M.D.; Soyhan Bagci
email: soyhan.bagci@ukb.uni-bonn.de

VMD, PhD Anna M Eis-Hübinger

PhD ; Atteyet

M.D.; F Yassin

M.D.; Arne Simon

MD, PhD a , Peter Bartmann

MD a , Axel R Franz

M.D. Andreas Müller

MD c , Atteyet F Yassin

MD Andreas Mueller

OF VIRAL INTESTINAL INFECTION IN PRETERM AND TERM NEONATES

Keywords: keyword 1: Norovirus keyword 2: Rotavirus keyword 3: Astrovirus keyword 4: Necrotizing enterocolitis keyword 5: Neonates Norovirus, rotavirus, astrovirus, necrotizing enterocolitis, neonates

Objectives: The clinical presentation of the viral enteric pathogens in newborn infants has not been adequately examined. The aim of this study was to evaluate the clinical characteristics of viral intestinal infections in newborn infants. Methods: Clinical data of all term and preterm infants admitted to our tertiary neonatal intensive care unit from 1998 to 2007 with clinical signs of gastroenteritis (GE) or necrotizing enterocolitis (NEC) were retrospectively reviewed and compared between infants with different viral enteric pathogens in stool specimens. Results: In thirty-four infants with signs of GE or NEC, enteropathogenic viruses were found in stool specimens. Rotavirus was detected in 12 cases, of which 2 infants had NEC. Compared with infants with rotavirus or norovirus, infants with astrovirus more frequently suffered from NEC (p<0.05). In addition, an acute systemic inflammatory response was significantly more common in patients with astrovirus infection (astrovirus vs. rotavirus and astrovirus vs. norovirus p<0.01 and p<0.05, respectively). Of 8 children infected with norovirus, one infant had a systemic acute inflammatory response and NEC. Conclusions: This study demonstrates that in newborn infants, intestinal rotavirus, norovirus, and astrovirus infections may be associated with severe illness such as hemorrhagic enteritis resulting in bloody diarrhea or even NEC.

Reviewers' Comment 1: In the Abstract, under the Objectives paragraph it is stated that "The clinical presentation of viral intestinal infections in preterm and term neonates has not been adequately evaluated". This statement is not an objective in itself. It is an observation that could be included as background or as part of the introduction. The aims of the study should be better defined. Answer 1: According the reviewers' suggestions we revised the objectives in the abstract. Because of "200 words-limit in abstract" we revised the abstract, too (all changes made to the manuscript text are underlined).

Reviewers' Comment 2: In the Results section (p.2, line [START_REF] Schreier | Molecular epidemiology of outbreaks of gastroenteritis associated with small round structured viruses in Germany in 1997/98[END_REF] it should be mentioned that enteropathogenic viruses were found in 34 infants out of 220 (15.45%) infants with gastroenteritis (GE) and NEC (nectotizing enterocolitis). Answer 2: According the reviewers' suggestions we changed the sentence as recommended (Page 6, p.2).

Reviewers' Comment 3: Among 112 infants with gastroenteritis, enteric viruses were detected in 22 patients (19.64%), and in 12 cases (11.11%) out of 108 infants with NEC. That means that approximately only in one case out of every 10 infants suffering of NEC was an enteric virus detected. The majority of cases with RV infection (10/12) were mild and self-limiting GE, but 2 preterm infants had signs of NEC. In this study, no enteric viruses were detected among 186 infants with the diagnosis of GE or NEC. Despite these observations, the authors conclude (Abstract, p. 2, line 39) that this study demonstrates that in newborn infants, intestinal rotavirus, norovirus, and astrovirus infections may be associated with severe illness such as hemorrhagic enteritis resulting in bloody diarrhea or even NEC. The important question that needs to be answered is whether this association is significant or not, and this answer is not given. Answer 3: This topic is extensively discussed in the discussion on pages 9 and 10 (p.3, about our patients with HAstV and p.4, about NV).

Reviewers' Comment 4: It is remarkable that the virus most frequently detected in cases of NEC is human astrovirus (9 infants), whereas in only 5 infants with GE was this virus found. This topic was already addressed by the authors of the present manuscript in a previously published paper [START_REF] Bagci | Detection of astrovirus in premature infants with necrotizing enterocolitis[END_REF]: Detection of astrovirus in premature infants with necrotizing enterocolitis. Pediatr Infect Dis J 27:347-50). In fact, 6 infants with NEC and astrovirus infection were already reported in that paper. Answer 4: Our previous publication [START_REF] Bagci | Detection of astrovirus in premature infants with necrotizing enterocolitis[END_REF]: Detection of astrovirus in premature infants with necrotizing enterocolitis. Pediatr Infect Dis J 27:347-50) pointed at the association between HAstV and NEC for the first time. In this study, only patients with NEC were analyzed. In our present study, neonatal characteristics and clinical findings of newborns with enteric viral infection (NEC and GE) are summarized and a statistical analysis according to agents was performed. Therefore, we had to add these 6 patients from our previous study to the present study.

Reviewers' Comment 5: In several sentences it is said that viruses may 'colonize' the gut: "colonization or infection with HAstV" (Abstract, p. 3, line 29), "RV infection or colonization" (Discussion, p. 8, line 29; p. 10, lines 34 and 51). What do the authors mean with viral colonization? In regard to viruses, what is the difference between colonization and infection? Answer 5: The pathogenesis of NEC remains unclear. Several studies have reported that early abnormal bacterial colonization plays a key role in the development of NEC (1,2). But it is still unclear, whether viral colonization of the gastrointestinal tract without cytolysis and cell destruction may play a role in the pathogenesis of NEC in newborn infants. Therefore, we preferred to use "infection or colonization", until we understand the role of enteric viruses in the pathophysiology of NEC.

Reviewers' Comment 6: It is stated that all patients who shared a room with an infected infant were immediately tested for enteric viruses. Were viruses found in asymptomatic infants? Were dual (mixed) viral infections detected? Apparently no adenovirus infections were found. These results should be clearly presented.

Answer 6: According the reviewers' suggestions the following sentences have been added to results (Results, p. 4): "No adenovirus was identified." and "Moreover, RV was detected in the second stool specimen of an infant with HAstV who was admitted to the group of HAstV."

Ms. Ref. No.: EJCMID-D-10-00107

Title: Clinical characteristics of viral intestinal infection in preterm and term neonates Authors: Soyhan Bagci, Anna M. Eis-Hübinger, Atteyet F. Yassin, Arne Simon, Peter Bartmann, Axel R. Franz, Andreas Mueller Dear Sir, We revised our manuscript "Clinical characteristics of viral intestinal infection in preterm and term neonates" according to the reviewers' comments. You may find our comments, additions and answers below (all changes made to the manuscript text are underlined).

Reviewers' Comment 1: In the Abstract, under the Objectives paragraph it is stated that "The clinical presentation of viral intestinal infections in preterm and term neonates has not been adequately evaluated". This statement is not an objective in itself. It is an observation that could be included as background or as part of the introduction. The aims of the study should be better defined. Answer 1: According the reviewers' suggestions we revised the objectives in the abstract. Because of "200 words-limit in abstract" we revised the abstract, too (all changes made to the manuscript text are underlined). were mild and self-limiting GE, but 2 preterm infants had signs of NEC. In this study, no enteric viruses were detected among 186 infants with the diagnosis of GE or NEC. Despite these observations, the authors conclude (Abstract, p. 2, line 39) that this study demonstrates that in newborn infants, intestinal rotavirus, norovirus, and astrovirus infections may be associated with severe illness such as hemorrhagic enteritis resulting in bloody diarrhea or even NEC. The important question that needs to be answered is whether this association is significant or not, and this answer is not given.

Answer 3: This topic is extensively discussed in the discussion on pages 9 and 10 (p.3, about our patients with HAstV and p.4, about NV).

Reviewers' Comment 4: It is remarkable that the virus most frequently detected in cases of NEC is human astrovirus (9 infants), whereas in only 5 infants with GE was this virus found. This topic was already addressed by the authors of the present manuscript in a previously published paper (Bagci et al., 2008: Detection of astrovirus in premature infants with necrotizing enterocolitis. Pediatr Infect Dis J 27:347-50). In fact, 6 infants with NEC and astrovirus infection were already reported in that paper.

Answer 4: Our previous publication [START_REF] Bagci | Detection of astrovirus in premature infants with necrotizing enterocolitis[END_REF]: Detection of astrovirus in premature infants with necrotizing enterocolitis. Pediatr Infect Dis J 27:347-50) pointed at the association between HAstV and NEC for the first time. In this study, only patients with NEC were analyzed. In our present study, neonatal characteristics and clinical findings of newborns with enteric viral infection (NEC and GE) are summarized and a statistical analysis according to agents was performed. Therefore, we had to add these 6 patients from our previous study to the present study. Etiologic studies of acute GE showed that RV is the major cause of clinically severe, epidemic and sporadic viral GE in young children, immunocompromized patients, and in the elderly [1]. NV and HAstV are usually associated with cases of mild and self-limiting GE in children [START_REF] Walter | Astrovirus infection in children[END_REF][START_REF] Patel | Systematic literature review of role of noroviruses in sporadic gastroenteritis[END_REF][START_REF] Simon | Norovirus outbreak in a pediatric oncology unit[END_REF][START_REF] Thornton | Noroviruses: agents in outbreaks of acute gastroenteritis[END_REF].

