首页> 外文期刊>Wireless Networks >Optimized and load balanced clustering for wireless sensor networks to increase the lifetime of WSN using MADM approaches
【24h】

Optimized and load balanced clustering for wireless sensor networks to increase the lifetime of WSN using MADM approaches

机译:针对无线传感器网络的优化和负载均衡群集,使用MADM方法来延长WSN的使用寿命

获取原文
获取原文并翻译 | 示例
           

摘要

The power utilization has verified as a major problem in wireless sensor networks (WSNs). Many researchers have provided efficient solutions for power utilization. Clustering is one of them that helps in topology control and ensures efficient power utilization. However, the clustering method should be effective that could obtain the best clusters. Comprehensive evolution of clustering protocols for the lifetime of sensor nodes is a unique approach to the total enhancement of the lifetime of WSNs. There are many conflicting factors that affect the efficiency of clustering, i.e. distance between CH and the base station, distance form node to cluster head (CH), maximum residual energy of CHs, etc. The coordination among these factors has a capability to insure the optimal power utilization by reducing power consumption and load balancing among the nodes and CHs. In this paper, we have considered total sixteen such factors and made coordination among them to select the best CHs. Multiple attribute decision-making methods are used to choose best set of CHs from the available alternatives that can fulfill the condition of coordination efficiently. The experimental results validate that the coordination among these sixteen factors put up one of the best demonstration for choosing best CHs.
机译:在无线传感器网络(WSN)中,功耗已被证明是一个主要问题。许多研究人员提供了有效的电源利用解决方案。群集是其中之一,有助于进行拓扑控制并确保有效的电源利用。但是,聚类方法应该有效,可以获得最佳聚类。集群协议在传感器节点生命周期中的全面发展是一种独特的方法,可以全面提高WSN的生命周期。影响群集效率的因素很多,例如,CH与基站之间的距离,节点到群集头的距离(CH),CH的最大剩余能量等。这些因素之间的协调能够确保通过减少节点和CH之间的功耗和负载平衡来实现最佳的电源利用率。在本文中,我们考虑了总共十六种这样的因素,并在它们之间进行协调以选择最佳的CH。多属性决策方法用于从可有效满足协调条件的可用替代方案中选择最佳的CH集合。实验结果验证了这16个因素之间的协调性是选择最佳CH的最佳例证之一。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号