Nicole M Le Douarin

José M Brito

Sophie Creuzet

Research Reviews -Special Issue ROLE OF THE NEURAL CREST IN FACE AND BRAIN DEVELOPMENT

Keywords: Craniofacial development, Endoderm, Prosencephalon, Shh, Fgf8, Quail-chick chimeras ANR, anterior neural ridge, BA: branchial arch, E, embryonic day, NC, neural crest, NCC neural crest cells, NT, neural tube, r, rhombomere, ss: somite stage, ZLI, zona limitans intra-thalamica

Since the time of Ramon y Cajal, very significant progress has been accomplished in our knowledge of the fate of the early neural primordium. The origin of the peripheral nervous system from the transient and pluripotent embryonic structure, the neural crest has been fully deciphered through the use of appropriate cell marking techniques. Most of the pioneer work in this field was carried out in lower vertebrates up to 1950 and later on in the avian embryo. New techniques which allow the genetic labelling of embryonic cells by transgenesis are now applied in mammals and fish.

One of the highlights of neural crest studies was its paramount role in head and face morphogenesis. Work pursued in our laboratory for the last fifteen years or so has analysed at both cellular and molecular levels the contribution of the NCC to the construction of the facial and cranial structures. Recently, we have found that the cephalic neural crest plays also a key role in the formation of the fore-and mid-brain.

Introduction

The neural crest (NC) was discovered by Wilhem His in 1868 in the chick in which he called it Zwischenstrang, meaning that it appears just after the closure of the neural tube (NT) as a "band of particular material lying between the NT and the superficial ectoderm" (quoted from Sven Horstadius in "the Neural Crest", 1950). W.His noticed that the cells forming the NC rapidly started to migrate away from the neural primordium and, as seen under the microscope, aggregated laterally to the neural tube to form the dorsal root ganglia. Hence, the term of "ganglionic crest" also attributed to this structure.

Investigations carried out mainly in lower vertebrates at the turn of the XX th century revealed that the NC was the source of many other derivatives. Apart from the components of the peripheral nervous system and melanocytes, it was shown to yield cells participating in the formation of the facial skeleton. The first mention that "some mesenchymal cells" of the head are of NC origin was from Katschenko in 1888 in selacians. This notion was extended to teleosts and birds by Goronowitsch (1892;1893). Julia Platt then claimed that NC-derived cells contributed to the cartilage of the visceral arches and to the dentine of the teeth (1893; 1897). She coined the term of mesectoderm to designate these cells which were different in origin from the rest of the body mesenchyme which is derived from the mesodermal germ layer and that she called mesendoderm. The term mesectoderm or ectomesenchyme have subsisted until now to designate the mesenchyme derived from the NC, thus of ectodermal origin.

These seminal observations were not readily accepted at the end of the XIX th century since the germ layer theory developed by von [START_REF] Baer | Ueber Entwicklungsgeschichte der Tiere[END_REF] was still powerful. According to the latter, the skeletal tissue was considered to be exclusively derived from the mesoderm.

However, the contribution of the mesectoderm to the head skeleton was further confirmed during the first half of the XX th century. A thorough account of the investigations carried out on this problem essentially on the amphibian embryos can be found in the monograph written by Horstadius in 1950. The work of Pierre Chibon in France (1964) based on the use of a cell-marking technique using tritiated thymidine ([ 3 H]TdR) to label neural crest cells (NCC), fully confirmed the results of the previous investigations. This technique has also been used in the chick embryo by Jim Weston in 1963. This was the first attempt to follow the migration of NCC in higher vertebrates by means of an efficient cell-marking technique (see le Douarin, 1982, and references therein). Labelling cells with [ 3 H]TdR to investigate the fate of the cephalic NCC in the chick embryo was first undertaken by Malcolm C. Johnston (1966) and later on by Drew Noden (1975;1976;1978a, b), The demonstration that the entire facial skeleton and most of the skull were formed by cells of ectodermal origin was brought about after the quail-chick chimera system was devised by one of us (Le Douarin, 1969;1973a;1973b;1974;1976). This technique which provides a stable cell labelling allowed to demonstrate that the NC is the only source of the cells forming the facial skeleton. Moreover, it led to the construction of a very precise fate map of the cephalic NC derivatives (Le Lièvre et Le Douarin, 1975;Le Lièvre, 1978;[START_REF] Couly | The triple oprigin of skull in higher vertebrates : a study in quail-chick chimeras[END_REF][START_REF] Couly | The regeneration of the cephalic neural crest, a problem revisited : the regenerating cells originate from the contralateral or form the anterior and posterior neural fold[END_REF]Köntges and Lumsden, 1996).

The role of the cephalic neural crest in the formation of craniofacial structures

Although in fish the NC of the entire neural axis is at the origin of mesectodermal derivatives (see Le Douarin, 1982, andLe Douarin andKalcheim, 1999, for references), in higher vertebrates, the ability of the NCC to form skeletal tissues is not uniformly distributed along the antero-posterior axis. Yielding cartilage and endochondral bone appears as a ground property of the skeletogenic NC corresponding to the domain located between the middiencephalic level to rhombomere 8 (r8) included. However, within this domain, the capacity of NCC to form membrane bones (e.g. skull bones) is restricted to its most rostral part corresponding to NCC of the nasofrontal and maxillo-mandibular processes. The rostral NC which forms the craniofacial skeleton is designated FSNC (for Facial Skeletogenic NC; Fig. 1A,B).

These different domains exhibit distinct molecular traits. The caudalmost domain of the cephalic NC (from r4 down to r8) expresses Hox genes of the first four paralogous groups (Hunt et al., 1991;Prince and Lumsden, 1994;Köntges and Lumsden, 1996;[START_REF] Couly | The regeneration of the cephalic neural crest, a problem revisited : the regenerating cells originate from the contralateral or form the anterior and posterior neural fold[END_REF]. Rostrally, the FSNC (from mid-diencephalon down to r2) does not express any Hox genes (it is referred to as Hox-negative). At the edge of both, NCC from r3 exhibit a versatile Hox gene status according to the environment into which they migrate (Graham et al., 1993;1994;[START_REF] Creuzet | Reciprocal relationships between Fgf8 and neural crest cells in facial and forebrain development[END_REF]. The cells exiting from r3 level and contributing to the first branchial arch (BA1) lose their Hoxa2 expression, whereas those migrating to BA2 maintain it (Fig. 1C-F).

The Hox-negative cephalic NC is the only domain able to yield the facial skeleton

If the entire Hox-negative NC domain is removed, no facial structures develop (Couly et al., 2002;[START_REF] Creuzet | Negative effect of Hox gene expression on the development of neural crest derived facial skeleton[END_REF]; Fig. 2A,B). Moreover, if grafted to the anterior domain, Hoxexpressing NCC cannot substitute for the Hox-negative ones [START_REF] Couly | Determination of the identity of the derivatives of the cephalic neural crest : incompatibility between Hox gene expression and lower jaw development[END_REF]2002; Fig. 2C,D). In this experimental situation, however, the Hox-positive cells migrate within the foremid-brain area and maintain their Hox gene expression at least up to embryonic day 6 (E6). These Hox-positive cells differentiate into neural derivatives, yield some connective-like cells but do not differentiate into cartilage and bones (see Fig. 4 in [START_REF] Couly | Interactions between Hoxnegative cephalic neural crest cells and the foregut endoderm in patterning the facial skeleton in the vertebrate head[END_REF]. By contrast, any fragment (about a third of the normal Hox-negative NC domain) of the Hox-negative NC can regenerate a normal face if left in situ (or if grafted from a quail to a chick embryo following the excision of the entire host Hox-negative NC; [START_REF] Couly | Interactions between Hoxnegative cephalic neural crest cells and the foregut endoderm in patterning the facial skeleton in the vertebrate head[END_REF]; Fig. 2E,F). Thus, the Hoxnegative NCC behave as an "equivalence group". Since any small region of this area is able to yield the same derivatives as the whole area itself. One can then conclude that NCC do not possess the information to pattern each of the skeletal elements forming the facial skeleton. This information has thus to come from the environment in which the facial skeleton develops.

