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A decentralized approach for information dissemination in Vehicular Ad hoc Networks

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A decentralized approach for information dissemination in Vehicular Ad hoc Networks
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  A decentralized approach for information disseminationin Vehicular Ad hoc Networks Seytkamal Medetov a , Mohamed Bakhouya b , Jaafar Gaber a , Khalid Zinedine c ,Maxime Wack a , Pascal Lorenz d, n a University of Technology Belfort-Montbeliard, 90010 Belfort Cedex, France b International University of Rabat Parc Technopolis, 11 100 Sala el Jadida, Morocco c Chouaib Doukkali University, El Jadida, Morocco d University of Haute Alsace, 68008 Colmar, France a r t i c l e i n f o  Article history: Received 3 November 2013Received in revised form28 June 2014Accepted 30 July 2014Available online 10 August 2014 Keywords: VANETsMANETSInformation disseminationBroadcasting protocolsAnt colonySwarm computing a b s t r a c t Substantial research efforts on Ad hoc networks have been devoted recently to Vehicular Ad hocNETworks (VANETs) to target Vehicle to Vehicle (V2V) and Vehicle to Roadside unit (V2R) communica-tions in order to increase driver/vehicle safety, transport ef  fi ciency and driver comfort. VANETs arespecial subclass of Mobile Ad hoc NETworks (MANETs) for inter-vehicle communication and haverelatively more dynamic nature compared to MANETs due to the rapid network topology changes. Thedevelopment and implementation of ef  fi cient and scalable algorithms for information dissemination inVANETs is a major issue which has taken enormous attention in the last years. In this paper, an ef  fi cientdistributed information dissemination approach is proposed, inspired by Ant-colony communicationprinciples, such as scalability and adaptability that are useful for developing a decentralized architecturein highly dynamic networks. The main objective is to provide each vehicle with relevant informationabout its surrounding to allow drivers to be aware of undesirable events and road conditions.A  “ relevance ”  value into emergency messages is de fi ned as an analog to pheromone throwing in Antcolony, to take an appropriate action. Simulations are conducted using NS2 network simulator andrelevant metrics are evaluated under different node speeds and densities to show the effectiveness of theproposed approach. &  2014 Elsevier Ltd. All rights reserved. 1. Introduction VANETs appeared as a subclass of MANETs for inter-vehiclecommunication. However, VANETs have relatively more dynamicnature as compared to MANETs with respect to network topology.The design and implementation of an ef  fi cient and scalablearchitecture for information dissemination in VANETs constitutesa major issue that should be tackled. Indeed, in this dynamicenvironment, increasing number of redundant broadcast messageswill increase resource utilization, which would indirectly affect thenetwork performance (Bakhouya et al., 2011). By relying on the participation of vehicles' community and wireless communication,information coming from one vehicle may not be credible andreliable to take right action or trigger an alert. Therefore, vehicleswithin a particular geographical area should be involved incommunicating their context to con fi rm or reject an emergencysituation. Involving multiple vehicles in exchanging context infor-mationwill increase the con fi dence about a global current context.In addition, vehicles equipped with advanced sensors (e.g., ABS,ESP) and capable to become aware of speci fi c abnormal conditionscan share this information with other vehicles lacking this tech-nology (Hartenstein and Laberteaux, 2010). For example, once theAutomatic Braking System (ABS) within a vehicle is activated toindicate an icy road, strong rainfall or snow, the driver will benoti fi ed (Dar et al., 2010a). This information could be disseminated to other surrounding vehicles in order to be informed andeventually take preventive actions before getting into samedangerous situation. Another important scenario concerns exchan-ging information between vehicles to prevent traf  fi c jams fromgrowing too fast. For example, a vehicle having embedded traf  fi cdetection sensors can send traf  fi c information to its followingvehicles that can take preventive actions to avoid the congestedareas (Dar et al., 2010a; Fuchs et al., 2007). This paper proposes a decentralized Context Aware InformationDissemination (CAID) approach using two strategies (G1 and G2)that takes inspiration from the Ants' pheromones spreadingContents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/jnca  