Journal of Emerging Technologies in Web Intelligence Contents

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86 JOURNAL OF EMERGING TECHNOLOGIES IN WEB INTELLIGENCE, VOL. 2, NO. 2, MAY 2010Bee-Inspired Routing Protocols for MobileAd HOC Network (MANET)Deepika ChaudharyChitkara Institute of Engg & Technology JhanslaTeh. Rajpura,Distt Patiala-140401,Punjabdeepika.chaudhary@chitkara.edu.inAbstract – Mobile AdHoc networks( MANETs) are receivinga significant amount of attention from researchers. Thispaper provides a high light on a new and very energyefficient algorithm for routing in Manets BeeAdHoc. Thisalgorithm is a reactive source routing algorithm andconsumes less energy as compared to other existing state ofart routing algorithms because a fewer control packets forrouting are sent as compared to other networks.I. INTRODUCTIONMobile Ad HOC networks (MANET’S) are networks inwhich all nodes are mobile and communicate with each other viawireless connections. Nodes can join or leave the network at anytime. There is no fixed infrastructure. All nodes are equal andthere is no centralized control or overview. There no designatedrouters all nodes can serve as routers for each other and datapackets are forwarded from node to node in multihop fashion.Since a few years researcher’s interest in MANETS havebeen growing and especially the design of MANET routingprotocols has received a lot of attention. One of the reasons isthat routing in MANETS is particularly challenging task due tothe fact that the topology of the network changes constantly andpaths, which were initially efficient, can quickly becomeinefficient or even infeasible. Moreover control information flowin the network is very restricted. This is because the bandwidthof the wireless medium is very limited and the medium isshared: nodes can only send or receive data if no other node issending in their radio neighborhood. It is therefore important todesign algorithm that are adaptive robust & self-healing. Natureself-organizing systems like insect societies show precisely thesedesirable properties. Making use of a number of relativelysimple biological agents like ants, a variety of differentorganized behavior are generated at the system level from thelocal interaction among the agents and with the environment.The robustness and effectiveness of such collective behaviorswith respect to variations of environment conditions are keyaspects of their biological success. This kind of systems areoften referred to with the term swarm intelligence. Swarmsystems have recently become a source of inspiration for designof distributed & adaptive algorithms.II. DESIGN ISSUES OF ROUTING ALGORITHMSThe most important challenge in designing algorithms forMANETs are mobility and limited battery capacity of nodes.Mobility of nodes results in continuously evolving newtopologies and consequently the routing algorithms have todiscover or update the routes in real time but with small controloverhead . The limited battery capacity requires that the packetsif possible be distributed on multiple paths , which would resultin the depletion of batteries of different nodes at an equal rateand hence as a result the life time of networks would increase[1].Therefore an important challenge in Manets is to design arouting algorithm that is not only energy effieicent but alsodelivers performance same or better than existing state of artrouting protocols.III. CLASSIFICATION OF ROUTING ALGORITHMS INMANETSThe routing algorithms for Manets can be broadly classifiedas proactive algorithms or reactive algorithms. Proactivealgorithms periodically launch control packets which collect thenew network state and update the routing tables accordingly. Onthe other hand, reactive algorithms find routes on demand only.Reactive algorithms looks more promising from the prespectiveof energy consumption in Manets. Each category of abovementioned algorithms can further be classified into hostintelligent or router intelligent algorithms . A few reactivealgorithms are DSR ( Dynamic Source Routing ) which is hostintelligent algorithm while AODV( AdHoc On DemandDistance Vector Routing) which is a router –intelligentalgorithm.However these algorithms are not designed for energyefficient routing. Here in this study an deep insight is providedon BeeAdHoc which delivers performance same as better thanthat of DSR,AODV but consumes less energy as compared tothem. The algorithm achieves these objectives by transmittingfewer control packets and by distributing data packets onmultiple paths.IV. EXISTING WORK ON NATURE –INSPIRED MANETROUTING PROTOCOLSThe first algorithm which presents a detailed scheme forMANET routing based on ant colony principles is ARA [3]. Thealgorithm has its roots in ABC AND AntNet Routing algorithmsfor fixed networks and are