Inhibition of the development of skeletal tissues by Hox gene expression in the rostral NC domain

Another question raised by these experiments was whether forced expression of Hox genes in the rostral NCC exerts an inhibition on facial skeleton development. This possibility was tested in experiments where Hox gene expression was experimentally targeted to the FSNC by electroporation of Hoxa2, Hoxa3 or Hoxb4 constructs into the pre-migratory NCC. Expression of these genes was found to preclude the development of the facial skeleton [START_REF] Creuzet | Negative effect of Hox gene expression on the development of neural crest derived facial skeleton[END_REF]; Fig. 2G-M).

Role of the foregut endoderm in patterning the facial skeleton

The next step of our investigation was to look for a source for the information able to pattern the facial skeleton from the Hox-negative NCC. It has been known for long that the interaction between NCC and the pharyngeal endoderm is critical for branchial skeleton development. Experiments performed in amphibians, chick and mouse, involving explants of NC-derived mesenchyme, showed that the mesenchyme of crest origin can differentiate into cartilage only if co-cultured or co-grafted in contact with pharyngeal endoderm (Epperlein and Lehmann, 1975;Hall and Armstrong, 1980;Graverson and Hall, 1987;Seufert 1990). In contrast, the differentiation of other NC derivatives such as melanocytes, ganglia, nerves lined by Schawnn cells, does not depend on the presence of endoderm (Epperlein, 1978). Moreover, organ culture of chick mandibular ectomesenchyme at E3, after removal of the ectodermal epithelium, does not prevent chondrogenesis to occur, while membrane bone formation does not take place in these explants (Takahashi et al, 1991).

In vivo, mutation of the van gogh (vgo) gene in zebrafish prevents the segmentation of the pharyngeal endoderm and consequently the formation of pharyngeal pouches. Pharyngeal cartilages differentiate and fuse to form a single piece of cartilage. Thus, during embryonic development, formation of the visceral cartilages directly depends on the segmentation of pharyngeal arches (Piotrowski and Nüsslein-Volhard, 2000). Therefore, the pharyngeal endoderm has at least two roles: first on NCC differentiation into cartilage and second in BA segmentation a process critical for patterning the branchial cartilages.

Furthermore, disruption of the Nodal pathway by mutation of casanova (cas) gene, completely hampers endoderm development in zebrafish and results in the absence of all the branchial cartilages. In absence of endoderm, the cephalic NCC fail to migrate ventrally and the expression of chondrogenic markers is down-regulated [START_REF] Alexander | casanova plays an early and essential role in endoderm formation in zebrafish[END_REF]David et al., 2002). Moreover, repression by morpholinos of Fgf3 production by the pharyngeal endoderm results in defects in the posterior arch derivatives, without affecting the first and second BAs (David et al;2002). Hence, the endoderm is essential for development of the BAs. It is a source of growth factors which display different antero-posterior distribution and have specific functions in the ontogeny of the visceral skeleton.

Another set of evidence on the role of the pharyngeal endoderm of facial skeleton development was provided by experiments carried out in our laboratory in chick embryos. Ablation of antero-posterior stripes of foregut endoderm at 5-6 somite stage (5-6ss) resulted in the loss of skeletal pieces specific of the level of ablation [START_REF] Couly | Interactions between Hoxnegative cephalic neural crest cells and the foregut endoderm in patterning the facial skeleton in the vertebrate head[END_REF]. This is in agreement with previous observation that the presence of the pharyngeal endoderm is critical for the migration of the NCC leading to the development of the branchial arches [START_REF] Alexander | casanova plays an early and essential role in endoderm formation in zebrafish[END_REF]. In addition, it was possible to demonstrate that orthotopic grafts of the same stripes of quail ventral foregut endoderm into an intact chick embryo induced the duplication of the bone rudiments that normally develop at this level [START_REF] Couly | Interactions between Hoxnegative cephalic neural crest cells and the foregut endoderm in patterning the facial skeleton in the vertebrate head[END_REF]. Thus, graft of the endoderm of the anterior foregut of 5-6ss quail embryos (see zone II/III; fig. 3A) at the presumptive level of BA1 ectoderm [START_REF] Couly | Head morphogenesis in embryonic avian chimeras: evidence for a segmental pattern in the ectoderm corresponding to the neuromeres[END_REF] leads to the formation of an extra-Meckel's cartilage in addition to the endogenous lower jaw (Fig. 3B,C). It is noteworthy that the extra-cartilage tissue was exclusively made up by endogenous NCC of the chick host embryo (see Couly et al., 2002, fig. 9C). The role of the quail endoderm was only to induce the formation of this extra bone. Moreover, changing the antero-posterior (AP) and dorso-ventral (DV) orientation of the grafted endodermal stripes modified the polarity of the supernumerary cartilage elements (see Couly et al., 2002, fig.10). Conversely, the grafts of the ventral foregut endoderm were not able to induce BA1-type cartilages or bones in the posterior BAs (in which the endoderm, NCC and surrounding tissues express Hox genes) [START_REF] Couly | Interactions between Hoxnegative cephalic neural crest cells and the foregut endoderm in patterning the facial skeleton in the vertebrate head[END_REF]. One can therefore conclude that the anterior ventral endoderm of the 5-6ss embryo foregut is able to trigger the skeletogenic developmental programme of the lower jaw when it is in the context of BA1.

The nature of the signal through which this programme is initiated was the subject of our recent investigation.

Role of Shh in triggering the development of the lower jaw.

The disruption of Shh gene in the mouse by [START_REF] Chiang | Cyclopia and defective axial patterning in mice lacking Sonic hedgehog gene function[END_REF] revealed the paramount role of this morphogen in the development of the vertebrate head and particularly of its craniofacial skeleton. In Shh-/-mutant embryos, the expression of several genes fails to be activated in the developing BA1. Such is the case for Fgf8, Bmp4, Barx1, Gsc, Sox9 and Twist (Moore-Scott and Manley, 2005;Washington-Smoak et al., 2005;Yamagishi et al., 2006). The source of the Shh morphogen playing a role in the induction and/or maintenance of expression of these genes was not known until recently.