Journal of Network and Computer Applications http://dx.doi.org/10.1016/j.jnca.2014.07.0371084-8045/ &  2014 Elsevier Ltd. All rights reserved. n Corresponding author. E-mail addresses:  seytkamal.medetov@utbm.fr (S. Medetov),mohamed.bakhouya@uir.ac.ma (M. Bakhouya), jaafar.gaber@utbm.fr (J. Gaber), zinedine@ucd.ac.ma (K. Zinedine), maxime.wack@utbm.fr (M. Wack), pascal.lorenz@uha.fr (P. Lorenz). Journal of Network and Computer Applications 46 (2014) 154 – 165  principles for information dissemination in VANETs. The mainfocus is on critical emergency information dissemination in safetyrelated applications. Ants' communication principles are used todevelop new approaches of problem solving in different areas of research and development (Mullen et al., 2009; Rizzoli et al.,2007). In Ant colony, when Ants observe a food source they createpheromone to inform other Ants about route information to thatfood source (Chu et al., 2004); Detrain and Deneubourg, 2006). In some Ant species, the amount of pheromone deposited is propor-tional to the quality of the food source found, i.e., paths that leadto better food sources receive higher amount of pheromone(Dsrco et al., 2000). In the proposed Ant inspired information dissemination method, when an abnormal environmental event isnoticed on the road surface, a safety message is created to informother vehicles and roadside units (RSUs) along its way. Similar tothe pheromone values, we de fi ned the relevance value of safetymessages, which depend upon the severity and event types.Furthermore, as pheromones are evaporated with the passage of time, the lesser used Ant paths are gradually vanished (Dsrco etal., 2000, 2006). Similarly, the relevance value decreases over time,with distance, till the corresponding safety message is vanishedand dropped from the system.The remainder of this paper is organized as follows. Section 2presents the related work. The proposed dissemination strategy isdescribed in Section 3 with an overview of Ant system. Simulationresults are presented in Section 4. Conclusions and future work aregiven in Section 5. 2. Related work  VANET is a type of wireless network where nodes that com-municate with each other are vehicles and RSUs. Unlike MANETswhere nodes can freely move in a certain area, the movements of vehicles in VANETs could be predicted, because it is dependent onstreets, traf  fi c and speci fi c rules. Communication between nodesin VANETs is less reliable due to the high mobility and differenttraf  fi c patterns compared to MANETs. In addition, in VANETs, thesafety information should be disseminated to other surroundingvehicles in order to be informed and eventually take preventiveactions. For example, a vehicle having an embedded traf  fi c detec-tion sensor can disseminate current traf  fi c state to its followingvehicles that can take preventive actions to avoid the congestedareas (Hartenstein and Laberteaux, 2010).Various information dissemination approaches were proposedin theliterature (Nadeem et al.,2004;Brickleyetal., 2007).Flooding is the simplest technique for information dissemination in Ad hocbased networks, in which nodes disseminate a received message toall their neighbors. This algorithm can lead to the broadcast stormproblem that severely affects the resources consumption due toredundantmessage rebroadcasts (Nietal.,1999). Several techniques have been proposed to solve this problem by preventing certainnodes from rebroadcasting received messages or by differentiat-ing the timing of rebroadcasts, e.g., using strategies based on abroadcasting probability, or according to the number of samereceived messages, the distance between receivers and senders, orthe location (i.e., position) in an appropriate cluster of nodes(Bakhouya, 2013; Ye et al., 2012). However, it should be noted that these methods used various static threshold parameters which arenot appropriate for dynamic networks, such as VANETs, whereinadaptability is an important issue to consider (Bakhouya and Gaber2014). In Bakhouya et al. (2011), an adaptive approach for informa- tion dissemination is proposed where each node can dynamicallyadjust the values of its local parameters using information fromneighboring nodes. It is worth noting that broadcasting anddissemination are two different issues: broadcasting protocols canbe tackled at the routing layer, while dissemination algorithms dealwith the application layer.Applications in VANETs can be classi fi ed into two main cate-gories, i.e., comfort and safety applications (Dar et al., 2010b;Nadeem et al., 2006). In general comfort related applications areaimed to improve passenger comfort and traf  fi c ef  fi