In contrast to the usually self-limiting course of GE in healthy children, NEC, a major and life-threatening gastrointestinal emergency, has occasionally been reported associated with RV infection or colonization in preterm infants [START_REF] Rotbart | An outbreak of rotavirus-associated neonatal necrotizing enterocolitis[END_REF][START_REF] Sharma | Rotavirus-associated necrotizing enterocolitis: an insight into a potentially preventable disease?[END_REF][START_REF] Herruzo | Identification of risk factors associated with nosocomial infection by rotavirus P4G2, in a neonatal unit of a tertiary-care hospital[END_REF]. Moreover, we have previously shown that colonization or infection with HAstV may also be associated with severe confirmed NEC in preterm infants [START_REF] Bagci | Detection of astrovirus in premature infants with necrotizing enterocolitis[END_REF], and recently, Armbrust et al. [START_REF] Armbrust | Norovirus infections in preterm infants: wide variety of clinical courses[END_REF] reported a NV outbreak in 11 premature infants in a tertiary Neonatal Intensive Care Unit (NICU), of whom 2 developed NEC.

With more sensitive virus identification techniques, viral GE has been increasingly reported in infants, especially in pediatric hospitals and child-care centers. The aim of this retrospective investigation was to evaluate the clinical presentation of viral intestinal infections especially with NV in newborns admitted to a NICU.

METHODS

Medical records of 3402 newborn infants admitted between January 1998 and

December 2007 to a tertiary NICU of the Department of Neonatology, University Hospital of Bonn were retrospectively reviewed for the diagnoses of GE or NEC. As several studies showed the relationship between pathogenic microorganisms and NEC [START_REF] Caplan | New concepts in necrotizing enterocolitis[END_REF] , it has been routine care at our institution during this 10 year period to examine fecal specimens of all infants with one or more acute gastrointestinal symptoms such as abdominal distension, feeding difficulties, increased gastric residuals (> 5 ml/kg per feeding), vomiting, bloody stools, loose stools, or diarrhea by culture for enteric bacterial pathogens, by cell culture test (human foreskin fibroblasts) for Clostridium difficile cytotoxin, and by ELISA or PCR for a series of viral pathogens including RV, AdV, NV, and HAstV. When a new case with viral pathogen was identified, all patients who shared a room with the infected infant were immediately tested. All infants who were diagnosed to have NEC or GE were eligible for analysis. Infants without NEC or GE were excluded from the study if no viral or bacterial pathogens were detected in their stool specimens.

Case Definitions and Laboratory Methods: NEC was staged according to modified

Bell's criteria [START_REF] Bell | Neonatal necrotizing enterocolitis. Therapeutic decisions based upon clinical staging[END_REF], a definite case of NEC (stage ≥ IIA) is an infant with one of the following intestinal or systemic signs: visible blood from rectum, apnoea, shock, hypotension or X-rays with positive signs of pneumatosis intestinalis; a suspected case of NEC (stage I) is a infant with at least two of the following clinical signs: abdominal distension, gastric residual (> 5 ml/kg per feeding), occult blood in stool or a radiological finding of persistent intestinal distension [START_REF] Faustini | An epidemic of gastroenteritis and mild necrotizing enterocolitis in two neonatal units of a University Hospital in Rome, Italy[END_REF].

Although there was no clear definition to differentiate between NEC stage I and GE, we defined viral GE in this study by the presence of diarrhea defined as loose, watery stools that occur more than three times per day for at least three consecutive days and a positive ELISA or RT-PCR for a viral enteric pathogen but negative culture results for bacterial enteric pathogens and Clostridium difficile cytotoxin [START_REF] Faustini | An epidemic of gastroenteritis and mild necrotizing enterocolitis in two neonatal units of a University Hospital in Rome, Italy[END_REF].

From all infant records, that contained the diagnoses GE or NEC with positive ELISA or RT-PCR for an enteric virus, the following data were extracted: Baseline characteristics; clinical features of the acute episode, standard laboratory tests, including complete blood cell count, basic metabolic profile, acute phase reactant including C-reactive protein and interleukin 6, reports of stool cultures, virus detection, therapeutic interventions, and complications. An acute systemic inflammatory response was defined as either C-reactive Protein >10 mg/l [START_REF] Weitkamp | Diagnostic use of C-reactive protein (CRP) in assessment of neonatal sepsis[END_REF] or Interleukin 6 >100 pg/ml [START_REF] Krueger | Cord blood levels of interleukin-6 and interleukin-8 for the immediate diagnosis of early-onset infection in premature infants[END_REF] and lactic acidosis was defined as lactate >1.8 mmol/l.

Examinations of viral pathogens were done by antigen-specific enzyme-linked immunabsorbent assay (ELISA) for RV (Premier Rotaclone, Meridian Bioscience, Inc. Cinncinati, USA), AdV (Premier Adenoclone, Meridian Bioscience, Inc. Cinncinati, USA) and HAstV (Amplified IDEIA Astrovirus, DakoCytomation, Carpinteria, CA, USA). All ELISAs were performed according to the manufacturer's instructions. NV was detected by RT-PCR as previously described [2,[START_REF] Ando | A one-tube method of reverse transcription-PCR to efficiently amplify a 3-kilobase region from the RNA polymerase gene to the poly(A) tail of small round-structured viruses (Norwalk-like viruses)[END_REF][START_REF] Hohne | Detection and characterization of norovirus outbreaks in Germany: application of a one-tube RT-PCR using a fluorogenic real-time detection system[END_REF][START_REF] Schreier | Molecular epidemiology of outbreaks of gastroenteritis associated with small round structured viruses in Germany in 1997/98[END_REF].

Statistical Analyses: Statistical analysis was performed by SPSS 17.0 software package for windows. Infants with evidence of different viral pathogens were compared using Fisher's Exact Test for dichotomous variables, Mann Whitney U test for continuous variables which were not normally distributed and t-test for continuous variables with normal distribution. P < 0.05 was considered statistically significant.

RESULTS

A total of 906 stool specimens from 567 infants were examined for gastrointestinal viruses and enteropathogenic bacteria. Of 220 infants, 108 (3.2%) had NEC and 112 (3.3%) had GE. In the other 347 infants, no viral or bacterial pathogens were detected and these infants were excluded from analysis.