We were able to show that Shh produced by the anterior foregut endoderm is critical for lower jaw development [START_REF] Brito | An early role for sonic hedgehog from foregut endoderm in jaw development: ensuring neural crest cell survival[END_REF]. In chick embryos the expression of Shh in the foregut endoderm starts at about 4-5ss in the most rostral part of the endoderm which is in close contact with the prechordal plate (Fig. 3D,E). At 6ss, Shh is expressed in the ventral part of the endoderm down to the level of the prosencephalon-mesencephalon boundary. Shh expression in the foregut endoderm remains restricted to its anterior ventral domain up to 16ss. Later on, Shh transcripts are present along the whole pharyngeal ventro-lateral endoderm from which BA1 endodermal pouches eventually form. Excision of the forehead (including the complete area of the anterior foregut endoderm producing Shh) at 5-6ss prevented the expression of Shh in the first branchial pouch endoderm. The NCC however colonized BA1 but failed to survive and the absence of lower jaw ensued (Fig. 3F,F'). At E3-4, expression of Fgf8, Bmp4 and Pitx1 in the oral ectoderm did not occur. The same was true for Pitx1 in the mesenchyme of BA1.

We decided to try and substitute the normal source of Shh production by providing the decapitated embryos with Shh-soaked beads as indicated in figure 3I. This was followed by the expression of Shh in the endoderm of the first branchial pouch and by the survival of NCC which had colonized BA1. The development of a lower jaw was rescued as seen at E11 (Fig. 3J,K). Expression of Pitx1, Bmp4 and Fgf8 was restored in BA1 (see Brito et al., 2006, fig 3N,Q). Although, at these early stages, Shh is produced by various other sources (ventral neuroectoderm, notochord and facial ectoderm), the most important one for BA1 development is the ventral foregut endoderm.

On the same line, the culture of E3 chick embryo BA1 in which the endoderm had been removed, did not show expression of Fgf8 in the ectoderm of BA1. Interestingly, treatment of these cultures with Shh-soaked beads was able to restore this expression (Haworth et al., 2004;[START_REF] Brito | An early role for sonic hedgehog from foregut endoderm in jaw development: ensuring neural crest cell survival[END_REF].

In conclusion, the foregut endoderm is a source of morphogens crucial for the development of BA1 derivatives. Among those, Shh plays a key role in the survival of the NCC which have migrated to BA1 and in the induction of several downstream gene activities critical for their further developmental programme.

NCC and Fgf8 expression from ectoderm : a reciprocal signalling process

As described above, excision of the FSNC results in the agenesis of the facial skeleton. In addition, it promotes a strong impairment of brain development (Fig. 2B,D). Removal of the FSNC is accompanied by the nearly complete absence of Fgf8 expression in BA1 ectoderm and in the anterior neural ridge (ANR; Fig. 4B). In FSNC-ablated embryos, defects are significantly corrected by implantation of Fgf8-soaked beads either laterally to the presumptive ANR or on the bilateral BA1 ectodermal presumptive territories. In these cases, the upper and lower jaw skeleton develops, closure of the NT takes place and the overall development of the brain tends to normalize (Fig. 4F).

The results of these Fgf8-rescue experiments raised the question of the origin of the NCC responsible for regeneration of the face. Replacing r3 in chick FSNC-deprived embryos by its quail counterpart showed that Fgf8 supply strongly stimulates the r3-derived NCC growth. These cells migrate massively rostrally and colonize BA1 as can be seen by staining r3-derived NCC by the quail specific antibody QCPN (Fig. 4G,H). In addition, the cells which have invaded BA1 become Hoxa2-negative whereas those which have migrated into BA2, remain Hoxa2positive (see Creuzet et al., 2004, fig. 1W-Z). This is in agreement with the fact that when high expression of Hoxa2 is experimentally imposed to BA1-NCC [START_REF] Creuzet | Negative effect of Hox gene expression on the development of neural crest derived facial skeleton[END_REF], no differentiation of skeletal tissue ensues. Moreover, this result shows that maintenance of expression of this gene depends upon cues arising from the environment. These cues are clearly missing in BA1.

In experiments where the excision of FSNC includes r3, it is seen that NCC from r4 do not migrate to BA1 even when Fgf8 beads are present. These experiments demonstrate the strong regeneration capacities and the high degree of plasticity displayed by the pre-otic NCC and the absence of such properties in post-otic NCC.

In vivo silencing of FGF8 gene in BA1

The above described experiments suggest a chemo-attractive role of Fgf8 in directing the migratory flux of NCC. In order to further explore this problem, double strand RNA designed from the Fgf8 c-DNA (Pekarik et al., 2003) was introduced by electroporation into the superficial ectoderm of the presumptive BA1 territory on the right side of 5-6ss chick embryos, the contralateral side being the control. The aim of this inhibition of Fgf8 protein synthesis was to see whether the migration of NCC was disturbed on the experimental side. When the embryos were observed at E2.5 (25ss) after whole-mount immunostaining of NCC by the HNK1 monoclonal antibody [START_REF] Abo | A differentiation antigen of human NK and K cells identified by a monoclonal antiboby (HNK-1)[END_REF]Tucker et al., 1984;Vincent and Thiery, 1984) which decorates migratory NCC, the experimental side was strikingly devoid of NCC [START_REF] Creuzet | Reciprocal relationships between Fgf8 and neural crest cells in facial and forebrain development[END_REF], showing that Fgf8 expression by the ectodermal component of BA1 is critical for its colonization by NCC. Whether this effect is related to the stimulation of NCC survival and proliferation or to a chemo-attractive process remains to be investigated.

NCC signal regulates FGF8 expression in the superficial and neural ectoderm of the ANR

The previously described experiments showed that removal of the anterior (Hoxnegative) NCC at pre-migratory stages strongly precludes Fgf8 expression in ANR ectoderm. In order to know if this effect can be mediated exclusively by the FSNC, we replaced the Hoxnegative NCC domain by the neural fold corresponding to r4-r6 from 5-6ss quail embryos (Fig. 4I). The results observed from E2 to E11 showed that the NCC from the Hox-positive domain had normally migrated. At E2.5, they had invaded the space between the prosencephalic neural epithelium and the superficial ectoderm (Fig. 4J-L), where they were mixed up with chick mesodermal cells as in normal development (see Etchevers et al., 1999, fig. 7 andEtchevers et al., 2001, Figs. 2 and3). Interestingly, the superficial ectoderm and the neural epithelium corresponding to the ANR exhibited abundant Fgf8 transcripts (while NCC did not; Fig. 4M). At E6, the head morphology of these embryos was characterized by the dorsal closure of the brain, a rudimentary BA1 and a strongly reduced forebrain (Fig. 4N). At E8, the lower jaw skeleton had further developed (Fig. 4O,P). At E11, the lower jaw skeleton was nearly complete, the occipital and otic regions of the skull of mesodermal origin (see [START_REF] Couly | The triple oprigin of skull in higher vertebrates : a study in quail-chick chimeras[END_REF] were present. In contrast, the nasal skeleton was absent as well as the frontal and parietal bones (Fig. 4Q).

The interpretation of this experiment was that NCC, whether originating from the anterior Hox-negative domain (as in normal development) or from a more caudal (Hox-positive) area of the neural axis exert a positive effect on Fgf8 production by the superficial and neural ectoderm of the ANR. The embryos subjected to this operation are therefore in a situation comparable to those in which the normal source of Fgf8 was replaced by exogenous Fgf8-soaked beads. In both cases, r3-derived NCC invade BA1 (Fig. 4K) and develop into a lower jaw (Fig. 4O-Q; [START_REF] Creuzet | Reciprocal relationships between Fgf8 and neural crest cells in facial and forebrain development[END_REF]).

The role of the NC in patterning the pre-otic brain.

