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].

本文介绍了使用压缩感知 (CS) 来减少资源消耗以最大限度地减少电池和带宽使用。它还侧重于如何消除攻击和不当行为。提议的邻域压缩感知 (NCS) 模型压缩邻域稀疏数据，例如路由表更新、广告和信任信息。它最大限度地减少了资源消耗，因为主要计算由领导节点执行。压缩感知的使用减少了资源消耗，因为它减少了网络中传输的数据量。它还可以防止网络受到不需要的广告和攻击，因为邻居节点不直接接受广告和更新，而是使用领导节点的处理信息。所提出的 NCS 模型是在 DSR 协议之上的“GloMoSim”中实现的，当网络为满足其自私的需求而不当行为时，与 DSR 协议相比，它具有有效性。仿真结果表明，所提出的 NCS 模型在能耗、网络寿命和丢包率方面优于 DSR。这项工作是 Reduction in Resource Consumption 的扩展版本，以使用 Compressive Sensing 加强 MANET 中的合作（Akhtar 和 Sahoo，2015）[68]。