly from the schedule. Thus, it just has to forward this packet in an outgoing cell with the same track id.

6top defines how a node may negotiate a cell with one neighbor: the enquirer specifies a list of available < timeslot, channel of f set > and the number of cells it asks for [START_REF] Wang | 6tisch operation sublayer (6top) interface. draft[END_REF]. The neighbor will accept the request if these cells are available also in its schedule: it sends an Information Element to notify the enquirer. However, 6top does not define which cells should be selected.

Let's consider the figure 1 which illustrates a possible schedule with 4 different tracks. We see that the link B ! A supports two tracks with respectively the source B (in pink) and the source D (in gray). Since each track has dedicated resource, we guarantee traffic isolation: the packets of D do not impact the traffic of B. For the flow (D ! A), the incoming cell in B is located after the outgoing cell. Thus, B has to buffer the corresponding packet during the whole slotframe, increasing drastically the end-to-end delay.

In this paper, we use the 6TiSCH stack to reserve reactively the cells for each track: each flow reserves hop-by-bop its own dedicated cells, while taking care of limiting the end-to-end delay.

C. Traffic Aware Scheduling Algorithm

To assign the resource for each packet is currently a very challenging objective: 6top has to define which cell should be used for each flow, along each hop of the route to the border router. While 6TiSCH defines how the cells are negotiated (with the 6top protocol), any scheduling algorithm may be actually implemented. We propose here a distributed scheduling algorithm adapted to 6top.

Ghosh et al. [START_REF] Ghosh | Multi-channel scheduling algorithms for fast aggregated convergecast in sensor networks[END_REF] proposed to minimize the schedule length in a multichannel TDMA environment. Tsitsiklis et al. [START_REF] Tsitsiklis | On the power of (even a little) centralization in distributed processing[END_REF] studied the tradeoff between a centralized and a distributed scheduling. By adopting a queue theory based approach, they demonstrated a centralized algorithm is more efficient. TASA proposed to construct a centralized scheduling for a multihop IEEE802.15.4-TSCH network [START_REF] Palattella | On optimal scheduling in duty-cycled industrial iot applications using IEEE802.15.4e[END_REF]. Yigit et al. [15] studied the impact of routing on the scheduling: using unreliable links increases the number of timeslots required to achieve a minimum reliability. However, these centralized approaches assume the radio topology is known a priori: the protocol must know precisely the group of interfering links. These approaches are well suited for industrial networks with strict requirements on reliability and delay.

DeTAS proposed a decentralized version of TASA [START_REF] Accettura | Decentralized traffic aware scheduling for multi-hop low power lossy networks in the internet of things[END_REF]: the children of the border routers collect the information and

TABLE I NOTATIONS

compute the schedule of their subtree (called micro-schedules). Finally, the micro-schedules are re-arranged into a globally acceptable schedule. Thus, the scheduling is still concentrated in a few nodes, which are aware of the radio interference. Phung et al. [START_REF] Phung | Schedule-based multi-channel communication in wireless sensor networks: A complete design and performance evaluation[END_REF] proposed to use a Reinforcement Learning based scheduling algorithm to cope with a variable traffic. However, the authors do not propose to use dedicated cells: the nodes have always to execute a CSMA-CA phase before transmitting their packets. We propose rather an approach similar to Z-MAC [START_REF] Rhee | Z-mac: A hybrid mac for wireless sensor networks[END_REF] where a pair of nodes negotiate locally the timeslots they will use further. However, Z-MAC does not exploit a fully synchronized FTDMA network.

III. PROBLEM STATEMENT

We consider a model designed for Low Power Lossy networks (LLN) organized by RPL in a single DODAG (Destination Oriented Directed Acyclic Graph), anchored in a border router. Each node maintains its rank denoting its virtual distance from the border router. Typically, the rank can be the average cumulative number of transmissions (ETX) along the path to the border router [START_REF] Winter | Rpl: Ipv6 routing protocol for low-power and lossy networks[END_REF].

We consider here the standard version of RPL, where a node uses only its preferred parent to route its packets. Thus, a node has to negotiate a set of cells with its parent, next hop to the border router. The traffic may be constant or variable, and we use tracks to reserve dedicated cells for each flow. When the traffic is sporadic, a dedicated cell is used infrequently (e.g. one every 10 slotframes).