Gastrointestinal viral agents were detected in 34 infants out of 220 (15.5%) infants with GE and NEC; of these, 26 (77 %) were preterm infants at the onset of clinical signs. All patients with virus detection showed signs of GE (n=22) or NEC (n=12), of whom 6 had Bell's stage ≥ IIA NEC. There was no statistically significant difference in the gestational age between infants with and without viral enteric pathogens both in the GE group (median [range]: 34 [START_REF] Mitchell | Astrovirus gastroenteritis[END_REF][START_REF] Graham | Norwalk virus infection of volunteers: new insights based on improved assays[END_REF][START_REF] Dolin | Biological properties of Norwalk agent of acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Guo | Comparative pathogenesis of tissue culture-adapted and wild-type Cowden porcine enteric calicivirus (PEC) in gnotobiotic pigs and induction of diarrhea by intravenous inoculation of wildtype PEC[END_REF][START_REF] Schreiber | The mucosal lesion of the proximal small intestine in acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Wobus | Murine norovirus: a model system to study norovirus biology and pathogenesis[END_REF][START_REF] Morotti | Calicivirus infection in pediatric small intestine transplant recipients: pathological considerations[END_REF][START_REF] Cheetham | Pathogenesis of a genogroup II human norovirus in gnotobiotic pigs[END_REF][START_REF] Kliegman | Necrotizing enterocolitis: research agenda for a disease of unknown etiology and pathogenesis[END_REF][START_REF] Lin | Necrotising enterocolitis[END_REF][START_REF] Markel | Cytokines in necrotizing enterocolitis[END_REF][37][38][39][40] vs. 31 [START_REF] Mumphrey | Murine norovirus 1 infection is associated with histopathological changes in immunocompetent hosts, but clinical disease is prevented by STAT1-dependent interferon responses[END_REF][START_REF] Sirinavin | Neonatal astrovirus gastroenteritis during an inborn nursery outbreak[END_REF][START_REF] Lundgren | Role of the enteric nervous system in the fluid and electrolyte secretion of rotavirus diarrhea[END_REF][START_REF] Mitchell | Astrovirus gastroenteritis[END_REF][START_REF] Graham | Norwalk virus infection of volunteers: new insights based on improved assays[END_REF][START_REF] Dolin | Biological properties of Norwalk agent of acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Guo | Comparative pathogenesis of tissue culture-adapted and wild-type Cowden porcine enteric calicivirus (PEC) in gnotobiotic pigs and induction of diarrhea by intravenous inoculation of wildtype PEC[END_REF][START_REF] Schreiber | The mucosal lesion of the proximal small intestine in acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Wobus | Murine norovirus: a model system to study norovirus biology and pathogenesis[END_REF][START_REF] Morotti | Calicivirus infection in pediatric small intestine transplant recipients: pathological considerations[END_REF][START_REF] Cheetham | Pathogenesis of a genogroup II human norovirus in gnotobiotic pigs[END_REF][START_REF] Kliegman | Necrotizing enterocolitis: research agenda for a disease of unknown etiology and pathogenesis[END_REF][START_REF] Lin | Necrotising enterocolitis[END_REF][START_REF] Markel | Cytokines in necrotizing enterocolitis[END_REF][37][38][39][40] weeks; p=0.064), and in the NEC group (29 [START_REF] Lundgren | Role of the enteric nervous system in the fluid and electrolyte secretion of rotavirus diarrhea[END_REF][START_REF] Mitchell | Astrovirus gastroenteritis[END_REF][START_REF] Graham | Norwalk virus infection of volunteers: new insights based on improved assays[END_REF][START_REF] Dolin | Biological properties of Norwalk agent of acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Guo | Comparative pathogenesis of tissue culture-adapted and wild-type Cowden porcine enteric calicivirus (PEC) in gnotobiotic pigs and induction of diarrhea by intravenous inoculation of wildtype PEC[END_REF][START_REF] Schreiber | The mucosal lesion of the proximal small intestine in acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Wobus | Murine norovirus: a model system to study norovirus biology and pathogenesis[END_REF][START_REF] Morotti | Calicivirus infection in pediatric small intestine transplant recipients: pathological considerations[END_REF][START_REF] Cheetham | Pathogenesis of a genogroup II human norovirus in gnotobiotic pigs[END_REF][START_REF] Kliegman | Necrotizing enterocolitis: research agenda for a disease of unknown etiology and pathogenesis[END_REF][START_REF] Lin | Necrotising enterocolitis[END_REF] vs. 28 [START_REF] Mumphrey | Murine norovirus 1 infection is associated with histopathological changes in immunocompetent hosts, but clinical disease is prevented by STAT1-dependent interferon responses[END_REF][START_REF] Sirinavin | Neonatal astrovirus gastroenteritis during an inborn nursery outbreak[END_REF][START_REF] Lundgren | Role of the enteric nervous system in the fluid and electrolyte secretion of rotavirus diarrhea[END_REF][START_REF] Mitchell | Astrovirus gastroenteritis[END_REF][START_REF] Graham | Norwalk virus infection of volunteers: new insights based on improved assays[END_REF][START_REF] Dolin | Biological properties of Norwalk agent of acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Guo | Comparative pathogenesis of tissue culture-adapted and wild-type Cowden porcine enteric calicivirus (PEC) in gnotobiotic pigs and induction of diarrhea by intravenous inoculation of wildtype PEC[END_REF][START_REF] Schreiber | The mucosal lesion of the proximal small intestine in acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Wobus | Murine norovirus: a model system to study norovirus biology and pathogenesis[END_REF][START_REF] Morotti | Calicivirus infection in pediatric small intestine transplant recipients: pathological considerations[END_REF][START_REF] Cheetham | Pathogenesis of a genogroup II human norovirus in gnotobiotic pigs[END_REF][START_REF] Kliegman | Necrotizing enterocolitis: research agenda for a disease of unknown etiology and pathogenesis[END_REF][START_REF] Lin | Necrotising enterocolitis[END_REF][START_REF] Markel | Cytokines in necrotizing enterocolitis[END_REF][37][38][39][40][41] weeks; p=0.207), respectively.

RV was detected in stool specimens of 12 infants, HAstV in 14, and NV in 8 infants. No adenovirus was identified. RV could be identified only during an outbreak of gastrointestinal rotavirus infections between January 1998 and June 1998. Moreover, RV was detected in the second stool specimen of an infant with HAstV who was admitted to the group of HAstV. The majority of cases with RV infection have been mild and self-limiting GE, but 2 preterm infants had signs of NEC.

Infants with detection of HAstV more frequently suffered from NEC ≥ IIA if compared with infants with detection of RV or NV (RV n=2/12. NV n= 1/8, HAstV n=9/14; HAstV vs. RV and HAstV vs. NV p <0.05, respectively). In addition, analysis concerning the infants with GE (without NEC), HAstV GE showed more frequently an acute systemic inflammatory response (RV n=0/10, NV n=1/7, HAstV n=4/5; HAstV vs. RV and HAstV vs. NV, p <0.01 and p <0.05, respectively). The clinical features of all neonates with clinical GE or NEC in whom viral pathogens were detected are summarized in Table 1.

NV was detected in 8 newborns with a median gestational age of 29 weeks (range 26-36 weeks). Of these 8 children, 5 (63%) were still preterm at the onset of illness.

Predominant clinical signs in infants in whom NV was detected were abdominal distension, diarrhea, and apnea. Four neonates (n=4/8, 50%) with detection of NV showed bloody stools and one of them displayed an acute inflammatory response with elevated values for C-reactive protein (maximum value 42.1 mg/l), lactate (4.5 mmol/l) and clinical findings of NEC stage IB. In this infant oral feedings were withheld and antibiotics were administered for seven days. In one infant, repetitive stool specimens revealed a positive result for NV for 21 days after the onset of illness. The clinical features of infants in whom NV was detected are shown in Table 2.

DISCUSSION

Although viral pathogens have been identified as cause of epidemics of hospitalacquired GE for many years, the association of viral agents with NEC in preterm infants has only recently been recognized [START_REF] Sharma | Rotavirus-associated necrotizing enterocolitis: an insight into a potentially preventable disease?[END_REF][START_REF] Herruzo | Identification of risk factors associated with nosocomial infection by rotavirus P4G2, in a neonatal unit of a tertiary-care hospital[END_REF][START_REF] Bagci | Detection of astrovirus in premature infants with necrotizing enterocolitis[END_REF][START_REF] Lodha | Human torovirus: a new virus associated with neonatal necrotizing enterocolitis[END_REF][START_REF] Turcios-Ruiz | Outbreak of necrotizing enterocolitis caused by norovirus in a neonatal intensive care unit[END_REF]. Our study demonstrates that intestinal RV, NV and HAstV infection in preterm and term neonates may be associated with severe illness such as hemorrhagic enteritis resulting in bloody diarrhea or even NEC and provides further evidence for the role of gastrointestinal viral infections in this most common gastrointestinal emergency in premature infants. Nevertheless, the etiologic role of gastrointestinal viral agents in the pathogenesis of hemorrhagic enteritis or NEC remains largely unknown [1,[START_REF] Lundgren | Pathogenesis of rotavirus diarrhea[END_REF][START_REF] Mumphrey | Murine norovirus 1 infection is associated with histopathological changes in immunocompetent hosts, but clinical disease is prevented by STAT1-dependent interferon responses[END_REF].

Rotavirus is the main viral pathogen that causes severe diarrheal diseases in infants and young children up to two years. In addition, several reports have described the association of NEC with RV infection or colonization [START_REF] Rotbart | An outbreak of rotavirus-associated neonatal necrotizing enterocolitis[END_REF][START_REF] Sharma | Rotavirus-associated necrotizing enterocolitis: an insight into a potentially preventable disease?[END_REF][START_REF] Herruzo | Identification of risk factors associated with nosocomial infection by rotavirus P4G2, in a neonatal unit of a tertiary-care hospital[END_REF]. In our cohort we found two patients with RV infection and NEC. Hypotheses of the mechanism of diarrhea include reduced absorptive surface, functionally impaired absorption, cellular damage impairing absorption, enterotoxic effects of rotavirus protein NSP4, and stimulation of the enteric nervous system [1,[START_REF] Lundgren | Pathogenesis of rotavirus diarrhea[END_REF]. However, the role of RV in the pathogenesis of NEC has not been established. The authors suggested that a possible synergism between RV and other microorganism can worsen the infection in the intestine and cause necrotizing enterocolitis [1,[START_REF] Rotbart | An outbreak of rotavirus-associated neonatal necrotizing enterocolitis[END_REF][START_REF] Sharma | Rotavirus-associated necrotizing enterocolitis: an insight into a potentially preventable disease?[END_REF]. Although all patients in our NICU received a regular screening for viral agents and enteric bacterial pathogens during an outbreak of RV infections, no other gastrointestinal pathogen microorganisms were detected. Furthermore, we found no asymptomatic RV carriers in our NICU at that time.

Although HAstV is usually associated with cases of mild and self-limiting GE in older children, we previously reported that colonization or infection with HAstV may be associated with the development of severe NEC in preterm infants [START_REF] Bagci | Detection of astrovirus in premature infants with necrotizing enterocolitis[END_REF]. Previously, Sirinavin et al. [START_REF] Sirinavin | Neonatal astrovirus gastroenteritis during an inborn nursery outbreak[END_REF] described a HAstV outbreak in healthy neonates in a nursery of a maternity ward. However, so far neonatal cases are rare and outbreaks have not been reported from NICUs. Enteropathogenic viruses generally infect epithelial cells and result in cytolysis and cell destruction [START_REF] Lundgren | Role of the enteric nervous system in the fluid and electrolyte secretion of rotavirus diarrhea[END_REF]. In symptomatic HAstV infection, viral particles have been detected in the low villous, and on the surface of the intestinal epithelium as well as in macrophages of the lamina propria. Investigations in an animal astrovirus model revealed vacuolization followed by degeneration and cell death leading to villous atrophy [START_REF] Mitchell | Astrovirus gastroenteritis[END_REF]. However, it is unclear which pathogenetic mechanisms are involved in the occurrence of acute systemic inflammatory response and intestinal ischaemia, i.e. in NEC, in infants with HAstV infection / colonization. Of our 14 infants infected with HAstV, 5 (36%) had Bell's stage ≥ IIA NEC and 4 (80%) of 5 infants with clinical GE showed an acute systemic inflammatory response. In contrast to older children, the intestinal epithelium in premature infants may not have the same regenerative capacity. Exaggerated inflammation caused by immature intestinal innate immunity may lead to the generation of toxic metabolites, enhance the epithelial damage and result in intestinal lesions recognized as necrosis. On the other hand, one could speculate that NEC or the systemic inflammatory response may result from bacterial translocation after mucosal damage as a result of a possible synergism between HAstV and bacteria or from the systemic spread of virus particles. However, we are unable to identify another bacterial enteropathogenic agent in stool and blood cultures in these infants.