During embryogenesis, regionalisation of the neural plate and the neural tube is controlled by secreted molecules of the Shh, Fgf, and Wnt families which are endowed with morphogenetic properties. These morphogens were shown to be involved in the regulation of pre-otic brain development. They are produced from signalling centres (the ANR, the isthmus, the dorsal midline, the Zona Limitans Intrathalamica -ZLI-, and the floor plate) that act on brain regionalisation. These centres regulate the expression of definite transcription factors that control the identity of thevarious domains of the neural epithelium (Martinez et al., 1999;McMahon and Bradley, 1990;Houart et al., 1998;Reifers et al., 1998;Vieira et al., 2005). These signalling centres are considered as "secondary brain organizers". Distinct sets of signals are produced by each of them : Shh by the basal plate and the ZLI, Wnt by the dorsal midline, Fgf8 by the ANR and the isthmus.

In FSNC-deprived embryos, the brain remains wide open all along the resected territory and the cephalic vesicles (tel,-di-, and mesencephalon) are no longer distinguishable. The prosencephalic and mesencephalic exencephaly is accompanied by the complete loss of the dorso-medial markers, Wnt1 and Wnt8b (Fig. 4R,S). In the telencephalic primordium, expression of Emx2, Pax6 and Dlx2 is severely reduced (Fig. 4U,V). Moreover, a striking dorsalization of Shh transcript distribution increases the prosencephalic basal plate at the expense of the alar plate. At this level, Otx2 expression is up-regulated as if the diencephalic alar plate was posteriorized. Long-term structural defects in the dorsal diencephalic midline ensue, together with agenesis of the thalamic and pre-tectal nuclei (Creuzet et al., 2006).

In the embryos subjected to FSNC removal and further supplemented FGF8-soaked beads at the level of the ANR, the morphogenesis of the brain is mostly rescued. As mentioned above, exogenous FGF8 stimulates the progression of NCC (from the edge of the excised territory, i.e. r3) to the forehead. Our data show that NCC migrating rostrally are necessary for the neural tube of the mid-and fore-brain to close. Moreover, the deployment of NCC restores the antero-posterior division of the cephalic vesicles and rescues the growth of the prosencephalic alar plate as shown by the expression of genes normally detected dorsally (Wnt1, Wnt8b, Emx2, Pax6, Otx2; Fig. 4T,W). These data suggest that NCC also repress the Shh ventral signalling arising from the basal plate (Creuzet et al., 2006).

Concluding remarks

Altogether, our data support the emerging picture that the cephalic NC coordinates the formation of craniofacial structures and the development of the anterior encephalic vesicles. The ventral foregut endoderm is essential for the development of the facial skeleton since it provides the facial skeletogenic neural crest cells (FSNC) with a survival signal mediated by Shh (Fig. 5). Shh also induces the expression of a set of genes which are critical for patterning the facial structures. These genes are expressed either in the ectoderm (Bmp4, Fgf8) or in the mesectoderm (Pitx1) of the facial processes. Fgf8 is itself crucial for the migration, further survival and proliferation of Hox-negative NCC (Fig. 5).We have discovered a novel role for the Hox-negative NCC on brain development (Creuzet et al., 2006). Removal of the FSNC (from mid-diencephalon down to r2 included) results in exencephaly at the level of fore-and midbrain. The neural tube does not close dorsally and most of the alar plate-derived structures do not develop. If the lack of Fgf8 in the ANR is compensated by an exogenous source of Fgf8, NCC from r3 migrate rostrally and mostly rescue brain development. In addition, the NC is at the origin of (still unknown) signals that trigger and maintain the expression of Fgf8 in the ANR ectoderm. Fgf8 of ANR origin exerts a positive effect on the patterning of the basal plate in the di-and mesencephalon as attested by the restriction of Shh expression to the ventral midline and ZLI when exogenous Fgf8 is provided to FSNC-ablated embryos. On the other hand, the NC has a direct effect on patterning the development of alar and roof plates in the di-and mesencephalon. It is also essential for the normal forward extension of the telencephalon.

Figures and legends

Figure 1 :

 1 Figure 1 : Skeletogenic NC and craniofacial development.

Figure 2 :

 2 Figure 2 :

Figure 3 :

 3 Figure 3:

Figure 4 :

 4 Figure 4 :

Acknowledgements :

Work in the authors' laboratory is supported by the Centre National de la Recherche Scientifique, Association pour la Recherche sur le Cancer (grant n°3929). J.B. is a recipient of a fellowship from la Fondation pour la Recherche Médicale.

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 [START_REF] Couly | Interactions between Hoxnegative cephalic neural crest cells and the foregut endoderm in patterning the facial skeleton in the vertebrate head[END_REF]. This effect is mediated (partly) by Shh which triggers the survival of the NCC and re-establishes the normal patterning of gene expression in BA1 ectoderm. Presence of NCC in BA1 is critical for expression of Fgf8 in BA1 ectoderm. Fgf8 has a positive effect on NCC migration and proliferation [START_REF] Creuzet | Reciprocal relationships between Fgf8 and neural crest cells in facial and forebrain development[END_REF].


Bruno Rodrigues
email: rodrigues@ifi.uzh.ch

Thomas Bocek
email: bocek@ifi.uzh.ch

Burkhard Stiller
email: stiller@ifi.uzh.ch

Multi-domain DDoS Mitigation based on Blockchains

Keywords: Distributed Denial-of-Service (DDoS), Security, Blockchain, Software-defined Networks (SDN), Network Management

The exponential increase of the traffic volume makes Distributed Denial-of-Service (DDoS) attacks a top security threat to service providers. Existing DDoS defense mechanisms lack resources and flexibility to cope with attacks by themselves, and by utilizing other's companies resources, the burden of the mitigation can be shared. Technologies as blockchain and smart contracts allow distributing attack information across multiple domains, while SDN (Software-Defined Networking) and NFV (Network Function Virtualization) enables to scale defense capabilities on demand for a single network domain. This proposal presents the design of a novel architecture combining these elements and introducing novel opportunities for flexible and efficient DDoS mitigation solutions across multiple domains.

Introduction and Motivation

A Distributed Denial-of-Service (DDoS) attack is a large-scale, coordinated attempt to make a target system's resources unavailable. Although being a known category of attack, it remains as one of the major causes of concern for service providers. The increasing number of unsecured connected devices (stationary and portable) and their growing processing capacity, allow attackers to take control of a vast amount of unsecured devices that ranges from connected cameras to smart fridges to generate malicious attacks.

Major causes of concern for service providers is that not only the volume of traffic of DDoS attacks is growing, but also their complexity. Botnets taking advantage of unsecured IoT (Internet of Things) devices are the primary cause of these large-scale attacks. The Mirai botnet [START_REF] Gamblin | Source code of the mirai botnet available on github[END_REF], for example, exploits default and weak security credentials to spread itself for other devices.

In an attack launched on Krebs Security [START_REF]Akamai: How to Protect Against DDoS Attacks -Stop Denial of Service[END_REF] website in September 2016, Mirai peaked 623 Gbps in volume of traffic. Akamai, the service hosting the website, had to shut down the site because defending it during three days became too costly. It was reported that so many devices were used that the attacker did not have to use any sophisticated strategy.

Problem Description

As DDoS attacks become progressively sophisticated and coordinated, the defense from such attacks likewise needs distribution and coordination. To prevent or reduce damages caused by these DDoS attacks, different detection and mitigation methods are available.