ciency, e.g.,traf  fi c-information, weather information, gas station or restaurantlocation, advertisements and other Internet services (Caliskan andGraupner, 2006). In safety-related applications, high reliability andshort delays are required for information dissemination. In otherwords, safety messages are time-critical; vehicles are required todisseminate warnings immediately to avoid probable accidentsand traf  fi c congestions (Zhuang et al., 2011). However, safety and comfort applications are not completely separated from eachother. For example, a message generated for accident can be seenas a safety urgent message from the perspective of nearbyvehicles. The same message can be seen by farther vehicles as aninformative message to choose an alternative optimal route withlow traf  fi c jams (Hartenstein and Laberteaux, 2010).The role of RSU is important in urban areas where density of vehicles is commonly very high, since vehicles cannot alwaysverify all received messages from neighbors in a timely manner,which can cause message loss. Several works are devoted to RSUslocation, coverage area extension, and its effective use in informa-tion dissemination process. For example, two different optimiza-tion methods for placement of a limited number of RSUs in urbanareas are proposed in Mullen et al. (2009), namely Binary integer programming and Balloon expansion heuristic methods. Thesemethods were used to tackle the optimization problem of mini-mizing an average reporting time. Indeed, a RSU typically canreach with a single hop only a fraction of the interested vehicles.Three algorithms to extend RSU's coverage area using multi-hopinter-vehicle communications are proposed by Bakhouya andGaber (2014). These algorithms apply a set of geometrical rulesbased on the position of sending nodes. In Nadeem et al. (2004), inter vehicle communication is integrated with vehicle to infra-structure communication as an extension of the IEEE 802.11p MACstandard to increase driver's awareness in safety-critical cases. InDar et al. (2010b), a hybrid network architecture is proposed, thatconsists of multiple Ad hoc clusters, connected through proxyservers and cellular links to target the delivery of emergencymessages to all intended vehicles in a short time interval. A RSU-aided message authentication scheme (RAISE), where RSUs areresponsible for verifying the authenticity of the messages sentfrom vehicles and notifying the results back to all the associatedvehicles, is proposed by Nadeem et al. (2006).Since vehicles can receive safety messages, that can be more orless critical, from the infrastructure and other vehicles, selectinguseful and reliable information is one of the most important issuesin the context of VANET safety applications (Huang et al., 2010). In the absence of a central authority monitoring in VANETs, applica-tion of an accurate trust and reputation mechanism might beextremely helpful in that context. For example, a TRIP model, todecide whether to accept, disseminate or discard traf  fi c warningscoming from other vehicles is proposed by Marmol and Perez(2012), by assessing the trustworthiness/reliability of the issuer of such message. The priorities are assigned to messages based ontheir urgency level (Suthaputchakun and Ganz, 2007). Higher priority messages are transmitted more times than lower prioritymessages to provide higher reliability for higher priority messages.Disseminatingemergencymessagesto differentdistances accordingto their importance is proposed by Zhuang et al. (2011). In Moreno et al. (2009), a distributed power control method is proposed tocontrol the load of periodic messages on a channel. It is based on astrict fairness criterion, i.e., a distributed fair power adjustmentthat copes with vehicular environments. A WAVE-enhanced safety S. Medetov et al. / Journal of Network and Computer Applications 46 (2014) 154 – 165  155  message delivery scheme to minimize the delivery delay of safetymessages in multi-channel VANETs is proposed by Felice et al.