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首页> 外文期刊>Ad-hoc & sensor wireless networks >Tree-based Threshold-sensitive Energy-efficient Routing Approach using Moth Flame Optimization for Wireless Sensor Networks
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Tree-based Threshold-sensitive Energy-efficient Routing Approach using Moth Flame Optimization for Wireless Sensor Networks

机译：无线传感器网络中基于树蛾的基于阈值的节能敏感路由算法

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摘要

Wireless sensor network (WSN) is a cost-effective networking solution for information updating in the coverage radius or in the sensing region. To record a real time event, large number of sensor nodes (SNs) need to be arranged systematically, such that information collection is possible for longer span of time. But, the hurdle faced by WSN is the limited resources of SNs. Hence, there is high demand to design and implement an energy efficient scheme to prolong the operational lifetime of WSN. Clustering based routing is the most suitable approach to support for load balancing, fault tolerance, and reliable communication to prolong performance parameters of WSN. These performance parameters are achieved at the cost of reduced lifetime of cluster head (CH). To overcome such limitations in clustering based hierarchical approach, efficient CH selection algorithm, and optimized routing algorithm are essential to design efficient solution for larger scale networks. In this paper, a tree based clustering approach named tree-based threshold-sensitive energy-efficient routing protocol is proposed using moth flame optimization (MFO) algorithm to extend the operational lifetime of the network. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in terms of energy consumption, stability period and system lifetime.
机译：无线传感器网络（WSN）是一种经济高效的联网解决方案，用于在覆盖半径或感测区域中进行信息更新。为了记录实时事件，需要系统地布置大量传感器节点（SN），以便可以在更长的时间范围内收集信息。但是，WSN面临的障碍是SN的资源有限。因此，迫切需要设计和实施节能方案以延长WSN的使用寿命。基于群集的路由是最合适的方法来支持负载平衡，容错和可靠的通信，以延长WSN的性能参数。这些性能参数是以降低簇头（CH）的寿命为代价的。为了克服基于聚类的分层方法中的此类限制，有效的CH选择算法和优化的路由算法对于为大型网络设计有效的解决方案至关重要。本文提出了一种基于树的聚类方法，称为基于树的阈值敏感型节能路由协议，该方法使用飞蛾火焰优化（MFO）算法来延长网络的使用寿命。分析和仿真结果表明，该算法在能耗，稳定期和系统寿命方面均明显优于竞争聚类算法。

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