Typical implementation is based on dedicated ASIC-based appliances to analyze flow records exported from edge routers, and further filtering or load balancing traffic. Cloud-based solutions such as Cloudfare [START_REF] Cloudfare | Cloudflare advanced ddos protection[END_REF] and Akamai [START_REF]Akamai: How to Protect Against DDoS Attacks -Stop Denial of Service[END_REF] can take away the burden of detection and mitigation, serving as a proxy able to load balance, reroute, or drop the traffic in case of DDoS attacks.

Many centralized defense systems lack of hardware resources or software capabilities to detect and mitigate attacks themselves. Traditional or cloud-based defenses can become a communication bottleneck due to the need to download and process all the traffic measurements at a single location. Thus, if an attack is highly sophisticated and there is no countermeasure available, legitimate users may be impaired until the attack stops.

An alternative is sharing hardware and defense capabilities with other systems, an approach called cooperative DDoS mitigation. However, existing cooperative approaches involve the proposal of a particular distributed architecture and protocols that usually require the modification of existing hardware and software in its support.

State-of-the-art

Although there are several related works, concepts and technologies guiding the development of the proposal, for brevity in this section we highlight only three main related works. Internet Engineering Task Force (IETF) is proposing a protocol [START_REF] Nishizuka | Inter-organization cooperative ddos protection mechanism[END_REF] named DOTS (DDoS Open Threat Signaling) covering both intraorganization and inter organization communications. DOTS requires servers and clients organized in both centralized and distributed architectures to advertise black or whitelisted addresses. However, DOTS presents a complex architectural design, which hinders your deployment without the complete standardization of the DOTS protocol. A different approach is [START_REF] Sahay | Towards autonomic ddos mitigation using software defined networking[END_REF], proposing a collaborative framework that allows the customers to request DDoS mitigation from ASes. However, the solution requires an SDN controller at customer side interfaced with the service provider, which can change the label of the anomalous traffic and redirect them to security middle-boxes. A similar approach is seen in [START_REF] Rashidi | Cofence: A collaborative ddos defence using network function virtualization[END_REF]. The authors propose a cooperation between domains that implements VNFs to alleviate DDoS attacks by redirecting and reshaping excessive traffic to other collaborating domains for filtering. However, the proposal still requires the support of a gossip-based protocol by the network infrastructure to exchange information about attacks.

Research Questions

Many research challenges are found in the current scenario to improve current DDoS defense mechanisms not only in a single domain, but in a cross-domain perspective. Expected contributions of this work are categorized herein into three major stages of the DDoS protection: 1) analysis and detection, 2) collaboration across multiple domains, and 3) scalability of the proposed solution. Therefore, contributions of this work are expected to answer the following research questions:

RQ1: How to efficiently identify traffic types avoiding that, in presence of attacks, legitimate users may be hampered by the traffic of attackers? This proposal involves the identification of techniques based on machine learning to promote the signaling of attacks. RQ2: How to simplify existing cooperative DDoS architectures and protocols so minimal hardware and software modifications are necessary to advertise DDoS information across multiple domains? In addition, it is necessary to investigate an incentive scheme to balance the relationship between cooperative entities, preventing a domain from abusing the cooperative scheme. RQ3: How does the solution scale to report a number of addresses given the scale of devices involved in large-scale attacks?

Approach and Next Steps

A novel approach is presented herein to mitigate DDoS attacks across multiple domains. Recent advances on networking technology, such as Software-defined Networking (SDN) and Network Function Virtualization (NFV) are gaining attention towards the establishment of software-defined infrastructures. Blockchain and Smart Contracts may be used to advertise information across multiple domains, reducing the complexity of distributed protocols and architectures for gossiping DDoS attacks information. Figure 1 illustrates the proposed architecture of the system.

-Software-Defined Networks (SDN): enable the development of customizable security policies and services managed in a dynamic, softwarebased fashion. Among the available SDN controllers, Ryu is an open-source controller providing an well defined API for interacting and managing applications. -Network Function Virtualization (NFV): enforce the security policies of the centralized control through virtualized functions provisioned in generic hardware. The VNF-BC is the virtual appliance deployed both on the network domain and customers, that may inteface with network management systems, and optionally import flow-records of widely used network monitoring tools, as sFlow or NetFlow. SDNs optimize the management of flows in response to attacks by enabling the deployment of sophisticated traffic analysis based on global network awareness given by a centralized controller. Aligned, SDN and NFV offer flexible and programmable network infrastructures toward generic network hardware deployed on open software, in which functions of the centralized control can be performed through virtualized network functions (VNF) and capabilities from NFV.

Security policies and thresholds may be defined based on historical records directly obtained from southbound protocols such as OpenFlow or SNMP, or exported from monitoring tools as sFlow or NetFlow. In response to attacks, the SDN controller may dynamically provision virtual functions for firewalling, packet inspection (e.g., Snort), or black-holing malicious traffic.

Blockchain and Smart Contracts can be used to advertise DDoS attacks information across multiple domains [START_REF] Bocek | Smart Contracts -Blockchains in the Wings[END_REF]. This simplifies existing cooperative DDoS mechanisms by using an existing distributed infrastructure to broadcast black or whitelisted addresses without the need to build specialized registries or other dis-tribution mechanisms/protocols. The Ethereum blockchain supports a Turingcomplete contract language [START_REF] Bocek | Smart Contracts -Blockchains in the Wings[END_REF], such as Solidity. Therefore, a node participating in the Ethereum blockchain runs a Solidity smart contract by executing a script, which is used to store references to the advertised addresses. The contracts is further processed checking if the entity reporting addresses is certified and its result is stored in a block.

However, entities issuing addresses need to have its identity certified. Similar to IETF-DOTS, certificates can be used to ensure authenticity of entities. Therefore, a network domain may issue to its customers a an authentication service to its customers through a registered VNF appliance able to report black or whitelisted addresses to the blockchain. For example, an LDevID certificates signed by the device owner may encode an owner assigned unique identifier and a PKI matching a private key held within the VNF appliance. Inter-domain trust can be established through any of the multi-PKI trust models in use today [START_REF] Shimaoka | Memorandum for multi-domain public key infrastructure interoperability[END_REF]. Then, information on the registered appliances will be hashed and referenced in the smart contract.

Summary

An architecture for multi-domain DDoS Mitigation based on Blockchains, SDN and VNFs was presented. Although designed based on SDN, a VNF appliance to read/write in the blockchain could be integrated with different networkingsystems that exports flow records with sFlow or NetFlow. Expected contributions are not limited to the collaborative perspective of the DDoS defense, but also on the detection and mitigation of these attacks in a single domain based on key technologies such as SDN and NFV.

Fig. 1 .

 1 Fig. 1. Proposed Architecture


Lisa Kristiana

Corinna Schmitt

Burkhard Stiller

The Evaluation of the V2VUNet Concept to Improve Inter-vehicle Communications

Due to the high mobility behavior in inter-vehicle communications (IVC), packet forwarding among vehicles becomes an important issue. For IVC in a traditional packet forwarding setting, it was observed that the ratio between packets received and the packets transmitted is often very low, sometimes less than 50%. This ratio is highly influenced by the environment, especially by road topologies and obstructions (e.g., buildings or overpasses). Further influences encompass the number of driving vehicles on streets offering burdens for the IVC as well as serving as relay candidates. In order to improve IVC this paper introduces a Vehicular-to-Vehicular Urban Network (V2VUNet) to overcome inevitable obstructions and frequent network changes by selecting the best relay candidate. The V2VUNet implemented was evaluated in an IVC with the focus on three-dimensional road topologies including overpasses with a different number of driving lanes. The result shows that the developed V2VUNet provides about 30% better packet transmission performance compared to traditional packet transmission in IVC.