(2012).In this work, a self-organized approach to disseminate infor-mation about safety critical incidents on roads is presented, whichis inspired by Ants' direct and indirect communications toexchange information about food source locations. Ants are simpleinsects that can collectively perform complex tasks with remark-able consistency. Examples of such complex problem solvingbehavior include building nests, co-operating in carrying preys,and  fi nding the shortest routes from the nest to food locations(Dorigo et al., 2000). Ants adapt their foraging behavior when environmental conditions are suddenly changed, e.g., when a pathtowards a food source is obstructed or when new and shorterroutes are discovered (Vittori et al., 2004). Number of applicationspublished so far implemented ants' communication principles indifferent areas of research, e.g., route optimization, wireless net-work routing, scheduling problems, vehicles routing (Bakhouyaand Gaber, 2007; Grasse, 1960; Trivedi, 2008). For example, a self-organizing approach for routing in MANETs, called distributed antrouting, is proposed by Rosati et al. (2008); routing is stochastic, i.e., a next hop is selected according to weighted probabilities thatare calculated on the basis of the pheromone trails left by ants.Routes not recently used are purged by means of pheromoneevaporation.The ant colony optimization (ACO) algorithm is one of the moststudied and successful optimization techniques (Mullen et al.,2009). Several applications of ACO have been used to solveoptimization problems in different area of research. For example,a delay-sensitive vehicular routing protocol derived from the ACOis proposed by Li and Boukhatem (2013). A route setup process isachieved by reactive forward ants and backward ants, which are incharge of network exploration and pheromone disseminationrespectively. The pheromone dissemination is declared withrespect to the relaying delay of the visited road segments. Basedon the pheromone routing tables at each intersection, routingdecision is made by opportunistically selecting next optimalintersection. Similar work presented by Jabbarpour et al. (2014)used ACO to alleviate the vehicle congestion problem usingintelligent traf  fi c lights. The algorithm is based on streets traf  fi cload condition; road network is divided into different cells andeach vehicle guided through the less traf  fi c path to its destinationusing ACO in each cell. A hybrid Ant colony system is proposed totarget dynamic vehicle routing problem (VRP) using heuristics toreconstruct routes and update pheromone by Rashidi and Farahani(2012). In this time window-based approach, requests arrivingduring a slice time are listed and posted to the next closest timeslice. During each time slice, a problem similar to a static VRP istraced, but with vehicles having different capacities and startinglocations.Aforementioned and many other Ant-based algorithms wereproposed due totheir superior ability in solving dynamic problems(Peinado and Ortiz-Garcia Munilla, 2013). In this paper, informa-tion dissemination approaches taking inspiration from swarmcommunication principles are proposed. 3. The dissemination strategy  In this section, mapping rules of Ant-colony communicationsystem to Vehicular Ad hoc Networks are presented. Two analo-gous information dissemination strategies are presented.  3.1. Ant communication principles in VANETs In the proposed dissemination strategy, each vehicle is con-sidered as an Ant. When an abnormal environmental event isnoticed on the road, a safety message is created and disseminatedto inform other vehicles and roadside units along its way. This issimilar to Ant behavior i.e., when an Ant observes a food source itleaves pheromone traces to convey indirectly to other Ants aboutroute information of that food source. Research published byWilson (1962) demonstrated that Ant pheromone trails providepositive and negative feedbacks to organize foraging at the colonylevel. A colony forms a trail when successful foragers depositpheromone on their return to the nest, with the trail gaining instrength as more and more workers add pheromone to it, soproviding positive feedback (Bakhouya and Gaber, 2014). More- over, according to Dsrco et al. (2000), in some Ant species the amount of pheromone deposited is proportional to the quality of the food source found, i.e., path that leads to a better food sourcesreceive a higher amount of pheromone.Similarly, in the proposed Ant inspired information dissemina-tion method, we de fi ne the  relevance of safety messages  dependingupon the severity and type of events that took place on the road.Furthermore, as pheromones evaporate with the passage of time,the lesser used Ant paths are gradually vanished (Dsrco et al.,2000, 2006). In fact, when the food runs out, foragers refrain fromreinforcing it on their return, so providing negative feedback(Bakhouya and Gaber, 2014; Jackson and Ratnieks, 2006). Taking the concept of pheromones decay from the Ant system, therelevance of safety messages, similar to pheromone values, eva-porates over time and with distance, and  fi nally be vanished fromthe system. Ants also adapt when they face obstacles in theircurrent preferred route by selecting next available paths. Similarly,drivers take preventive appropriate actions (e.g., choose alterna-tive route, slow down speed, or immediate stop) according to therelevance value of received emergency messages from the ContextAware Information Dissemination (CAID) module (see Fig. 1).Table 1 presents the mapping between Ants' foraging behaviorand the proposed decentralized system for information dissemi-nation in VANETs.  