inpired by the pheromone layingbehavior of ant colonies . AntHocNet, which is hybrid algorithmhaving both reactive and proactive components have also beenproposed.This algorithm tries to keep most of features of theoriginal AntNet and shows promising results in simulationcomared to AODV Termite is another MANET routingalgorithm inspired by termite behaviour .Here no special agentsare needed for updating the routing tables rather data packets aredelegated this task.V. OVERVIEW OF BEEADHOC ARCHITECTUREBeeAdHoc is an on-demand multi path routing algorithm formobile adhoc networks inspired from the foraging principles ofhoney bees[4]. BeeAdHoc works with types of agents: packers,scouts foragers and swarms. The packers locate a forager andhand over the data packet to the discovered forager. Scoutsdiscover new routes from the launching node to the destination© 2010 ACADEMY PUBLISHERdoi:10.4304/jetwi.2.2.86-88
JOURNAL OF EMERGING TECHNOLOGIES IN WEB INTELLIGENCE, VOL. 2, NO. 2, MAY 2010 87node through broadcasting principle and an expanding time tolive (TTL) timer. Foragers, the main workers.The architecture of the hive is shown in Fig 1 where theentrance floor is an interface to the lower MAC layer, while thepacking floor is an interface to the upper transport layer. Thedance floor contains the foragers and the routing information toroute locally generated packets. The functional characteristics ofeach floor composing the hive are explained in the following.floor from the MAC layer. If the packet is the forager and th ecurrent node is its destination, then the forager is forwarded tothe packing floor.; otherwise, it is directly routed to the MACinterface of the next hop node. If the packet is a scout, it isbroadcast to the neighbor nodes if its TTL timer has not expiredyet or if the current node is not its destination. The informationabout the ID of the scout and its source node is stored in a locallist. If a replica of previously received scout arrives at theentrance floor , it is removed from the system. If a forager withthe same destination as the scout already exists on the dancefloor, then the forager’s route to the destination is given to thescout by appending it to the route held so far by the scout.Fig 1. Overview of BeeAdHoc ArchitectureVI. PACKING FLOORThe packing floor is an interface to the upper transport layer(e.g, TCP or UDP) . Once a data packet arrives from transportlayer, a matching forager for it is looked up on the danced floor .If a forager is found then the data packet is encapsulated in itspayload . Otherwise, the data packet is temporary bufferedwaiting for a returning forager. If no forager comes back withina certain predefined time, a scout is launched which isresponsible for discovering new routes to the packet destination .Figure 2 explains the series of action performed at packing floor.Fig 3: The EntranceVIII. DANCE FLOORFig 2 : The Packing FloorVII. ENTRANCEThe function performed in the entrance are shown in figure.3. The entrance is an interface to the lower level MAC layer.The entrance handles all incoming and out going packet. Actionon the dance floor depends on the type of packet entered theThe dance floor is the heart of the hive because it maintainsthe routing information in the form of foragers. The dance flooris populated with routing information by means of mechanismreminiscent of the waggle dance recruitment in natural bee hivesonce a forager returns after its journey, it recruits new forager by“dancing” according to the quality of the path it traversed.A lifetime forager evaluates the quality of its route based onthe average remaining battery capacity of the nodes along itsroute. The central activity of the dance floor module consists ofsending a matching forager to the packing floor in response to arequest from a packer. The foragers whose lifetime has expiredare not considered for matching. If multiple path be identifiedfor matching, then a forager is selected in a random way. Thishelps in distributing the packets over multiple paths, which inturn serves two purpose : avoiding congestion under high loadsand depleting batteries of different nodes at comparable rate. Aclone of the selected forager is sent to the packing floor and thenumber of permitted clones. If the dance number is 0 then theoriginal forager is sent to the packing floor removing it in thisway from the dance floor. This strategy aims at favoring youngover old foragers.If the last forager for a destination leaves ahive then the hive does not have any more route to thedestination. Nevertheless if a route to the desination still existsthen soon a forager will be returning to the hive if no foragercomes back within reasonable amount of time, then the node has© 2010 ACADEMY PUBLISHER
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