Introduction

Inter-vehicle networks as a part of Vehicular Ad-hoc Network (VANET) are expected to support communications with multiple participating vehicles [START_REF] Papadimitratos | Vehicular Communication Systems: Enabling Technologies, Applications, and Future Outlook on Intelligent Transportation[END_REF]. Thus, information exchanges in a vehicular network communication require stable and reliable connections. During packet transmissions and receptions the communication path has to be maintained in any cases. For IVC in a traditional packet forwarding setting, it was observed that the Packet Delivery Ratio (PDR) as the indicator of network performance is often less than 50% due to path failures [START_REF] Kolici | Performance Evaluation of a VANET Simulation System Using NS-3 and SUMO[END_REF]. These path failures are mainly caused by the road topology complexity of the environment, such as overpass constructions and buildings at intersection roads [START_REF] Walfisch | Theoretical Model of UHF Propagation in Urban Environments[END_REF].

For inter-vehicle communications, a position-based forwarding scheme is generally used, since it offers an advantage of not relying on packet broadcasting in its routing mechanisms. Since position information is already made available, the approach proposed in this paper, the Vehicular-to-vehicular Urban Network (V2VUNet), emphasizes in filtering unnecessary participant nodes [START_REF] Kristiana | V2VUNet -A Filtering Out Concept For Packet Forwarding Decision in Three-Dimensional Inter-vehicular Communication Scenarios[END_REF] and predicting the routing path based on the position information and on the calculated direction information [START_REF] Kristiana | Predictive Forwarding Scheme in Three-dimensional Vehicular Communication Scenarios[END_REF]. Therefore, the packet forwarding scheme is expected to become more efficient. In this research work, the packet forwarding is tested in two types of road environment models. The first type is the cross road model and the second type is the parallel road model. Both types reflect the three-dimensions cases with three coordinate axes x, y, and z. The advance beyond state-of-the-art in this three-dimensional area is determined by the z axis, which in many of VANET scenarios is rarely included. In addition, the three-dimensional case in VANET is significantly influenced by objects placed between signal transmitting devices. These objects can be a building or an overpass. Therefore, it is important to investigate the packet forwarding in these three-dimensional environments. Besides a better performance, the packet forwarding scales best in case of non-safety or non-real-time applications, which can be considered as delay constraint. Thus, delays are evaluated here as a less significant characteristic.

Another relevant aspect today is the use of Multiple Input Multiple Output (MI-MO) technology in Inter-vehicle communication (IVC). MIMO is a method to increase the radio link capacity and becomes a promising solution, since it increases the number of transmitted data by embedding multiple transmitters and receivers [START_REF] Moser | MIMO-Enabling PHY Layer Enhancement for Vehicular Ad-Hoc Networks[END_REF]. This method is useful to be implemented in a non-safety application, such as for infotainment, since it requires high data rates and large amount of data interchanges. However, as this work in this paper here focuses on the network layer, MIMO is better to be evaluated in the data link layer.

In previous works as shown in [START_REF] Kristiana | Predictive Forwarding Scheme in Three-dimensional Vehicular Communication Scenarios[END_REF] and [START_REF] Kristiana | V2VUNet -A Filtering Out Concept For Packet Forwarding Decision in Three-Dimensional Inter-vehicular Communication Scenarios[END_REF], the evaluation of network performance of each approach is compared to a traditional location-based routing. This paper ensues to evaluate both forwarding approaches in V2VUNets by implementing various size of packets, different network densities, and speed of vehicles.The remainder of this paper is organized as follows: Section II describes related work of the packet forwarding model used. Section III introduces the key idea of the vertical angle forwarding scheme being part of a V2VUNet. Additionally, the evaluation of the V2VUNet is discussed in Section IV, followed by the summary and future work in Section V.

Related Work

Successful communication requires an efficient packet forwarding. Packet forwarding is considered as efficient, when the packet is broadcasted with a smaller probability of errors. Packet forwarding for non-safety applications refers to numerous size of data and is assumed to be distributed at a high rate [START_REF] Mauve | VANET Convenience and Efficiency Applications[END_REF], [START_REF] Aoki | Inter-vehicle Communication: Technical Issues on Vehicle Control Application[END_REF], [START_REF] Papadimitratos | Vehicular Communication Systems: Enabling Technologies, Applications, and Future Outlook on Intelligent Transportation[END_REF]. Therefore, dealing with frequent topology changes in IVC's behavior, the packet forwarding is based on the method of forwarding [START_REF] Aoki | Inter-vehicle Communication: Technical Issues on Vehicle Control Application[END_REF], [START_REF] Tavakoli | TIGeR: A Traffic-aware Intersection-based Geographical Routing Protocol for Urban VANETs[END_REF], [START_REF] Lin | A Three-Dimensional Scenario Oriented Routing Protocol in Vehicular Ad-hoc Networks[END_REF], [START_REF] Wang | An Improved VANET Intelligent Forward Decision-making Routing Algorithm[END_REF]. The first idea is to avoid collision in a dense network [START_REF] Mohimani | Mobility Modeling, Spatial Traffic Distribution, and Probability of Connectivity for Sparse and Dense Vehicular Ad-hoc Networks[END_REF], thus, the packet forwarding is designed to reduce the number of relay candidates by restricting the area of transmission [START_REF] Kristiana | V2VUNet -A Filtering Out Concept For Packet Forwarding Decision in Three-Dimensional Inter-vehicular Communication Scenarios[END_REF]. The second idea is to predict the direction of relay candidates by calculating the relative direction of a relay and by selecting the candidate that has the same direction with the destination's direction [START_REF] Kristiana | Predictive Forwarding Scheme in Three-dimensional Vehicular Communication Scenarios[END_REF]. It is obvious that the relay having the same direction with the destination increases the possibility to prolong the duration of a connection between communicating vehicles. Thus, in a large city environment with its road topology and traffic complexity [START_REF] Tavakoli | TIGeR: A Traffic-aware Intersection-based Geographical Routing Protocol for Urban VANETs[END_REF], both approaches will be evaluated to perform a reliable data transmission in VANETs, more specifically in IVC. The two concepts of packet forwarding in IVC are studied in a survey that shows relevant literatures [START_REF] Jerbi | An Improved Vehicular Ad-hoc Routing Protocol for City Environments[END_REF], [START_REF] Tavakoli | TIGeR: A Traffic-aware Intersection-based Geographical Routing Protocol for Urban VANETs[END_REF], [START_REF] Lin | A Three-Dimensional Scenario Oriented Routing Protocol in Vehicular Ad-hoc Networks[END_REF], [START_REF] Wang | An Improved VANET Intelligent Forward Decision-making Routing Algorithm[END_REF], and [START_REF] Kristiana | Survey of Angle-based Forwarding Methods in VANET Communications[END_REF]. While the first concept follows an angle-based forwarding approach, the second concept is defined as direction-based forwarding approach.