3.2. Context aware information dissemination module Figure 1 depicts the different components of the CAID moduleas follows:   GPS receiver  : available in modern cars and will be used to getposition information (GPS, 2007). Knowledge baseData Processing Communication interfaceGPS Receiver Generation of CAID messagesSensorsCAID moduleR eceivedmessageSend messagesReceived messages Fig. 1.  The CAID module architecture. S. Medetov et al. / Journal of Network and Computer Applications 46 (2014) 154 – 165 156    Sensors : different sensors will be used to monitor roadsideconditions, vehicles' states, and drivers' behaviors. Thesesensors will be part of each vehicle and RSU taking part indissemination process, e.g., ABS, ESP (Karpinski et al., 2006;Segata and Cigno, 2013).   Knowledge base : will be used to store messages received fromother vehicles/RSUs. This knowledge base will also be used tostore and transmit new safety messages.   Data processing unit  : will be used to analyze the data storedwithin the knowledge base unit and will pick up useful datachunks for next transmission.   Generation of messages : this module will generate completemessages along with timestamp, spatial data and the relevancevalue.   Communication interface : will be used to transmit and receivesafety messages. We recommend DSRC/WAVE technology forthis purpose, which is specially designed for automotive useand supports mobility (Dar et al., 2010b). Hence, CAID module will be integrated as a part of each vehicleand RSU that are involved in information dissemination process.  3.3. Information dissemination protocol in VANETs As stated above, we use Ants communication principles forinformation dissemination by focusing mainly on safety-criticalreason. In practice, providing such a service i.e., safety-criticalservices only take a short period of time and consume a smallfraction of bandwidth (Liu and Lee, 2010). The objective of theproposed approach is to provide each vehicle with the relevantinformation about its surrounding to allow drivers to be aware of undesirable events and road conditions. The dissemination proto-col is composed of four phases:  data generation, data dissemination,data reception, and data evaporation . For  data generation , when avehicle (or RSU)  v i  observes an event  p  j  that needs to be reportedto other vehicles, it generates a safety message  m  p  j . This messageincludes the timestamp  ð t  0 Þ ; location information, and the initialrelevance value ð R  0 ð Þ v i ;  p  j ð t  0 ÞÞ generated at time  t  0 . Alarm triggered bythe event  p  j  will be generated and  disseminated  periodically up to atime  T  , which represents the maximum time required to handle  p  j by road and security authorities (i.e., the lifetime of the emer-gency, de fi ned as the time needed to return to regular traf  fi cconditions after the emergency situation). Subsequently, an initialrelevance value ð R  0 ð Þ v i ;  p  j ð t  ÞÞ associated to a generated message at time t,  by a source node, is expressed by the following equation: R ð 0 Þ v i ;  p  j ð t  Þ¼ R ð 0 Þ v i ;  p  j ð t  0 Þ U T  ð t   t  0 Þ T   ;  t  0 r t  o T  0  t  Z T  (  ð 1 Þ In  data dissemination  process, two modes are distinguished:dissemination through V2R communication and disseminationthrough V2V communication. In the  fi rst mode, when a vehiclepasses through a RSU and one or both have some new messages toexchange, they will update each other's knowledge base by usingthe communication medium. This is just like an Ant throwspheromones alongside its route. A vehicle throws a new messageto RSU such that other vehicles could get this information.Similarly, vehicles can get information from RSU that has beenprovided by other vehicles or RSUs. In the second mode, when twovehicles (moving in opposite or in same direction) are locatedwithin the communication range of air interface and one/bothhave some new message(s) to exchange, they will update eachother's knowledge base by exchanging new messages. This is quitesimilar to direct communication between Ants.For  data reception  and  dissemination  process, we considered thetwo following strategies: strategy G1 and strategy G2. In G1, whena message  m  p  j  is received by the node  v k  (i.e., vehicle or RSU), itsrelevance value is computed according to the following logisticfunction: R v k ;  p  j ð t  