TASA [START_REF] Accettura | Decentralized traffic aware scheduling for multi-hop low power lossy networks in the internet of things[END_REF] is particularly efficient to schedule in a centralized manner the cells while minimizing the end-to-end delay. However, centralized scheduling deals inefficiently with variability: when a new node or flow is inserted, the schedule must be updated. In the same way, bad radio links require to over-provision cells for retransmissions. To react quickly to changes, we propose here a localized scheduling algorithm, robust to any change (traffic, reliability, topology).

A. Large end-to-end Delay with a Random Distributed Scheduling

We first compute here the average end-to-end delay we may obtain with a random scheduling algorithm. More precisely, when a pair of nodes has to negotiate a cell, the transmitter selects randomly a free timeslot and channel offset. Then, it sends a request to the receiver to verify if this cell is also free for the other side. The process reiterates until a common free cell is selected. Without loss of generality, let's assume the first hop has selected the timeslot 0. A packet has to be enqueued until the next outgoing cell, and these cells are uniformly distributed in the slotframe. Besides, a packet may be received uniformly in the slotframe. Thus, it needs to wait on average:

OutCell delay = SF length ⇤ T slot 2 ⇤ nbCellsOut(A, B) (2)
with SF length being the length of the slotframe, T slot the duration of a timeslot and nbCellsOut(A, B) the number of outgoing cells.

Besides, a packet needs possibly several retransmissions if the link is unreliable. Precisely, it needs on average ETX transmissions [START_REF] De Couto | A high-throughput path metric for multi-hop wireless routing[END_REF]: the average number of transmissions from A to B before receiving an acknowledgement.

Finally, the packet is enqueued during:

hop delay(A ! B) = SF length ⇤ T slot 2 ⇤ nbCellsOut(A, B) ⇤ ET X(A, B) (3)
with ET X(A, B) the ETX from A to B.

Since we assume a packet may be generated at anytime, the end-to-end delay for a packet along the route p is finally:

E2E Delay(p) = SF length ⇤ T slot |p| 1 X i=1 ET X(N i , N i+1 ) 2 ⇤ nbCellsOut(N i , N i+1 ) (4)
Figure 2 illustrates the end-to-end delay obtained with a typical slotframe of 1001 slots. This slotframe models typically an application where a flow has to send one packet every 15 seconds.

In conclusion, we may reduce the end-to-end delay by allocating more cells. However, this over-provisioning increases both the number of collisions and the energy consumption.

Besides, the end-to-end delay increases linearly with the network diameter. While we implemented this solution as a comparison purpose, we have to propose a specific smarter solution to reduce the end-to-end delay.

IV. DISTRIBUTED STRATUM SCHEDULING

We propose here a localized scheduling to be robust to any change (topology, traffic, routing paths). We are convinced a distributed schedule, reactively computed, may cover the needs of various applications (e.g. smart homes).

We propose to guarantee a maximum end-to-end delay equal to the slotframe duration: any packet which is generated at the beginning of the slotframe should be delivered before the end of the slotframe. By fixing the slotframe length, the network administrator is able to also fix the maximum delay.

We divide the network in stratums: all the nodes which are k hops far from the border router constitute the stratum k. We denote by depth the hop distance from the border router. Thus, each node includes in its DIO (DODAG Information Object, a RPL control packet) a field denoting its depth.

We aim now at assigning a time-frequency block (a band) to each stratum. All the nodes in the stratum k must pick their timeslots in the block k. We construct a global schedule in which the blocks from contiguous stratums are consecutive. In this way, we guarantee a packet is delivered before the end of the slotframe. Besides, our algorithm is localized since the stratum is directly determined by the depth.

With On-The-Fly scheduling (OTF), a node will monitor the number of packets to forward. When its traffic exceeds its outgoing capacity, OTF asks 6top to reserve a new cell.

We will now to define which block will be assigned to each stratum.

A. Sizing the number of stratums and their width

We consider that the nodes are uniformly distributed in a given area, and all the nodes generate the same amount of traffic. We denote by block all the nodes which are equidistant (in hops) from the border router. Our algorithm consists in assigning a portion of the schedule to each block.