Generally, NV infections are mild and self-limiting and diarrheal stool during NV infection is non-bloody, lacks mucus, and may be loose or watery [START_REF] Patel | Systematic literature review of role of noroviruses in sporadic gastroenteritis[END_REF][START_REF] Thornton | Noroviruses: agents in outbreaks of acute gastroenteritis[END_REF][START_REF] Graham | Norwalk virus infection of volunteers: new insights based on improved assays[END_REF]. In contrast, four of our 8 newborn infants with NV infection (50%) had bloody stools and one of them had NEC [START_REF] Thornton | Noroviruses: agents in outbreaks of acute gastroenteritis[END_REF]. Human noroviruses are thought to have an enteric tropism limited to the upper intestinal tract, because intestinal biopsies from volunteers revealed villous broadening and atrophy, crypt cell hyperplasia and cytoplasmic vacuolization in the jejunum and duodenum and an infiltration of polymorphonuclear and mononuclear cells into the lamina propria [START_REF] Dolin | Biological properties of Norwalk agent of acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Guo | Comparative pathogenesis of tissue culture-adapted and wild-type Cowden porcine enteric calicivirus (PEC) in gnotobiotic pigs and induction of diarrhea by intravenous inoculation of wildtype PEC[END_REF][START_REF] Schreiber | The mucosal lesion of the proximal small intestine in acute infectious nonbacterial gastroenteritis[END_REF][START_REF] Wobus | Murine norovirus: a model system to study norovirus biology and pathogenesis[END_REF]. Similar pathology is seen in biopsies from pediatric transplant patients with diarrhea associated with human NV infection [START_REF] Morotti | Calicivirus infection in pediatric small intestine transplant recipients: pathological considerations[END_REF].

Histopathologic examination in the intestine of gnotobiotic pig's also showed mild lesions in the upper intestinal tract, but no cytopathic lesions [START_REF] Cheetham | Pathogenesis of a genogroup II human norovirus in gnotobiotic pigs[END_REF]. Cheetham et al. [START_REF] Cheetham | Pathogenesis of a genogroup II human norovirus in gnotobiotic pigs[END_REF] speculated that extensive histopathologic lesions may not be apparent in the intestine because the NV-infected enterocytes may be dying by apoptosis rather than necrosis.

Recently, Turcios-Ruiz et al. [START_REF] Turcios-Ruiz | Outbreak of necrotizing enterocolitis caused by norovirus in a neonatal intensive care unit[END_REF] and Armbrust at al. [START_REF] Armbrust | Norovirus infections in preterm infants: wide variety of clinical courses[END_REF] reported cases of NEC associated with NV in newborn infants similar to the case we describe in this report.

Unfortunately none of these studies provided information on the histopathologic examination of colons to establish the involvement of the colon with NV infection / colonization in premature newborn infants.

In summary, just like other authors [START_REF] Kliegman | Necrotizing enterocolitis: research agenda for a disease of unknown etiology and pathogenesis[END_REF][START_REF] Lin | Necrotising enterocolitis[END_REF][START_REF] Markel | Cytokines in necrotizing enterocolitis[END_REF], we can only speculate that viral infections in preterm infants may increase epithelial cell damage leading to weakening of the mucosal barrier and occasionally resulting in NEC. The limitations of our study are the retrospective design, the lack of data on the prevalence of gastrointestinal viruses in stool specimen of infants without gastrointestinal symptoms and the lack of data concerning the time course of the development of GE or NEC with regard to the onset of colonization / infection with viruses. In order to understand the prevalence of enteric viruses in neonatal intensive care units and their role in the pathophysiology of NEC, gastrointestinal viruses should be included in the microbiological examination of stool specimens in patients with gastrointestinal symptoms and further studies are necessary.

Reviewers' Comment 2 :Answer 2 :

 22 In the Results section (p.2, line 19) it should be mentioned that enteropathogenic viruses were found in 34 infants out of 220 (15.45%) infants with gastroenteritis (GE) and NEC (nectotizing enterocolitis). According the reviewers' suggestions we changed the sentence as recommended (Page 6, p.2). Reviewers' Comment 3: Among 112 infants with gastroenteritis, enteric viruses were detected in 22 patients (19.64%), and in 12 cases (11.11%) out of 108 infants with NEC. That means that approximately only in one case out of every 10 infants suffering of NEC was an enteric virus detected. The majority of cases with RV infection (10/12)

Reviewers' Comment 5 :Answer 5 :Answer 7 :

 557 In several sentences it is said that viruses may 'colonize' the gut: "colonization or infection with HAstV" (Abstract, p. 3, line 29), "RV infection or colonization" (Discussion, p. 8, line 29; p. 10, lines 34 and 51). What do the authors mean with viral colonization? In regard to viruses, what is the difference between colonization and infection? The pathogenesis of NEC remains unclear. Several studies have reported that early abnormal bacterial colonization plays a key role in the development of NEC(1,2). But it is still unclear, whether viral colonization of the gastrointestinal tract without cytolysis and cell destruction may play a role in the pathogenesis of NEC in newborn infants. Therefore, we preferred to use "infection or colonization", until we understand the role of enteric viruses in the pathophysiology of NEC. Reviewers' Comment 6: It is stated that all patients who shared a room with an infected infant were immediately tested for enteric viruses. Were viruses found in asymptomatic infants? Were dual (mixed) viral infections detected? Apparently no adenovirus infections were found. These results should be clearly presented. Answer 6: According the reviewers' suggestions the following sentences have been added to results (Results, p. 4): "No adenovirus was identified." and "Moreover, RV was detected Reviewers' Comment 7: In the Discussion, first paragraph, it is included the citation to reference 7, Rotbart et al. (1983), as a recent description of the association of viral agents with NEC. A 27-years-old paper cannot be considered as "recent". Also, citations to reference 20 (Mumphrey et al., 2007) in the same paragraph (p. 8, line 7 and line 22) to document the association of viral agents with the pathogenesis of hemorrhagic enteritis or NEC is not appropriate. We corrected these errors which resulted from an error of the reference manager. INTRODUCTION Viral pathogens are the most frequent cause of endemic and outbreak-related GE and are responsible for significant morbidity and mortality in infants and children world-wide, both outbreak-related and endemic. Most episodes are due to infections with rotavirus (RV), human astrovirus (HAstV), norovirus (NV), and adenovirus (AdV) [1-2].

We thank you for reviewing the manuscript. Yours sincerely, Soyhan Bagci, Department of Neonatology, Children's Hospital, University of Bonn, Adenauerallee 119, D-53113 Bonn, Germany. Tel.: ++49-228-287-33408 Fax: ++49-228-287-16291 E-mail: soyhan.bagci@ukb.uni-bonn.de

Table1. Neonatal Characteristics and Clinical Findings of Newborns with Enteric Viral Infection


Zhiwei Ge
email: gezhiwei@tju.edu.cn

Junyan Tan
email: junyan.tan@univ-st-etienne.fr

Virginie Fresse
email: virginie.fresse@univ-st-etienne.fr

Fré Dé

Ric Rousseau
email: frederic.rousseau@imag.fr

Suying Yao
email: syyao@tju.edu.cn

A Scalable and Effective Routing Algorithm for Multi-FPGA Based Large Scale NoC

In this paper, we designed a hardware implementation of routing algorithm for multi-FPGA based large scale NoC based on the existing 2D routing scheme. The proposed routing algorithm can be used with both intra-FPGA and inter-FPGA communications. We showed a resource utilization and latency performance evaluation for our work.

Abstract -In the context of the FPGA resource limitation for large scale NoC, multi-FPGA based solutions are proposed. Due to the scalable routing scheme and packet format, the proposed routing algorithm can be used with both intra-FPGA and inter-FPGA communications. The effectiveness of the scheme is that it can be used for any multi-FPGA based NoC with small amount extra resource consumption. Index Terms-routing algorithm, multi-FPGA, NoC, emulation I. INTRODUCTION Network-on-Chip (NoC) has been proposed as a solution to implement future on-chip interconnections [START_REF] Benini | Networks on Chips: A New SoC Paradigm[END_REF]. NoCs can provide higher overall bandwidth and more scalability with less power consumption [START_REF] Kumar | A Network on Chip Architecture and Design Methodology[END_REF].