Angle-based Forwarding

An angle-based forwarding mechanism utilizes angle measurement to reduce the area of transmission. The idea of implementing angle is to locate relay candidates within the transmission range of a sender S. Thus, under the assumption that the location coordinate of a receiver R is known, the imaginary line is drawn in order to scale the angle as shown in Fig. 2. The angle-based forwarding mechanism selects one of the relay candidates as the intermediate relay based on the location where it has the smallest angle calculation respect to an imaginary line [START_REF] Spachos | Angle-based Dynamic Routing Scheme for Source Location Privacy in Wireless Sensor Network[END_REF], [START_REF] Banka | Angle Routing Protocol: Location Aided Routing for Mobile Ad-Hoc Networks Using Dynamic Angle Selection[END_REF]. As illustrated in Fig. 2, S selects node C as the relay node since C has the smallest angle value. The advantage of this mechanism suits on the dense network because of the efficient route path in terms of time [START_REF] Banka | Angle Routing Protocol: Location Aided Routing for Mobile Ad-Hoc Networks Using Dynamic Angle Selection[END_REF]. The comparison of existing angle forwarding schemes has been done in [START_REF] Kristiana | Survey of Angle-based Forwarding Methods in VANET Communications[END_REF].

Fig. 2. Angle Forwarding Scheme

Direction-based Forwarding

In IVC, vehicles are assumed to move on a predefined path such a straight or intersection road. Thus, vehicles can have heterogeneous directions depend on the road types. In order to cover route loss due to the 'free' movement of vehicles, the directionbased forwarding mechanism involves direction as a weight value to determine the next relay node. The direction has a dynamic value since it depends on the road topology and time-based factor. The direction value is calculated based on the sender and receiver position as illustrated in Fig. 3.

Fig. 3. A Relative Direction of a Vehicle

V2VUNet Concept

The concept used in V2VUNet is an enhancement of the selection method in order to find the best relay node of available candidates [START_REF] Mauve | VANET Convenience and Efficiency Applications[END_REF], [START_REF] Jerbi | An Improved Vehicular Ad-hoc Routing Protocol for City Environments[END_REF]. Previous work of V2VUNet determines the area restriction of transmission [START_REF] Kristiana | V2VUNet -A Filtering Out Concept For Packet Forwarding Decision in Three-Dimensional Inter-vehicular Communication Scenarios[END_REF] and the path prediction [START_REF] Kristiana | Predictive Forwarding Scheme in Three-dimensional Vehicular Communication Scenarios[END_REF]. Both area restriction and path prediction schemes in V2VUNet utilize the angle measurement on the same road level, i.e., Horizontal Relative Angle (HRA) measurement and different road levels i.e., Vertical Relative Angle (VRA) measurement. The implementation of V2VUNet in this work is performed to compare each algorithm in various parameters.

Area Restriction Scheme

In the area restriction scheme, the V2VUNet operates in two steps. The first step is to define the HRA with value of 30º, which is intuitively based on the width of a road in two-dimensional area and the closest distance between two vehicles. The second step is to adjust HRA based on the available relay candidates position. If the number of relay candidates is more than one, then the V2VUNet algorithm selects the relay based on the smallest value of HRA. The algorithm for the area restriction scheme is shown as in Algorithm 1 (cf. Fig. 4). The previously mentioned two steps are also applied in a three-dimensional area. Similar to HRA, VRA will be first defined as 30º, which is indicated as the preliminary angle value based on the transmission range. This 30º value is then increased gradually as part of the searching mechanism.

Fig. 4. Area Restriction Algorithm

Path Prediction Scheme

In this scheme, the HRA is used to predict the direction of relay candidates. The prediction algorithm is designed to overcome the disconnection possibility due to the transmission coverage in two-dimensional area. In case of VRA, the algorthm is designed to encounter the disconnection due to obstruction by the overpass. Furthermore, HRA and VRA in this scheme use the relative direction of each vehicle. This relative direction provides the actual direction in three-dimensional scheme. The path prediction scheme is shown in Algorithm 2 (cf. Fig. 5).

Fig. 5. Path Prediction Algorithm

For the sake of a precise prediction, the direction that is used in V2VUNet algorithm determines a relative direction since the direction of each vehicle is measured in vehicle's current position. This relative direction is changed whenever a vehicle changes its position as illustrated in Fig. 3. Thus, the traditional direction calculation cannot be implemented in this prediction as it is done in [START_REF] Kristiana | Predictive Forwarding Scheme in Three-dimensional Vehicular Communication Scenarios[END_REF]. Those two proposed algorithms are expected to provide a network performance as indicated by high PDR and low end-to-end (E2E) delays. In order to compare all algorithms implemented in this work, Tab. 1. shows a short description of each scheme and all related factors.

Table 1. Comparison of Angle, Area Restricted, and Path Prediction Forwarding Algorithms

As the first factor in this comparison table the coordinate location describes the coordinate axis which is used in measuring the current location of a node. The second factor is the weight value which determines the angle schemes, HRA for two-dimensional area and VRA for three-dimensional area. The third factor is the relative direction which is added in the path prediction algorithm in order to improve the calculation of the location coordinate. This relative direction factor is suitable when nodes move randomly and is useful to indicate the current direction of a node. Greedy routing is used in all algorithms because greedy routing uses the distance factor to do packet forwarding. Basically the greedy approach work best the many routing protocol mechanisms [START_REF] Karp | GPSR: Greedy Perimeter Stateless Routing for Wireless Network[END_REF]. The last factor that influences all forwarding schemes is the road topology, which becomes the main idea of forwarding packet improvement. The angle-based forwarding scheme is used in two-dimensional intersection, where the direction factor becomes an important value, and in the highway, where the speed of a vehicle is highly considered. However, it is necessary to consider about the complexity of a road topology. Thus, the area restriction and path prediction schemes raise the three-dimensional road topology indicated as three-dimensional intersection (i.e., cross road) and parallel roads.

As previously mentioned in the introduction section, this work evaluates and compares the area restriction and path prediction schemes as the improvement of traditional greedy routing.

Performance and Evaluation

The simulation in this work aims to validate the theoretical analysis of the proposed algorithms in IVC. Two simulation scenarios of a road environment with parallel and cross road topology are selected. In parallel road topology, the difference in vehicles' direction is more extreme than in a cross road topology. In a parallel topology, there are less chance that one vehicle can meet another vehicle once they pass each other. In a cross road topology, there is a segment of the road that is under another segment of the road, which could potentially contributes to disconnection at particular moment. In order to obtain a realistic city environment, typical parameters for the influencing factors are chosen as shown in Tab. 2. The Network Simulator-3 (NS-3.25) [14] is used to simulate wireless technologies (i.e., IEEE 802.11p), the routing protocol (i.e., Greedy Perimeter Source Routing (GPSR) [START_REF] Karp | GPSR: Greedy Perimeter Stateless Routing for Wireless Network[END_REF]), the mobility, the road topology, and the network density. The IEEE 802.11p is a well known technology since it is designed to cope the frequent topology changing in IVC. During 200s of simulation time, each vehicle is expected to run under and on the overpass in the first case, and on the different road level in the second case. S, R, and I are placed randomly both on two different road levels and SUMO [START_REF]Simulation of Urban MObility, SUMO[END_REF] is used to generate the realistic mobility of each vehicle. Moreover, the number of S and R are generated equally, which means a 10-vehicle network contains of 5 senders and 5 receivers. The simulation area covers an environment which involves crossing and parallel overpass scenarios (c.f. Fig. 1) in order to show many cases in three-dimensional area.

