Performance Evaluation And Nodes Mobility Effect Analysis On Aodv Based Internet Gateway Discovery Algorithms In Social Networks

Mobile ad hoc networks (manets), with gateway (gw) discovery protocols forrnInternet connectivity, allows portable devices to establish communication withrnHosts in the fixed network (or to the internet).rnThe ad hoc on demand distance vector (aodv) manet routing protocol,rnEnhanced to support proactive, reactive and hybrid gateway discoveryrnAlgorithms(gwdas), has been proposed and applied in various literature works.rnFor mns to get connection to the internet, the gw node has to be discovered byrnUsing a gwda and configured. The frequent topology change due to nodes’rnMovement in manets is a challenge in affecting performance of the gwdasrnCausing frequent link failures. This results in frequent gw discoveries and hencernIncreased total discovery, handover between gw nodes and disconnection time.rnThe link failure also causes packet drops that are being exchanged to thernInternet. In this thesis work, the impact of nodes’ mobility on the performance ofrnReactive, proactive and hybrid gwdas is studied thoroughly based on the densityrnOf nodes, traveler’s speed and strength of social interaction between nodes. Asrn(mns) are nothing but portable devices that are carried by humans, a morernRealistic mobility model (community based mobility model), that can show humanrnSocialization and cooperation behavior is used for the simulation. The results ofrnThis work showed that, the increase in travelers’ speed up to 10m/s showsrnImprovement in the performances of the algorithms as it helps the distribution ofrnMns in the simulation area, but after that, performance of all the threernAlgorithms degrades. The high social interaction helps to attain the bestrnPerformance at lower speed than the low social interaction mobility condition butrnAs travelers’ speed increases it aggravates the performance degradation of thernAlgorithms. The less dense environment is observed to aggravate the effect ofrnMobility on all algorithms. Comparatively the proactive gwda, with greaterrnRouting overhead, out performs the other two. An algorithm which improves thernReactive gwda by performing discovery before a gw route fails, called predictivrnGwda is proposed in this thesis work. It is observed to perform much betterrnThan the reactive gwda and has nearly equivalent performance with thernProactive gwda, but with a 5% to7% lesser overhead.rnKey words: manet, aodv, gw discovery, gwda, proactive, reactive, hybrid,rnCommunity based mobility model

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