NoC emulation using FPGA is widely used for evaluating the performances of the communication [START_REF] Schelle | Exploring FPGA Network on Chip Implementations Across Various Application and Network Loads[END_REF]. This experimental approach suffers from scalability issue, mainly due to the resource limitation of FPGA. Multi-FPGA based emulation systems are proposed to solve this problem [START_REF] Stepniewska | Network-on-Multi-Chip (NoMC) for Multi-FPGA Multimedia Systems[END_REF] [START_REF] Abdellah-Medjadji | Large Scale On-Chip Networks: An Accurate Multi-FPGA Emulation Platform[END_REF]. No fully scalable NoC architectures for multi-FPGA emulation purpose are proposed in literature. The contribution of this work is to propose a scalable NoC on multi-FPGA platform from existing mesh NoC using the packet-switching technique. We propose a routing algorithm considering inter-FPGA and intra-FPGA communications based on existing 2D routing algorithms.

II. THE HERMES NOC

In our work, we use Hermes NoC to illustrate the proposed routing algorithm. Any NoC with mesh topology using packet-switching technique can replace the Hermes NoC. The Hermes NoC was designed by Fernando MORAES from FACIN-PUCRS [START_REF] Moraes | HERMES: an infrastructure for low area overhead packet-switching networks on chip[END_REF], and is depicted in Fig. 1. The Hermes NoC uses the 2D mesh topology in which router has a set of bi-directional ports EAST, WEST, NORTH, SOUTH and LOCAL linked to other routers and PEs. The XY routing is often used due to its determinism and simplicity. The ATLAS tool can generate synthesizable VHDL NoCs with different flit sizes, buffer depths and routing algorithm. This tool also proposes SystemC simulation models with simulation VHDL models of traffic generators and traffic receptors.

III. THE ROUTING ALGORITHM FOR MULTI-FPGA BASED NOC A. The proposed routing algorithm

We consider a multi-FPGA platform with M FPGAs (the index of the FPGA that node N belongs to is denoted by z N ). We denote the source node and destination node of a packet with S and D, respectively, and the current node with C. There is also one identical multi-dimension node N MD in each FPGA. The N MD node is the node (2, 2) in Fig. 2 in the 3X3 NoC implemented on 2 FPGAs. In addition to the traditional ports, the switch of N MD has two extra ports UP and DOWN. The multi-dimension router can transfer packets to the adjacent FPGAs with these two extra ports. The basic idea of the multi-FPGA based routing scheme is to transfer the packet to the destination FPGA z D firstly (if the packet is not in FPGA z D ). The architecture of the router using the proposed multi-FPGA based routing algorithm is shown in Fig. 3. Three modules implement the router: input buffers, switch control logic and crossbar interconnections. When an input buffer receives the first 2 flits of a packet, it sends the flits to the switch control logic. The switch control logic can establish interconnections between the input ports and the correct outputs using the proposed routing algorithm. The algorithm compares the z C with z D firstly. Flits must be routed to D when z C equals to z D . If this is not the case, flits will be routed to the UP port of N MD when z C is greater than z D and to the DOWN port of N MD when z C is smaller than z D . Fig. 3 The architecture of router dedicated to multi-FPGA.

B. The packet format

In order to support and evaluate the described multi-FPGA based routing, we require a five-flit header. The format of packet is adapted to multi-FPGA based NoC communication and is depicted in Fig. 4. The first and the second flit of the header represent the address of the destination FPGA z D and the 2D co-ordinate information of the destination router. The number of flits in the packet payload is stored in the third flit. To evaluate the latency performance of the proposed algorithm, the total latency between the source and destination router and the inter-FPGA link latency are included in the header.

A. Resource utilization

Resource utilization experiments are done firstly for routers (32-bit flit, 16-flit buffer), as depicted in Fig. 5. The extra resources are about 50 registers and 300 LUTs between RPN_2D and RPN_3D (i.e. the same router using respectively the XY and the proposed routing algorithm). The resources used for N MD node are higher than any other nodes. The N MD node uses respectively about 160 more registers and 700 more LUTs than 2D nodes and 110 more registers and 400 more LUTs than 3D nodes.

We also compare the resource utilization for different size of NoCs (32-bit flit, 16-flit buffer), as shown in Fig. 6.

B. Average latency with different links

The average latency of multi-FPGA based NoC depends on both the offered load and the inter-FPGA link. The minimal latency in clock cycles using the proposed algorithm to transfer a packet is given by: latency = (∑ n i=1 R i )+P*2+T_LINK (1) Where n is the number of switches in the communication path (source and target included), R i is the number of clock cycles for routing data through one router, P is the packet size and T_LINK is the inter-FPGA link latency (flit 4 in the packet from Fig. 4). R i depends on the routing algorithm. R i is 7 clock cycles for 2D XY routing and 11 clock cycles for the proposed routing algorithm. Fig. 7 shows the average latencies with different links for the 3X3X2 NoC to transfer 50 packets with 9-flit length using the NoC and the scenario depicted in 2.

Fig. 1

 1 Fig. 1 The Hermes NoC

Fig. 2

 2 Fig.2The multi-FPGA based NoC and N MD node The basic idea of the multi-FPGA based routing scheme is to transfer the packet to the destination FPGA z D firstly (if the packet is not in FPGA z D ). The architecture of the router using the proposed multi-FPGA based routing algorithm is shown in Fig.3. Three modules implement the router: input buffers, switch control logic and crossbar interconnections. When an input buffer receives the first 2 flits of a packet, it sends the flits to the switch control logic. The switch control logic can establish interconnections between the input ports and the correct outputs using the proposed routing algorithm. The algorithm compares the z C with z D firstly. Flits must be routed to D when z C equals to z D . If this is not the case, flits will be routed to the UP port of N MD when z C is greater than z D and to the DOWN port of N MD when z C is smaller than z D .

Fig. 4

 4 Fig. 4 Format of packet for multi-FPGA routingIV. EXPERIMENTS AND RESULTSImplementations and emulations are done on a multi-FPGA platform using four ML506 development board with Xilinx ISE 10.1. The ML506 board contains a Virtex5 FPGA (32640 registers and 32640 LUTs) with high speed serial designs using the RocketIO™ GTP transceivers[7].A. Resource utilizationResource utilization experiments are done firstly for routers (32-bit flit, 16-flit buffer), as depicted in Fig.5.

Fig. 5

 5 Fig. 5 Resource utilization results for routers

Fig. 6

 6 Fig. 6 Resource utilization results for NoCs The 2x2 3D NoC uses 46.7% more registers and 29.1% more slice LUTs compared to the2x2 2D NoC. Extra LUTs are 31.2% or 26.8% for respectively the 3x3 and 4x4 NoC. Extra registers are 9.3% or 4.2% for respectively the 3x3 and 4x4 NoC. The number of extra resources is getting lower when the size of NoC is getting higher. With the

Fig. 7

 7 Fig. 7 The average latency for 2X3X3 NoC with different links The average latencies have the same behavior whatever the type of communication. The saturation point can be evaluated (around 70% for this case). From any emulation, we can estimate the latency between two nodes without considering the inter-FPGA communication (by removing the numbers of clock cycles used by the communication).


Christelle Caillouet
email: caillouet@math2.rwth-aachen.de

Xu Li
email: xu.li@inria.fr

Tahiry Razafindralambo
email: tahiry.razafindralambo@inria.fr

A Multi-objective Approach for Data Collection in Wireless Sensor Networks

Keywords: mobile sink, data collection, energy

Wireless sensors networks (WSNs) are deployed to collect huge amounts of data from the environment. This produced data has to be delivered through sensor's wireless interface using multi-hop communications toward a sink. The position of the sink impacts the performance of the wireless sensor network regarding delay and energy consumption especially for relaying sensors. Optimizing the data gathering process in multi-hop wireless sensor networks is, therefore, a key issue. This article addresses the problem of data collection using mobile sinks in a WSN. We provide a framework that studies the trade-off between energy consumption and delay of data collection. This framework provides solutions that allow decision makers to optimally design the data collection plan in wireless sensor networks with mobile sinks.

Introduction

Wireless sensor networks (WSNs) have received a lot of attention in recent years due to their potential applications in various areas such as environment monitoring or tracking [START_REF] Barrenetxea | The hitchhiker's guide to successful wireless sensor network deployments[END_REF][START_REF] Hart | Environmental sensor networks: A revolution in the earth system science?[END_REF][START_REF] Martinez | Glacsweb: a sensor network for hostile environments[END_REF]. In order to get useful and up-to-date information from the environment, the network is composed of a large number of low-capacity (processor, memories, battery) sensors. As the number of sensors increases, the amount of data in the network also increases. The data generated by the sensors has, then, to be sent to a central entity, called sink, for storage and processing. Thanks to the wireless communication capabilities and the protocols developed in the literature, multi-hop transmissions can be used to route data from a sensor to the sink if no direct connection is available. However, this classical N to 1 communication paradigm rapidly consumes the energy of intermediate sensors and provides unfair delay distribution depending on the distance to the sink [START_REF] Khadar | Performance evaluation of gradient routing strategies for wireless sensor networks[END_REF]. Therefore, data collection becomes a key issue in wireless sensor networks.

The data collection in wireless sensor networks consumes energy and needs low delay depending on the application. Reducing the energy consumption while increasing the amount of generated data to have a correct view of the environment is a great challenge. Due to this conflicting goals, the trade-off between energy consumption and environment observation accuracy is still an hot topic in wireless sensor networks. Moreover, WSNs are more and more used for delay sensitive applications such as battlefield monitoring. In these applications, delay reduction between data generation and data processing becomes mandatory.

