Node placement optimization using particle swarm optimization and iterated local search algorithm in wireless sensor networks,International Journal of Communication Systems

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Node placement optimization using particle swarm optimization and iterated local search algorithm in wireless sensor networks
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2021-04-05 , DOI: 10.1002/dac.4813
Slaheddine Chelbi ₁ , Habib Dhahri ₂ , Rafik Bouaziz ₃

Affiliation

Coverage and connectivity are the two most challenging issues in target‐based wireless sensor networks (WSNs). For that, node placement is one of the fundamental concerns that affect the performance of coverage and connectivity in WSN. This paper introduces a new approach by combining particle swarm optimization and iterated local search (PSO‐ILS) to have an optimum coverage and connectivity rate with the minimum number of nodes. In one side, to maintain the full coverage of targets, the PSO‐ILS is used to deploy the minimum number of sensor nodes. In other side, to achieve the full connectivity, the optimal position determination (OPD) algorithm was conceived to identify the optimal candidate positions which can be used by the PSO‐ILS to place the minimum number of relay nodes. The obtained results considered over a number of runs are compared with canonical PSO, differential evolution (DE), and genetic algorithms (GAs). The outcomes derived from this comprehensive analysis determine that PSO‐ILS provides an effectual improvement in contrary to the methods PSO, DE, and GA in terms of the selected potential positions to ensure full coverage of target points and the number of relay nodes required to achieve full connectivity.

中文翻译：

无线传感器网络中使用粒子群算法和迭代局部搜索算法的节点布局优化

覆盖和连接是基于目标的无线传感器网络（WSN）中两个最具挑战性的问题。为此，节点放置是影响WSN覆盖和连接性能的基本问题之一。本文通过结合粒子群优化和迭代局部搜索（PSO-ILS）引入一种新方法，以最少的节点数实现最佳的覆盖范围和连接速率。一方面，为了保持目标的完整覆盖范围，PSO-ILS用于部署最少数量的传感器节点。另一方面，为了实现完全连接，构想了最佳位置确定（OPD）算法来识别最佳候选位置，PSO-ILS可以使用该最佳位置来放置最少数量的中继节点。将在多次运行中考虑的获得的结果与标准PSO，差分进化（DE）和遗传算法（GA）进行比较。这项全面分析得出的结果表明，在选择的潜在位置方面，PSO-ILS与PSO，DE和GA方法相比，提供了有效的改进，以确保完全覆盖目标点和实现此目标所需的中继节点数量完全连接。

更新日期：2021-05-04

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