Enhancing cooperation in MANET using neighborhood compressive sensing model

This paper presents the use of Compressive Sensing (CS) in the reduction of resource consumption to minimize battery and bandwidth usage. It also focuses on how attacks and misbehavior can be nullified. The proposed Neighborhood Compressive Sensing (NCS) model compresses the neighborhood sparse data such as routing table updates, advertisement and trust information. It minimizes resource consumption because major computations are performed by the leader node. The use of compressive sensing gives the reduction in resource consumption because it reduces the amount of transmitting data in the network. It also prevents a network from unwanted advertisement and attacks because the neighborhood nodes do not accept the advertisements and updates directly, rather it uses leader node’s processed information. The proposed NCS model is implemented in “GloMoSim” on top of the DSR protocol, resulting its effectiveness, as compared to the DSR protocol when the network is misconducting for its selfish needs. Simulation result shows that the proposed NCS model is outperformed DSR in terms of the energy consumption, network lifetime and packet dropping ratio. This work is the extended version of Reduction in Resource Consumption to enhance cooperation in MANET using Compressive Sensing (Akhtar and Sahoo, 2015) [68].

Abstract licence: CC BY-NC-ND

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