The literature shows different ways to reduce the amount of transiting data in the network. On one hand, data aggregation techniques [START_REF] Krishnamachari | The impact of data aggregation in wireless sensor networks[END_REF] limit the generated data by using forecasting. These techniques have some strong assumptions regarding the data. However, forecasting strongly reduces the amount of generated data and thus increases the network lifetime. On the other hand, the use of mobile sinks reduces the number of forwarding sensors [START_REF] Luo | Joint mobility and routing for lifetime elongation in wireless sensor networks[END_REF] but needs motion capabilities for the sinks. In this paper, we focus on data collection using mobile sinks in wireless sensor networks with the objective of minimizing the energy consumption and the delay of data collection.

Our purpose is to determine where to place a set of gateways (or collection points) that are defined to collect the produced data of a region in the WSN field, and compute the route of a mobile sink moving along the gateways to gather the data from the sensors. To answer these questions, we propose a Multi-objective Linear Programming (MLP) framework that allows to optimally place the gateways and minimize jointly the energy spent in the WSN and the route of the mobile sink. Multi-objective optimization does not compute an unique solution, but a set of "best" solutions, called the Pareto front, capturing the trade-offs between the different metrics. Solving a multi-objective problem consists in finding the Pareto front, from which the decision maker chooses the solution that fits the best his needs. In this work, each point of the Pareto set is obtained by solving an optimization problem. The main contribution of this work is to give a multicriteria vision of the data collection problem in WSNs. As far as we know there is no multi-objective analysis in this subject. The developed solutions reduce the overall energy consumption but also reduce the delay of data delivery from the sensors to the sink. Unlike the works proposed in the literature, the results of this paper are twofold. First, we tackle the problem of optimal placement of data collection points in an energy-efficient WSN. Second, we optimize the data collection tour by the sink to minimize the delay. In the first contribution, our aim is to reduce the energy spent by intermediate sensors and in the second contribution, we focus on delay reduction.

In Section 2, we review the previous proposed solutions for optimizing the energy consumption and data collection in WSNs, and describe our assumptions for this work. Section 3 presents the formulation of our proposed MLP. Section 4 presents the method to optimaly solve our MLP. Section 5 shows the experimental results and Section 6 concludes the paper.

Background and assumptions

State of the art

Various solutions have been proposed to extend the network lifetime and reduce delay for data collection. Some solutions have proposed to deploy static sinks in order to reduce the traffic bottlenecks which affect the energy efficiency and the WSN lifetime. In [START_REF] Capone | Deploying multiple interconnected gateways in heterogeneous wireless sensor networks: An optimization approach[END_REF], authors propose an heterogeneous view of the network. They develop an ILP (Integer Linear Program) formulation for placing a minimum number of collection points (or gateways) and ensure connectivity among them and the sink to form a wireless mesh network to deliver the data. They minimize the number of collection points and the maximum distance between the sensors and a gateway so that energy consumption is minimized. The use of mobile sinks instead of static sinks to collect the data is more efficient and significantly increases the lifetime of the sensor network [START_REF] Gandham | Energy efficient schemes for wireless sensor networks with multiple mobile base stations[END_REF][START_REF] Luo | Joint mobility and routing for lifetime elongation in wireless sensor networks[END_REF]. In these works, the location of the mobile sinks is periodically computed so that the network lifetime is maximized. Some research efforts have focused on approaches either minimizing the energy consumed by the sensors [START_REF] Gandham | Energy efficient schemes for wireless sensor networks with multiple mobile base stations[END_REF], or maximizing the global network lifetime [START_REF] Saad | Multiple mobile sinks positioning in wireless sensor networks for buildings[END_REF][START_REF] Kalpakis | Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks[END_REF].

Considering the route of the mobile sinks in WSNs instead of its periodical relocation has not been addressed in previous work to the best of our knowledge. We propose a different formulation of the problem, seeking to jointly compute an optimal placement of the collection points (or gateways) in an energy-efficient way, while minimizing the length of the route of a mobile sink. The extension of our model to deal with several mobile sinks is straightforward as described in the next section. We do not claim to provide a unique best solution of the problem, but we study the trade-off between the energy spent by the sensor nodes in data collection, and the delay induced by a mobile sink collecting data at collection points in the WSN. Thus, our work provides solutions that allow decision makers to optimally design the data collection plan in wireless sensor networks with mobile sinks.

Motivating application

We consider a multi-tiered network structure in order to improve energy efficiency. The hierarchical architecture considered in this paper has been designed for WSN and consists of multi-tiers:

-Sensors are static devices that are capable of collecting information and are resource constrained. The sensors are spread out over the sensing field following a distribution that may be probabilistic or deterministic. -Gateways (or collection points) are static devices deployed to collect the traffic of a region of the network. -Sinks are devices with motion capabilities which gather data from sensors.

In our application, the sinks gather data at different collection points of the sensing field. Since the collection points may not be inside the communication range of a given sensor, sensors use multi-hop communications to send data to a given collection point. During the bootstrapping phase of our application, a set of possible collection points are defined. An optimal subset of collection points is chosen in order to reduce the application delay and to enhance the energy efficiency of the whole network. Moreover, since we consider mobile sinks, it is also important to optimize the route of the mobile sink in order to reduce its energy consumption and the delay for data delivery.

Model and assumptions

We assume that the routing in the WSN (from sensors to collection points) is given so that our model is independent on the specific routing strategy. We select and place the gateways in order to minimize the energy consumption of the WSN.

The energy model considered for the sensors is based on the first order radio model described in [START_REF] Heinzelman | Energy-efficient communication protocol for wireless micro sensor networks[END_REF]. A sensor consumes ǫ elec = 50 nJ/bit to run the transmitter or receiver circuitry, and ǫ amp = 100 pJ/bit/m 2 for the transmitter amplifier. Thus, to receive a k-bit message, sensor i consumes:

E r = ǫ elec k,
and

E t = ǫ elec k + ǫ amp dist 2 (i, j)k, (1)
to transmit this message to a neighbor j, where dist(i, j) is the euclidean distance between i and j.

In the following, we propose a Multi-objective Linear Programming (MLP) framework that allows to study the trade-offs between the length of the route of the mobile sinks associated with a computed gateway placement, and the overall energy consumption in a wireless sensor network.

Problem definition

In this work, we focus on data collection in WSNs minimizing the energy consumption and the delay. A set of gateways is chosen to collect the traffic of a region in the WSN field, and a mobile sink moves along the gateways to gather the data from each region.

Given a wireless sensor network represented by a set of sensor nodes S, we define a set of candidate sites C S which can potentially be a collection point. We want to determine the gateways' location such that each sensor is associated with its closest one. In order to associate each sensor with its closest gateway, we order, for each sensor node i ∈ S, the reachable gateways in the vector

O i : if j < k, then dist(i, j) ≤ dist(i, k) and O i (j) is before O i (k) in the vector. Sets J i are index sets of vector O i .
The routing table is an input of our optimization problem. We thus have the set P of paths between the sensors and the candidate sites where we can potentially deploy a gateway. O(p) (resp. D(p)) denotes the source node (resp. the destination node) of path p ∈ P . From the set of paths, we introduce the matrix C to indicate the connectivity between the sensors and the gateways:

C ic =
1 if there exists a route between sensor i and candidate site c 0 otherwise

The decision variables used in our MLP are the following:

E max = the maximum amount of energy consumed by a sensor

x ij = 1 if sensor i is assigned to gateway j 0 otherwise

y j = 1 if a gateway is installed at candidate site j 0 otherwise χ ij =   
1 if two gateways are installed at candidate sites i and j and the link (i, j) is selected for the route of the mobile sink 0 otherwise To evaluate the overall quality of our solutions, we use the following metrics:

-MinMaxE (f 1 ): Balancing the energy spent by the sensor nodes, that can be viewed as WSN lifetime maximization. From the energy model described in Section 2.3, we seek to minimize the maximum energy spent by each sensor node: min max s∈S (E tot (s)), where E tot (s) is the total amount of traffic sent and relayed by sensor s in the WSN. The formal definition of E tot (s) is given in the next subsection. -MinRoute (f 2 ): Minimizing the length of the route of the mobile sink between the different installed gateways: min i∈CS j∈CS dist(i, j)χ ij .

Multi-objective linear program

The optimization problem of placing the gateways such that we jointly minimize the length of the mobile sink route, and the energy spent by the sensor nodes is the following:

   (i) min f 1 = E max (ii) min f 2 = i∈CS j∈CS dist(i, j)χ ij (2) j∈CS x ij = 1 ∀i ∈ S (3)
x ij ≤ C ij y j ∀i ∈ S, j ∈ C S (4) y Oi(k) + h∈Ji,h>k x iOi(h) ≤ 1 ∀i ∈ S (5)
p ∈ P, i ∈ p, i = O(p) (E r + E t ) x O(p)D(p) + p ∈ P, i = O(p) E t x iD(p) ≤ E max ∀i ∈ S (6)
i∈CS

χ ij = y j , j∈CS χ ij = y i ∀i, j ∈ C S (7)
i,j∈K

χ ij i∈K\{k} y i + 1 -y c ∀k ∈ K ⊂ C S , c ∈ C S \ K (8)
The objective (2) seeks to minimize (i) the maximum energy consumed by the sensor nodes, and (ii) the length of the route of a mobile sink along the placed gateways, subject to the euclidean distance between the gateways. Constraints (3) and ( 4) ensure that each sensor must be associated with an installed gateway that can be reached using a given existing path. Constraints [START_REF] Hart | Environmental sensor networks: A revolution in the earth system science?[END_REF] force each sensor to be assigned to its closest gateway.