We will first explain how we assign a schedule to the nodes which are at most d max hops far from the border router. We will explain in the next subsection how frequency re-use allows the other blocks to receive also a non interfering portion of the schedule.

The nodes closest to the border router have more traffic to forward (the so-called funneling effect). Thus, the block i should be larger than the block i+1. We propose consequently to use a recursive division: the block i is twice as large as the block i + 1.

If the traffic is not uniformly distributed in the network, we may divide differently the global schedule into blocks. In the extreme case, if all the packets are generated by the nodes d max hops far, all the blocks should have the same size.

B. Frequency re-use

Many interfering models consider interference may be neglected when two nodes are sufficiently far [START_REF] Shi | How to correctly use the protocol interference model for multi-hop wireless networks[END_REF]. Let's denote by d max the number of hops after which we may assume no interference arises.

Practically, we fix the number of blocks to be equal to d max . A node in the stratum k will use the block k mod (d max ), with mod () denoting the modulo operator. Thus, nodes which are more than d max hops far from the border router re-use one already allocated cell, without creating interference since we consider they are sufficiently far.

0 1/2 1/4 1/

V. TRAFFIC ISOLATION WITH 6TISCH

We modified the openwsn (https://openwsn.atlassian.net) implementation of the 6TiSCH stack. It provides an opensource implementation of the whole 6TiSCH protocol's family (IEEE802.15.4-tsch, RPL, 6LoWPAN, CoAP) .

We modified the current openwsn implementation to cope with tracks. The best-effort track uses shared slots (with contention) for the RPL control packets (e.g. DIO, DAO) and 6top control packets (to negotiate the dedicated cells to use). Besides, each packet generated by an application is attached to a particular track (a track id of 16 bits, and a track owner of 64 bits): a flow reserves hop-by-hop its own dedicated resource, with dedicated slots without contention.

On-The-Fly scheduling is in charge of deciding how many cells to allocate for each radio link. We propose here a simple version of OTF: when the number of packets in the queue for a given track exceeds the number of outgoing cells for this track in the slotframe, OTF asks 6top to reserve some cells. More precisely, 6top has to reserve the difference between the number of packets and the number of outgoing cells.

6top then engages a bidirectional negotiation, as specified by 6TiSCH. A Link-Request is transmitted to the parent with the cells selected by the scheduling algorithm. Then, the parent replies with a Link-reply to accept or reject this allocation, depending of the availability of these cells in its schedule.

We propose here a reactive approach, in which OTF automatically adjusts the number of cells according to the reliability of the link. More retransmissions mean the queue becomes overfilled, requiring new outgoing cells.

VI. EXPERIMENTAL RESULTS

To evaluate thoroughly the behavior of our solution, we used the FIT/IOT-LAB testbed (https://www.iot-lab.info/, cortex-m3 nodes). We fixed the values for each parameter according to table VI, using openwsn modified as described in the previous section. We measured the following metrics:

A. End-to-end Delay

We first measure the end to end delay of the random and stratum strategies (Figure 4). For the nodes which are far from the border router, the end to end delay increases: the packets have to be relayed by intermediary nodes, increasing mechanically the delay. For nodes which are 6 hops far from the border router, the delay of the random strategy may reach almost 4.5 seconds.

In particular, we can verify the delay of the random strategy is proportional to the hop length, validating the equation 4 in section III-A. In other words, the delay is on average 15ms ⇤ SF length 2

⇤ depth if we reserve one outgoing cell for each hop (= 1500ms for nodes which are two hops far from the border router).

On the contrary, the delay of the stratum strategy is not linear: it is rather logarithmic. Indeed, the delay for each hop is directly given by the block length. More precisely, the end-toend delay is the cumulative sum of the block lengths from the

B. Scalability

We also measured the packet delivery ratio when having an increasing number of nodes (Fig. 5). We selected topologies so that we maintain the density constant, increasing the network diameter to evaluate more the scalability than the robustness to high densities. We increased the number of nodes from 5 to 40 with a pitch of 5.