In previous works, these two algorithms have not been evaluated over various packet sizes, thus, the packet size for the first evaluation is varied from 1 -10 kB, especially for non-safety applications: a half page of unformatted email is 1 kB, one typical HTML webpage is 30 kB, 1 minute of near-CD quality audio as MP3 or a 2048x1536 (4 megapixel) JPEG photo is 1 MB, to evaluate the size of packet that can be successfully transmitted in two algorithms. However, this simulation focuses only on transmitting email, with the size of the packet from 1 to 10 kB.

The first result (cf. Fig. 6) shows the PDR of all algorithms when different packet sizes are applied. This performed evaluation simulates 40 vehicles that move with an average speed of 40 km/h. The V2VUNet area restriction algorithm gives 20% better PDR compared to the greedy forwarding scheme which in the figure is indicated as No V2VUNet. V2VUNet area restriction also shows 10% better compared to V2VUNet-path prediction scheme. The showed PDR in overall algorithms decreases as the packet size increases, which indicates that more participating vehicles and simulation time are required to successfully complete the packet forwarding mechanism. V2VUNet indicates that HRA and VRA weight values have significant impacts in packet transmission. The second result shows the E2E delay of all algorithms (cf. Fig. 7) when different data sizes are applied. The E2E delay increases as the packet size increases. This is because more time are required to transmit packet with bigger size. The E2E delay of 200 ms (highest delay) is indicated by path prediction scheme. This is because the path finding mechanism in the V2VUNet path prediction scheme requires more time compared to the area restriction mechanism. In overall E2E delay results, the traditional forwarding scheme provides lowest delay compared to other two algorithms. This is because the traditional forwarding scheme does not need an additional mechanism to perform packet forwarding.

Speeds

The third set of results shows PDR of all algorithms in various number of participating vehicles in cross road scenario (cf. Fig. 8). These various number of vehicles are used to evaluate V2VUNet schemes when dealing with the network density and network speed. The V2VUNet-path prediction and V2VUNet-area restriction shows 10% and 20% better PDR, respectively, compared to a greedy forwarding without V2VUNet. As the network density grows, the PDR decreases in all forwarding schemes. From all simulation trials that have been performed, the highest PDR that can be achieved is about 40%. This is due to the path failure that occurs when the communicating vehicles are under the overpass. This path failure cannot be avoided since the overpass disturbs the transmission, thus it will never reach 100% of PDR. The network density with 60 -80 vehicles shows the maximum 40% result at speed 50 km/h. This indicates that 60 vehicles with 30 pairs of S and R are the 'best' condition where the packet transmission is performed.

However, in high speed mobility (i.e. 50 km/h -70 km/h), the PDR reaches higher results compared to PDR in low speed mobility (i.e., 30 km/h and 40 km/h). The main reason for this is that in higher speed mobility, the path reconstruction is even more possible than maintaining the old path. In this case, V2VUNet area restriction scheme provides PDR 10% higher compared to V2VUNet path prediction forwarding scheme. This is caused by the overpass construction which blocks the packet transmission, thus, it becomes difficult to complete path finding process.

Speeds

The fourth set of results shows E2E delays of all algorithms when various number of participating vehicles are involved in a cross road scenario (cf. Fig. 9). This E2E delay reaches 350 ms at 70 km/h speed. The high E2E delay can be caused by two reasons: the first reason is that the intermediate node which moves in the opposite direction (e.g., vehicle that changes its direction or turns back), has impact to the searching mechanism. Thus, the mechanism starts to find a new path and the transmission is delayed because of this reason. The second reason is that the connections between two vehicles are interrupted or discontinued, when one of the vehicles is located under the overpass. However, the E2E delays decrease for mobility with higher speeds i.e. 50 km/h -70 km/h. The similar explanation as in the PDR can also be applied to explain the E2E delays. The required period of time to find a new path is less than in the mobility with low speeds (i.e., 30 km/h and 40 km/h). In overall results, the E2E delays are considered as drawbacks in order to obtain better PDR by applying V2VUNet. Thus, this becomes an open question.

Speeds

The fifth set of result in Fig. 10 shows the evaluation of PDR in the parallel road scenario. Here, the path prediction scheme reaches 40%. When compared to other schemes, PDR of the path prediction is found to be the highest because in parallel road scenarios the direction of vehicles is predictable i.e., either in the same direction or opposite direction. Thus, in the parallel scenario, path prediction scheme works well in predicting the relay candidate's direction. In overall, the PDR decreases accordingly to number of participating nodes. This is because of the collision due to the network density.

The sixth set of result shows E2E delays (cf. Fig. 11) in the parallel road scenario. The traditional greedy routing shows the lowest delay compared to other scheme because the scheme does not include additional searching mechanism as previously mentioned. However, the path prediction scheme shows reasonable E2E delays of 50 ms as the prediction mechanism works well in the parallel road scenario.

Speeds

This work covers and ensues the evaluation of V2VUNet through a three-dimensional road topology in a large city. Important parameters of V2VUNet have been evaluated: packet size, speed, and number of vehicles. The V2VUNet takes into account HRA and VRA as additional weight values, which are applied in area restriction and path prediction algorithms. The network performance as indicated by PDR and E2E delay values shows to be reliable in non-safety applications. The PDR in an overall performance shows that V2VUNet provides 20% better result compared to traditional routing algorithms. However, the E2E delays in the overall evaluations are slightly higher than for traditional routing algorithms. Thus, these E2E delays are considered to determine the trade-off in V2VUNet, even though a non-safety application is assumed to be a delay tolerant scheme. Additionally, the path prediction scheme is less suitable to be adopted in the cross scenario, however, it performs better in the parallel scenario. Thus, it can be concluded that the V2VUNet path prediction works better in the parallel scenario, since the direction of vehicles is homogeneous. The V2VUNet area restriction performs better in the cross scenario, since it restricts the number of relay candidates.

Further research in improving V2VUNet, the area restriction, and path prediction concept can be performed for any position-based routing scheme, where the distance and direction indicate the influencing weight value. The combination of these two schemes will be considered as a hybrid scheme, thus, both algorithms in V2VUNet are expected to improve the packet forwarding scheme depending on the use case.

Fig. 1 .

 1 Fig. 1. Inter Vehicle Communication in a Three-dimensional Road Topology

Fig. 6 .

 6 Fig. 6. Evaluation of a Packet Delivery Ratio

Fig. 7 .Fig. 8 .

 78 Fig. 7. Evaluation of End-to-end Delays

Fig. 9 .

 9 Fig. 9. Evaluation of End-to-end Delays for Varying Numbers of Vehicles and Vehicle

Fig. 10 .

 10 Fig. 10. Evaluation of Packet Delivery Ratios for Varying Numbers of Vehicles and Vehicle

Fig. 11 .

 11 Fig. 11. Evaluation of End-to-end Delays for Varying Numbers of Vehicles and Vehicle

Table 2 .

 2 Parameter Settings

	Parameter	Unit
	Transmission Range IEEE 802.11p	up to 300 m
	Routing Protocols	GPSR
	Number of Vehicles	20 -100
	Simulation Area	500 m x 500 m
	Upper Road Height	20 m
	Vehicle Velocity	30 -70 km/h
	Packet Size	1 kB -10 kB
	Simulation Time	200s
	Number of Driving Lanes	4
	DSRC data rates