The objective (2)(i) and constraints (6) try to minimize the maximum amount of energy spent by the sensors. Each sensor has to send its own traffic to its associated gateway, and it has also to forward traffic received by other sensors destinated to their associated collection points. According to the definitions in Section 2.3, the total energy spent by sensor i to relay the data from another sensors associated to an installed collection point j equals:

E F tot (i) = p∈P, i∈p, i =O(p), y D(p) =1 (E r + E t ) x O(p)D(p) .
We have to add i's traffic to this formula:

E Stot (i) = p∈P, i∈p, i=O(p), y D(p) =1 E t x iD(p) .
Leading to the total amount of energy spent by i:

E tot (i) = E F tot (i) + E Stot (i).
In constraints (4), the sensor-gateway association cannot exist if the candidate site is not chosen, i.e. y j = 0 ⇒ x ij = 0, ∀i ∈ S. E tot (i) can thus be replaced by the left-hand side of constraints [START_REF] Heinzelman | Energy-efficient communication protocol for wireless micro sensor networks[END_REF]. We then bound this amount by E max which is to be minimized in the objective function. Equalities [START_REF] Kalpakis | Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks[END_REF] force the mobile sink to visit all the chosen collection points to collect the data generated by the sensors. They refer to the NP-complete Travelling Salesman Problem (TSP). Since our problem combines gateway placement and TSP, we do not know a priori the number of deployed gateways that have to be part of the TSP tour but only the number of candidate sites. The classical linear constraint for subtour elimination is not enough to ensure subtour elimination within the deployed gateways. Constraints (8) are so-called generalized subtour elimination contraints and ensure that there must be a selected edge between a subset K and K = C S \ K only if there is at least a deployed gateway inside and outside of K. Unfortunately, the number of subsets K ⊂ C S is exponential in the cardinality of C S . To avoid the complete enumeration of the subsets, we proceed as follows:

1. Solve the MLP without subtour elimination. 2. Check the solution: if it has no subtour, we are done. 3. If there is a subtour, add the corresponding constraint [START_REF] Khadar | Performance evaluation of gradient routing strategies for wireless sensor networks[END_REF] for the subtour and solve the program again. 4. Iterate until a solution without subtours is found.

Multiple mobile sinks

The extension with several mobile sinks is straightforward in our model and can be done in the following way:

-Introduce the set M of mobile sinks, and the decision variable χ m ij to be the selection of link (i, j), i, j ∈ C S in the route of mobile sink m ∈ M.

-Add the set of constraints specifying that each link between two gateways must be selected by exactly one mobile sink:

m∈M χ m ij = χ ij ∀i, j ∈ C S . (9)
-Ensure that the route of each mobile sink is a tour:

j∈CS χ m ji = j∈CS χ m ij ∀i ∈ C S , m ∈ M. (10)
Investigation regarding multiple mobile sinks is out of the scope of this paper and is left as future works. We can also notice that this simple extension can be enhanced by a coordination of the different mobile sinks' tours.

Energy-delay trade-off

In order to determine the optimal solutions of our problem, we have solved the proposed MLP with IBM Cplex solver3 version 12 on an INTEL Core 2 2.4 GHz with 2 Gb of memory.

Combining the two metrics of the objective function (2) for our problem is not relevant. Indeed, there exists confliction between route length and energy consumption in our optimization framework, i.e., pursuing the optimization of the route length of the mobile sink inextricably damages the performance of energy spent by the sensors. Saving energy enforces to deploy more collection points in the network, thus increasing the length of the route for the mobile sinks. As a result, the length of the route would be damaged, and vice versa. Consequently, for such a multi-objective optimization problem in which the objectives cannot be optimized simultaneously, the concept of Pareto optimality was introduced into the evaluation system.

The main idea to study the trade-offs between the two metrics MinMaxE and MinRoute is to find out all the possible non-dominated solutions of the optimization problem. In a general multi-objective problem of the form:

min f (x) = (f 1 (x), f 2 (x), . . . , f k (x)) s.t. g i (x) 0, i = 1, . . . , m
Where x ∈ R n is the decision vector belonging to the feasible region

F = {x ∈ R n | g i (x) 0, i = 1, 2, . . . , m}, a solution x 2 ∈ R n is dominated if there is another solution x 1 ∈ R n such that:
-The decision vector x 1 is not worse than x 2 in all objectives:

f i (x 1 ) f i (x 2 ), ∀i = 1, 2, . . . , k.
-The decision vector x 1 is strictly better than x 2 in at least one objective: f i (x 1 ) < f i (x 2 ) for at least one i = 1, 2, . . . , k.

A solution is non-dominated if there is no other solution dominating it. Informally, this means that if a solution is non-dominated within the whole solution space, it is not possible to improve one of the metrics without worsening at least one of the other metrics. Each multi-objective problem has a set of Paretooptimal solutions defined as the set of non-dominated solutions. The set of all non-dominated solutions is the Pareto front [START_REF] Laumanns | An adaptive scheme to generate the pareto front based on the epsilon-constraint method[END_REF]. The Pareto front provides a set of solutions that can be chosen depending on the application requirements. More precisely, each non-dominated solution represents a different optimal trade-off between the objectives. In this paper, the objective functions of our data collection problem for WSNs are f 1 = M inM axE and f 2 = M inRoute, which are used in the Pareto dominance comparison as in Figure 1. In order to generate Pareto-optimal solutions on the Pareto front, we use the ǫ-constraint method that transforms the multi-objective problem into a sequence of parameterized single-objective problems such that the optimum of each single-objective problem corresponds to a Pareto-optimal solution [START_REF] Laumanns | An adaptive scheme to generate the pareto front based on the epsilon-constraint method[END_REF]. We thus generate and solve monoobjective optimization problems of the form: The ǫ i are chosen such that f i * ǫ i , where f i * corresponds to the optimum value of the mono-objective problem minimizing only objective f i .

min f i (x) s.t. f j (x) ǫ j , ∀j = i MinRoute 0 0.

Performance evaluation

In this section, we present results obtained by solving our MLP with the ǫconstrained method in order to get optimal solutions on the Pareto front. We study networks of size between 50 and 250 sensors whose position is randomly chosen in a square area. The length is normalized so that the WSN is deployed in a unitary squared area. For each random network computed, we use two policies of candidate sites locations: a regular and a random one. The first model divides the area considered into equal squares in which one candidate site is placed in the center of the square. In this way, the candidate sites for placing the collection points form a regular grid. The second policy chooses randomly the location of the candidate sites in the area. We have tested the two policies with {3 2 , 4 2 , 5 2 } candidate sites. The set of paths considered is comprised of shortest paths between each pair (sensor, candidate site).

Effect of candidate sites and network density

To demonstrate the utility of the approach, we generate sets of non-dominated solutions by iteratively solving ǫ-constrained mono-objective optimization problems. Results are depicted in Figures 2 and3 for various network sizes and numbers of candidate sites.

We can easily see that limiting the energy spent by each sensor node increases the length of the mobile sink route. Moreover, the number of installed gateways strongly depends on the limit of the energy spent (M inM axE): The amount of forwarding traffic from other sensors is strongly limited. In particular, when we focus on energy (optimizing only MinMaxE, without any constraint on the number of deployed collection points) the optimal solution of our MLP minimizes the energy spent by each sensor essentially by limiting its forwarding traffic. We can thus see that the placement of the collection points verifies that each sensor is a neighbor of its associated gateway (when possible).

In order to get a better analysis about the forwarding traffic related to the energy consumed by the sensors, we have computed the number of paths going through the most loaded sensor node for a given placement of collection points. More formally, given the set of paths as an entry of our problem, we compute for each sensor i the number of paths containing i that have a gateway placed as destination node, and so that the source node of the path is associated with this gateway:

Load(i) = p∈P|i∈p x O(p)D(p) .
The most loaded sensor node is therefore the one that has the maximum number of paths going through it: Load(S) = max i∈S Load(i). Figure 4(b) represents another way of viewing the trade-off between the two objectives, by depicting the maximum number of paths going through the most loaded sensor node in function of the number of deployed gateways in the WSN. We can see that deploying more gateways allows to limit the amount of forwarding traffic at each sensor. When the number of gateway is large enough so that each sensor is a neighbor of one gateway (when possible), then the forwarding traffic becomes null and the sensor spends energy only for sending its own traffic.