þ τ  Þ¼ 2 U R ð 0 Þ v i ;  p  j ð t  Þ 1 þ e ð d þ  λ U τ  U s = D Þ  ð 2 Þ where  R ð 0 Þ v i ;  p  j ð t  Þ is the relevance of the message  m  p  j  disseminated bythe source vehicle  v i ;  d  is the distance between the currentlocation of receiver vehicle  v k  and the location where theevent appeared (source), which can be calculated as  d ¼  ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ð  X  v k   X   p  j Þ 2 þð Y  v k  Y   p  j Þ 2 q   ;  τ   is the assessment delay needed tocompute message relevance before re-disseminating it to othersurrounding vehicles;  s  is the current speed of   v k ;  λ  is a sign,representing vehicles direction: if it is moving toward the accidentlocation its value will be (  1), otherwise its value will be ( þ 1); D  is the radius for the relative geographical area, and the quantityof   λ U τ  U s  represents the in fl uence of distance variation during theassessment delay  τ  .It is worth noting that data, such as the initial relevance value,the generation time, location of the event and the relative geogra-phical area, which are used for computing received messages'relevance, are stored in the header of each message together withthe description of the event. In the strategy G1, information in theheader, which is generated by the source node, will not be changedby receivers. After computing the new relevance value, receivernodes should take appropriate actions depending on the relevancevalue. For instance, according to the relevance the CAID modulecould suggest drivers either to choose alternative road, or todecrease the speed, or to stop vehicle immediately if the value of message relevanceispositive orhigherthancertain thresholdvalue.If there are many vehicles within a relative geographical area,several redundant messages could be issued. Therefore, in order todecrease redundancy, for messages generated by the same source,which has entry for the same event, their generated time (time-stamp of new and previous received messages) will be compared;the latest generated message will be processed, i.e., its relevancewill be computed by Eq. (2); the early generated messages will bedropped. This process is necessary since the emergency messages  Table 1 Mapping rules.  Ants communication behavior Proposed dissemination approach Ants use pheromones to communicate indirectly Vehicles use messages to update road side units (V2R communication)Food sources Event location (e.g., accident)Pheromones thrown by Ants evaporate with the passage of time and the distance to the food locationThe relevance of stored messages is automatically decreased based on the time and distance to theevent location. The message will be deleted when its relevance value reaches 0Ants communicate directly to exchange useful information Vehicles communicate directly (V2V communication) using DSRC/WAVE technology to exchange safetyinformation about their routesAwareness to decide next actions: ants use alternate routewhen the current route is blockedDrivers, by receiving information from context-aware information dissemination module, takepreventive actions S. Medetov et al. / Journal of Network and Computer Applications 46 (2014) 154 – 165  157  are generated periodically; if the generation interval is very small,some nodes could receive redundant messages generated earliertraveling in communication area among neighbor nodes whilenewer messages have already been received. However, shortinterval in periodic message generation is also important in theconcept of safety applications due to some speci fi c characteristicsof VANETs, i.e., high mobility, very short communication duration,and highly dynamic topology.For messages generated by different sources for same ordifferent events, their relevance values will be computed and thehighest one will be disseminated  fi rst (immediately), messageswith lower relevance value will wait in the queue or will bedropped if their relevance value is lower than a given threshold.Unlike G1, in G2, when a node  v k  receives a message  m  p  j fromanother node  v  x , it computes its relevance value using node- v  x 'sinformation. More precisely, the difference between strategiesG1 and G2 is that the receiver node uses intermediate nodes'(sender/forwarder) relevance value (i.e.,  R v  x ;  p  j ð t  Þ ) instead of thesource generated relevance value (i.e.,  R  0 ð Þ v i ;  p  j ð t  Þ ) in the computationof the new relevance value. Thus, Eq. (2) is re-formulated forstrategy G2 as follows: R v k ;  p  j ð t  þ τ  Þ¼ 2 U R ð 0 Þ v i ;  p  j ð t  Þ 1 þ e ð d þ  λ U τ  U s = D Þ  ⟹ R  0 ð Þ vi ;  p j ð t  Þ - R v x ;  p j ð t  Þ R v k ;  p  j ð t  þ τ  Þ¼ 2 U R v  x ;  p  j ð t  Þ 1 þ e