The larger the network is, the lower the packet delivery ratio is: more collisions may arise. The random strategy aims at minimizing the probability of collisions by selecting different timeslots: the PDR is consequently the largest. However, the stratum strategy only slightly impacts the reliability. While we increase slightly the number of collisions because we select a timeslot randomly inside a block, we still achieve a reliability of 95% even with 40 nodes. We consequently divide the maximum end to delay by 4 in the worst case, with a negligible impact on the end-to-end packet delivery ratio.

C. Traffic scalability

We finally increased the traffic pressure to quantify its impact (Figure 6). We represented the boxplot for the packet delivery ratio in function of the inter packet time for data packets generated toward the border router.

More traffic (lower inter packet time) means a lower PDR. We can notice that stratum strategy creates more collisions, explaining the decrease of PDR. The random strategy is more robust to large traffic conditions: the stratum strategy is rather designed for low traffic and low duty cycle ratio scenarios.

D. Energy Savings

The stratum scheduling algorithm is able to provide a low network duty cycle ratio (DCR), computed as the percentage of timeslots during which a node is active (transmitting or receiving data). We can verify that both the random and the stratum strategies achieve a vey low duty cycle ratio (Fig. 7), always below 2% even with 60 nodes. Obviously, the ratio of active timeslots increases when the network has more traffic to forward.

VII. CONCLUSION

The emerging industrial IoT is based on a standard communications stack. IEEE ratified the TSCH-based IEEE802.15.4e MAC to support real-time traffic, with deterministic medium access.

In this paper, we studied in depth the end-to-end delay provided by a TSCH MAC layer. We propose a distributed scheduling based on stratums: the end-to-end delay is upper bounded by the slotframe size, whatever the length of the path to the border router is. This strategy is much more efficient than a random distributed scheduling to upper bound the delay, independent of the hop length, and to deal efficiently with retransmissions caused by unreliable links.

In the future, we plan to propose mechanisms for OTF to predict accurately the number of cells it requires for both sporadic and periodic traffic. We also plan to adapt centralized algorithms to enable local reconfigurations of the schedules when the traffic / topology changes.

Fig. 1 .

 1 Fig. 1. Schedule in a IEEE802.15.4-TSCH network -illustration of a slotframe with 8 timeslots

  ETX value from A to B nbCellsOut(A, B) Number of outgoing cells (transmissions) from A to B SF length Number of cells (i.e. the slotframe length) T slot Timeslot duration (by default 15ms) p = {S..D} path from S to D dmax Maximum hop distance for block re-utilization (i.e. frequency reuse)

Fig. 2 .

 2 Fig.2. End-to-end delay with a slotframe of 1001 timeslots (=15s)

Fig. 3 .

 3 Fig. 3. Division of the schedule into disjoint blocks (4 channel offsets, 8 timeslots)

Fig. 4 .

 4 Fig. 4. End to end delay Vs. number of hops

Fig. 5 .

 5 Fig. 5. Packet delivery ration Vs. number of nodes

Fig. 6 .Fig. 7 .

 67 Fig. 6. Impact of the traffic intensity

  Traffic type, rate CBR, inter packet time= 12s

	Data packet size		127 bytes
	MAC layer		IEEE 802.15.4e-TSCH
	Timeslot duration		15ms
	Slotframe length		101 slots
	Routing protocol		RPL
	Routing metric		ETX
	Hardware		AT86RF231 radio
				STM32F103REY
	dmax	(frequency	reuse	6 hops
	range)
			TABLE II
		PARAMETERS FOR THE EXPERIMENTS

ACKNOWLEDGMENT

This research was supported by the ICube (University of Strasbourg) project SemSeN .


Ronan Le Cointe

Youna Girault

Thierry Morvan

Jean-Baptiste Thibord

Philippe Larroudé

Guillaume Lecuyer

Manuel Plantegenest

David Bouille

Sylvain Poggi

Feeding pests as an IPM strategy: wireworms in conservation agriculture as a case study