When the size of the network increases, then the energy consumption of the sensor nodes also increases (see Figure 2). Indeed, the total traffic in the WSN is more important, so the sensors have more forwarding traffic to relay which increases their load. When the energy is limited to E max = 2 mJ for each sensor, it is worth noting that the length of the mobile sink route also increases with the network size. The average route length of the mobile sink equals respectively 0.33, 0.47, 0.6, and 0.65 for a WSN of 100, 150, 200, and 250 nodes. However, the maximum amount of energy spent by the sensor nodes decreases when the number of candidate sites in the network increases as depicted in Figure 3. On one hand, placing a gateway in a candidate site reduces the relaying traffic and, therefore, reduces the energy spent. On the other hand, the length of the mobile sink's route increases, especially when the energy consumed by each sensor is low. This assertion is confirmed by Figure 4(a) that depicts the number of deployed gateways depending on the maximum energy spent by the sensors.

Graphical trade-off interpretation

The trade-offs among the different metrics are shown using value paths in Figure 5. Value paths have proven to be an effective way to present trade-offs in multi-objective problems [START_REF] Miettinen | Graphical illustration of Pareto optimal solutions[END_REF]. In the figure, there is a vertical axis for each objective. The value assigned to each non-dominated solution on a particular axis is that solution's value divided by the best solution possible for that objective: i.e. f i /f i * for each i = 1, 2. The minimum value for each axis is 1.00, corresponding to the optimal mono-objective solution f 1 * and f 2 * : The minimum energy consumption for M inM axE and the minimum possible route length M inRoute for the mobile sink.

For a network of 50 sensors and 9 candidate sites (Fig. 5(a)), the optimal solution for M inM axE leads to a route 3 times longer than the optimal one. On the contrary, having the optimal route length incurs 233 per cent more in energy consumption than does the best solution. For a fair trade within the two-objectives, the best solution would be of minimizing the maximum value on all the axis: min . But when the number of sensors increases, while the number of candidate sites stays the same, then the scales in the percentage value paths have the same order for M inRoute, and does not increase a lot for M inM axE, because the routing stays roughly the same with the same number of candidate sites. The fair trade non-dominated solution is M inM axE = 0.3mJ and M inRoute = 1.8 for a network with 200 sensors and 25 candidate sites (Fig. 5(c) and 2(c)), which is quite effective. One can remark that the fair trade optimal solution is always closer to the optimal solution of M inM axE because when the route length is optimized, then the energy consumption becomes really bad in the WSN. After analysing such trade-offs, a network manager can then decide which option is preferred. The network manager can also choose the required number of collection points deployed and can then find the best way to route the data with minimum energy consumption.

v max f 1 ,f 2 {f 1 (v)/f 1 * , f 2 (v)/f

Impact of the candidate site positioning

The location of the candidate sites among the WSN is also important regarding the network lifetime and the delay of data collection. In Table results for various topologies in order to compare the two policies of candidate site placement described at the beginning of the section. For each policy (regular grid and random), we compute the optimal value of the 2 mono-objective optimizations f 1 * and f 2 * . On one hand, a regular placement of the collection points always saves energy in the WSN, thus increasing the network lifetime. These results are explained by the fact that the distance between a sensor and a gateway can be bounded due to the regular placement of candidate sites. On the other hand, a random placement of the collection points usually leads to a smaller route for the mobile sink, thus leading to a better data collection. This behavior is due to the possible useless placements of gateways since these placements are randomly chosen. Moreover, due to the same reason, the average number of deployed gateways among the Pareto optimum of the bi-objective optimization Dpl. Gtw is smaller for the random policy. However, the reduction of Dpl. Gtw increases the sensor's average load Load(S) (the mean value Load(S) over the Pareto optimum) compared to a regular placement of candidate sites.

When the candidate sites are regularly placed in the area (i.e. the regular policy as described in Section 5.1), then the sensor's load is significantly reduced in comparison to a completely random placement (see Table 1). This value is always greater of at least 20% when the gateway placement is performed among candidate sites chosen randomly, leading to more loaded sensors in the WSN.

Conclusion

In this paper, we have presented a framework for efficient data collection in wireless sensor networks. We have developed a Multi-objective Linear Program with two metrics to evaluate the trade-off between the maximum amount of energy spent by the sensor nodes, and the length of the route of mobile sinks collecting data at collection points that we jointly deploy. We can see from these particular results that the load of the sensors rapidly decreases with the number of gateways and that above a given number of deployed gateways the load remains stable (or decreases slowly). This allows to save energy in the WSN and maximize its lifetime. When the number of deployed gateways is important, then the mobile sink collecting data at the gateways has a longer route to perform, therefore increasing the delay of data collection until processing.

The proposed model therefore provides a means by which several objectives must be evaluated by a network manager. A fair trade optimal solution is drawn from the obtained Pareto fronts to fairly optimize the metrics. If the energy is the major concern, then the network lifetime objective may be favorable. If the decision maker wants to reduce the delay of collecting the data to ensure fast processing, he or she may give a higher priority to the route length objective when compared to other objectives. Hence, there is a critical necessity to incorporate all the different objectives when we model the data collection plan in WSNs.

Fig. 1 .

 1 Fig. 1. Non-dominated and dominated solutions for a 2-function minimization problem.

Fig. 4 .

 4 Fig. 4. Results for random networks with 25 candidate sites.

( c )Fig. 5 .

 c5 Fig. 5. Percentage path analysis for delay-energy trade-off.

  Pareto fronts for random networks with 50 sensors and different number of candidate sites |CS |.

		2.2										2.2
		2										2
		1.8										1.8
	MinMaxE (mJ)	0.6 0.8 1 1.2 1.4 1.6									MinMaxE (mJ)	0.6 0.8 1 1.2 1.4 1.6
		0.4										0.4
		0.2										0.2
		0										0
		0	0.3	0.6	0.9	1.2	1.5	1.8				0	0.3	0.6	0.9	1.2	1.5	1.8
					MinRoute									MinRoute
				(a) |CS | = 9									(b) |CS | = 16
		2.2										2.2
		2										2
		1.8										1.8
	MinMaxE (mJ)	0.6 0.8 1 1.2 1.4 1.6									MinMaxE (mJ)	0.6 0.8 1 1.2 1.4 1.6
		0.4										0.4
		0.2										0.2
		0										0
		0	0.3	0.6	0.9	1.2	1.5	1.8				0	0.3	0.6	0.9	1.2	1.5	1.8
					MinRoute									MinRoute
				(c) |CS | = 25									(d) |CS | = 36
	Fig. 3. MinMaxE (mJ) 0 0.5 1 1.5 2 Nb of installed gateways 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15	2.5	3 250 nodes 200 nodes 150 nodes 100 nodes 50 nodes	3.5	Nb paths on most loaded sensor	0 2 4 6 8 10 12 14 16 18 20 32 30 28 26 24 22	1	3	Nb of installed gateways 5 7 9 11	13 250 nodes 15 200 nodes 150 nodes 100 nodes 50 nodes
	(a) Number of deployed gateways de-	(b) Number of paths through the most
	pending on Emax.							loaded sensor depending on gateways.

  2 * }. The non-dominated solution optimizing the fair trade is thus the one incuring 66 percent more in energy

	3.33		27.45		57.65
						7.06
		3.00		6.79	45.50	6.75
			21.57
		2.71				6.06
	2.55
		2.41	17.06			5.45
				5.03	34.33	5.06
				4.76		4.88
	2.11
		2.00			24.53	4.45
			10.80 11.57	4.03 3.76	21.27	4.03 3.75
	1.66	1.71			16.69
			8.92
				3.03	13.35	3.03
	1.33	1.41	6.39	2.44 2.73	8.84 11.10	2.73
					7.84	2.42
	1.11		4.31	2.00	6.88 5.88	2.00
	1.00	1.00	3.00 2.31	1.42	3.92	1.73
					2.96
	MinMaxE	MinRoute	MinMaxE 1.00	MinRoute 1.00	MinMaxE 1.00	MinRoute 1.00
	(a) |S| = 50, |CS | = 9	(b) |S| = 50, |CS| = 25

Table 1 .

 1 1, we present (mJ) f 2 * Dpl. Gtw Load(S) f 1 * (mJ) f 2 * Dpl. Gtw Load(S) Comparison between regular and random placement of the candidate sites.

	Topology		Grid placement			Random placement
	|S| |CS | f 1 * 50 9 0.45	0.5	3.5	8.93	0.45	0.21	2.96	13.24
	50	16	0.15	0.4	4.25	8	0.35	0.22	4.63	9.83
	50	25	0.05	0.33	4.29	7.59	0.15	0.02	4.93	12.57
	100	9	0.45	0.5	3.33	10.2	0.65	0.28	3.71	21.26
	100 16	0.35	0.4	4.81	9.87	0.65	0.21	4	21
	100 25	0.05	0.33	4.7	9.05	0.25	0.03	4.24	23.74
	150	9	0.75	0.5	2.85	17	0.95	0.08	3.05	27.88
	150 16	0.45	0.4	4.24	12.76	0.75	0.01	4.41	20.53
	150 25	0.15	0.33	4.77	14.24	0.25	0.04	3.76	32.78
	200	9	0.85	0.5	3.9	16.3	0.95	0.22	3.17	20.79
	200 16	0.25	0.4	4.77	13.5	1.05	0.11	3.53	27.4
	200 25	0.05	0.33	4.4	15.84	0.35	0.07	4.43	34.3

⋆ Supported by an Alexander von Humboldt fellowship for postdoctoral researchers.

http://www.ibm.com/software/integration/optimization/cplex-optimizer/