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An integrated metaheuristic technique based energy aware clustering protocol for Internet of Things based smart classroom

机译:基于集成的智能课堂互联网能量感知群集协议

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摘要

With an advancement in wireless technologies, Internet of Things (IoT) are becoming popular in modern era because of its wide range of applications. In this paper, an IoT enable smart classroom is considered. However, IoT nodes are battery constrained, therefore, development and implementation of energy efficiency IoT based smart classroom turn out be more challenging issue. Recently, many clustering and inter-cluster data aggregation techniques are implemented to minimize the energy consumption of IoT devices. However, designing an energy aware IoT protocol is defined as a NP-hard problem. Therefore, many researchers have utilized various metaheuristic techniques to implement energy aware protocol. However, generally metaheuristic techniques suffer from various issues such as pre-mature convergence, stuck in local optima, poor convergence speed, etc. Therefore, in this paper, an integrated multi-objective optimization is designed for IoT based smart classroom by considering ant colony optimization and crossover operator. The proposed technique is used to improve the inter-cluster data aggregation of IoT based smart classroom. Extensive experiments are performed by considering various performance metrics. Comparative analyses show that the proposed protocol achieves remarkably significant results as compared to the competitive techniques.
机译:随着无线技术的进步,由于其广泛的应用,事物互联网(IOT)在现代时代变得流行。在本文中,考虑了一个IOT启用智能教室。但是,IOT节点是电池受限的限制,因此,基于信息效率的智能教室的能效的开发和实现变得更具挑战性问题。最近,实现了许多聚类和群集间数据聚合技术,以最小化IOT设备的能量消耗。但是,设计能量感知物联网协议被定义为NP难题。因此,许多研究人员利用了各种成像技术来实现能量感知协议。然而,一般的成群质技术遭受了各种问题,例如预成熟的收敛,在本地最佳的局部,收敛速度差等,因此,通过考虑蚁群来设计集成的多目标优化。优化和交叉运算符。所提出的技术用于改善基于IOT的智能课堂的群集间数据聚合。通过考虑各种绩效指标进行广泛的实验。比较分析表明,与竞争技术相比,该拟议的方案达到了显着的显着效果。

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