Purpose

Energy is the major concern in wireless sensor networks (WSNs) for most of the applications. There exist many factors for higher energy consumption in WSNs. The purpose of this work is to increase the coverage area maintaining the minimum possible nodes or sensors.

Design/methodology/approach

This paper has proposed multilayer (ML) nodes deployment with distributed MAC (DS-MAC) in which nodes listen time is controlled based on communication of neighbors. Game theory optimization helps in addressing path loss constraints while selecting path toward base stations (BS).

Findings

The simulation is carried out using NS-2.35, and it shows better performance in ML DS-MAC compared to random topology in DS-MAC with same number of BS. The proposed method improves performance of network in terms of energy consumption, network lifetime and better throughput.

Research limitations/implications

Energy consumption is the major problem in WSNs and for which there exist many reasons, and many approaches are being proposed by researchers based on application in which WSN is used. Node mobility, topology, multitier and ML deployment and path loss constraints are some of the concerns in WSNs.

Practical implications

Game theory is used in different situations like countries whose army race, business firms that are competing, animals generally fighting for prey, political parties competing for vote, penalty kicks for the players in football and so on.

Social implications

WSNs find applications in surveillance, monitoring, inspections for wild life, sea life, underground pipes and so on.

Originality/value

Game theory optimization helps in addressing path loss constraints while selecting path toward BS.

中文翻译：

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具有博弈论优化的多层 DS-MAC

目的

对于大多数应用，能源是无线传感器网络 (WSN) 中的主要关注点。导致 WSN 能耗较高的因素有很多。这项工作的目的是增加覆盖区域，保持尽可能少的节点或传感器。

设计/方法/途径

本文提出了具有分布式 MAC (DS-MAC) 的多层 (ML) 节点部署，其中节点侦听时间根据邻居的通信进行控制。博弈论优化有助于在选择通向基站 (BS) 的路径时解决路径损耗约束。

发现

仿真是使用 NS-2.35 进行的，与具有相同数量 BS 的 DS-MAC 中的随机拓扑相比，它在 ML DS-MAC 中显示出更好的性能。所提出的方法在能耗、网络寿命和更好的吞吐量方面提高了网络性能。

研究局限性/影响

能源消耗是 WSN 中的主要问题，其原因有很多，研究人员根据使用 WSN 的应用提出了许多方法。节点移动性、拓扑结构、多层和 ML 部署以及路径损耗约束是 WSN 中的一些问题。

实际影响

博弈论被用于不同的情况，例如国家的军队竞赛、企业的竞争、动物通常为猎物而战、政党争夺选票、足球运动员的点球等等。

社会影响

WSN 在野生生物、海洋生物、地下管道等的监视、监控和检查中得到应用。

原创性/价值

博弈论优化有助于在选择通向 BS 的路径时解决路径损耗约束。