ð d þ  λ U τ  U s = D Þ ð 3 Þ Similar to G1, in order to reduce redundancy, early generatedmessages will be ignored if the received node has already thesame entry in its knowledge base for the same event, which isgenerated by the same source. In addition, less relevant messageswith same generation time are ignored, while more recentmessages should be processed because, nodes in strategy G2 canreceive messages with different relevance values that are com-puted by intermediate nodes.The importance of safety related information received by avehicle depends mainly on the distance between the currentlocation of the vehicle and the place where safety data wasgenerated. The distance decreases when vehicles move in thedirection of the accident/event, and increases when the vehiclegoes away from the event/dissemination area. As depicted in Fig. 2,the average relevance value decreases when the distance from theevent location increases. The darker area denotes, the area beingaware of the event, and white areas indicate that no knowledge isavailable. Receiving such message when approaching this placecan help drivers to decide next actions, such as decreasing/increasing speed,  fi nding an alternative route avoiding traf  fi c jam, etc.This is quite similar to the pheromones, as pheromones lifetime also decreases as the distance between nest and food sourcesincreases. Taking the concept of pheromones decay from the Antssystem, as described above, we de fi ned the relevance of safetymessages similar to pheromone values, which evaporate and fi nally be vanished from the system. The relevance value of eachmessage decreases as the distance increases from the currentposition of the vehicle to the event location. The message will bedeleted from knowledge base when its relevance is below than 0(or a given minimal value). The algorithm of the proposedinformation dissemination approach is given in Fig. 3. 4. Performance evaluation In this section, parameters related to mobility and traf  fi cscenarios are  fi rst described. Performance metrics together withsimulation results are then reported and analyzed. The perfor-mance evaluation of the proposed scheme is studied using thenetwork simulator ns2 (Network Simulator NS 2.34, 2011). Theobjective is to evaluate the in fl uence of relevance values oninformation dissemination process within related geographicalareas. Because, drivers far away from the event location (outsideof the related geographical area) may not be interested since noactions are needed from them to avoid such a dangerous situation.Similar to Ant's communication principles (i.e., the amount of deposited pheromone is proportional to the quality of the foodsource found (Dsrco et al., 2000)) the source node initializes therelevance value of emergency messages according to the eventseverity (signi fi cance). In fact, the relevance value increases forapproaching vehicles, and decreases for going away vehicles. 4.1. Simulation parameters In this study, a realistic mobility scenario is used to conductsimulations. This scenario is generated by Traf  fi c and NetworkSimulation Environment (TRaNS) (Piorkowski et al., 2008), whichare built on top of SUMO, an open source micro-traf  fi c simulator(Simulation of Urban Mobility). The scenario generated, usingthese tools, is a grid topology of 800  800 m 2 with a block sizeof 200 m  200 m as depicted in Fig. 4.The maximum speed of vehicles is  fi xed to 1, 5, 15, 25 m/s andthe number of vehicles is  fi xed to 25, 50, 75, 100 for eachsimulation, respectively. These scenarios are randomly generatedand each of them contains six roads, nine intersections, and 12crossover points at the border. Vehicles move along the grid of horizontal and vertical streets on the map. Each line representinga single-lane road and vehicular movement occurs on the direc-tions shown by arrows. At a crossover, vehicles choose to turn leftor right with equal probability, 0.5. At the intersections of thehorizontal and vertical streets, each vehicle chooses to keepmoving in the same direction with probability 1/2 and to turn leftor right with probability 1/4.The simulation time is  fi xed to 100 s, which is long enough toevaluate the dissemination strategies with different nodes' speedand densities. Each node uses IEEE 802.11 MAC protocol, operatingat 2 Mbps, to send/broadcast and receive messages. We used two-ray ground model for radio propagation and 200 m for thetransmission range. The simulation parameters are described inTable 2. Fig. 2.  The information dissemination process. S. Medetov et al. / Journal of Network and Computer Applications 46 (2014) 154 – 165 158
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