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Artificial bee colony metaheuristic for energy-efficient clustering and routing in wireless sensor networks

机译:无线传感器网络中节能聚类和路由的人工蜂殖民地殖民地

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摘要

Swarm intelligence (SI)-based metaheuristics are well applied to solve real-time optimization problems of efficient node clustering and energy-aware data routing in wireless sensor networks. This paper presents another superior approach for these optimization problems based on an artificial bee colony metaheuristic. The proposed clustering algorithm presents an efficient cluster formation mechanism with improved cluster head selection criteria based on a multi-objective fitness function, whereas the routing algorithm is devised to consume minimum energy with least hop-count for data transmission. Extensive evaluation and comparison of the proposed approach with existing well-known SI-based algorithms demonstrate its superiority over others in terms of packet delivery ratio, average energy consumed, average throughput and network life.
机译:基于群体的智能(SI)的核心学,适用于解决无线传感器网络中有效节点聚类和能量感知数据路由的实时优化问题。 本文介绍了基于人工蜂殖民地成群质主义的这些优化问题的另一种卓越的方法。 所提出的聚类算法具有基于多目标健身功能的改进的群集头选择标准的有效的群集形成机制,而路由算法被设计为消耗最小能量,以进行数据传输的最小跳数。 具有现有众所周知的基于SI的算法的建议方法的广泛评估和比较在数据包交付比率,平均能量消耗,平均吞吐量和网络生活方面证明了其对他人的优势。

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