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

FEEDING PESTS AS AN IPM STRATEGY Wireworms in conservation agriculture as a case study RONAN LE COINTE [START_REF] Parker | The biology and management of wireworms (Agriotes spp.) on potato with particular reference to the U[END_REF] , YOUNA GIRAULT [START_REF] Traugott | The feeding ecology of elaterid larvae in Central European arable land: New perspectives based on naturally occurring stable isotopes[END_REF] , THIERRY MORVAN (3) , JEAN-BAPTISTE THIBORD [START_REF] Staudacher | Plant diversity affects behavior of generalist root herbivores, reduces crop damage, and enhances crop yield[END_REF] , PHILIPPE LARROUDE [START_REF] Staudacher | Plant diversity affects behavior of generalist root herbivores, reduces crop damage, and enhances crop yield[END_REF] , GUILLAUME LECUYER [START_REF] Parker | The biology and management of wireworms (Agriotes spp.) on potato with particular reference to the U[END_REF] , MANUEL PLANTEGENEST [START_REF] Parker | The biology and management of wireworms (Agriotes spp.) on potato with particular reference to the U[END_REF] , DAVID BOUILLE [START_REF] Traugott | The feeding ecology of elaterid larvae in Central European arable land: New perspectives based on naturally occurring stable isotopes[END_REF] AND SYLVAIN POGGI [START_REF] Parker | The biology and management of wireworms (Agriotes spp.) on potato with particular reference to the U[END_REF] 1-INRAE -IGEPP, Domaine de la motte, BP 35327, 35653 Le Rheu Cedex-France 2-CRAB, 1, L'abbaye Saint Jacques, 35160 Montfort sur Meu -France

• Wireworms (WW) (Fig. 1), the larvae of click beetles (Coleoptera: Elateridae), have been damaging a wide range of crops worldwide since long [1-3]. We have investigated the influence of CA principles on wireworm populations and their harmfulness by addressing the 3 following questions:

1. Does reduced tillage increase WW populations ?

2. Does permanent organic soil cover limit crop damages?

3. How crop diversification and intercropping limit crop damages?

Results (1) Does RT increase WW populations ?

• Long-term experiments : Context

• This system is increasing worldwide as a low-input system.

Reduced Tillage

Direct Seeding

Plow

Results (2)

Does soil cover limit damages on maize? Results (3) Does intercropping limit damages on maize?

Discussion

• Glasshouse experiment :

• The influence on maize damage of two types of soil cover (1) wheat seeding and ( 2) bark mulch was compared to the control (bare soil).

• 2 Agriotes lineatus wireworms aged under 1 year and previously unfed during 4 weeks were placed in 0.25ml pot of a mix of sand and potting soil.

• In treatment 1 (T1) soil was left bare, in T2 9 seeds of wheat were sown and grown, and in T3 soil was covered with bark wood.

• After 14 days, wheat seedlings were cut and maize sown (1 seed per pot)

• 21 days after sowing, seedlings were removed and the presence of symptoms monitored.

• Field experiment :

• The influence on maize damage of wheat intercropping as companion plant was compared to the control (bare soil) and to a chemical treatment (Belem, 13kg/ha).

• The sowing date was May 10 th , 2019 2 &3) demonstrate that reducing tillage increases wireworm populations.

• Our results (Figure 4) show that the soil organic cover protects maize seedlings only when organic matter is fresh. • Our results (Figures 5 and6) show that intercropping protects maize seedlings from wireworms damages.

Fig. 3

 3 Fig. 3. Wireworm infestations after 19 years of reduced tillage and direct seeding compared to plowing (soil samplings)

Fig. 1 .

 1 Fig. 1. Wireworms

Fig. 4 .

 4 Fig. 4. Percentage of maize seedlings damaged by wireworms according to the type of soil cover

Fig. 5 .Fig. 6 .

 56 Fig. 5. Percentage of damaged maize seedlings

•

  Crop damage was assessed on June 11 th , 2019

						Bare	Companion	Belem
						Soil	Plant	Chemical
					Percentage of maize	seedling with damage	Control	Wheat	control
	of maize seedling with	damage	Bare Soil (control)	Wheat Cover Crop	Bark Mulch
	Percentage

• Our results in experimental platform (Figures

Funding

This research was supported by AFB as part of the call on "Sustainable crop protection without neonicotinoids: improving the emergent and opening innovative perspectives" launched by the French Ministries in charge of Ecology (MTES), Agriculture (MAA), Health (MSS) and Research (MESRI). For more information : (https://www6.inra.fr/startaup/)