Mobile Adhoc Networks Performance Analysis Using Terrain Aware Propagation Loss Conditions (P-0248) (MFN 4727)

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dc.contributor.author Purva Bashir, 01-133102-074
dc.contributor.author Zarmeena Tariq, 01-133102-103
dc.date.accessioned 2017-07-12T09:48:13Z
dc.date.available 2017-07-12T09:48:13Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/123456789/2426
dc.description Supervised by Mr. Najam Ul Islam en_US
dc.description.abstract A .Mobile. Ad. Hoc. Network. (MANET) consists. of. a. group. of. autonomous nodes communicating in an infrastructure-less environment. MANETs can configure themselves on the go. Due to the aforementioned properties, MANETs are favored in rescue and relief services and have varied military applications. MANETs can be deployed anywhere, regardless of the topographical conditions. However, topography plays a huge role in the network performance of mobile nodes. Network. Simulator. 2 (NS-2). is. the. most popular. simulation. tool. used by researchers for Ad hoc networks performance analysis. Radio.Propagation. models. used. in simulations.greatly influence the performance of.MANETs for both Line.of.Sight (LoS) .and .Non .Line .of .Sight (NLoS).conditions. The existing propagation models in NS-2 are fairly simplistic and don’t account for the effect of multiple intersections and/or obstacles. The Two Ray Ground and the Free Space Path loss models yield unrealistic results for an Ad hoc network scenario (i.e. no infrastructure). We have integrated Cost 231 muti-wall model in NS-2 to provide a more sophisticated approach for indoor path loss evaluations. All obstructions (i.e. walls) between the transmitter and the receiver are considered. The individual material properties for all obstructions are also taken into account. We have also analyzed the effect of group based and entity based mobility models such as Manhattan Grid model, Random Waypoint, Gauss Markov and Reference Point Group Mobility model. Different network performance.metrics. such. as. Packet. Delivery. Ratio(PDR). and. mean Delay were evaluated with varying node densities. The network performance degrades severely with the use of Cost 231 Multi-wall propagation model and entity based mobility models. en_US
dc.language.iso en en_US
dc.publisher Electrical Engineering, Bahria University Engineering School Islamabad en_US
dc.relation.ispartofseries BEE;P-0248
dc.subject Electrical Engineering en_US
dc.title Mobile Adhoc Networks Performance Analysis Using Terrain Aware Propagation Loss Conditions (P-0248) (MFN 4727) en_US
dc.type Project Report en_US


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