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.

中文翻译：

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一种基于集成元启发式技术的能量感知聚类协议，用于基于物联网的智能教室

随着无线技术的进步，物联网（IoT）因其广泛的应用而在现代变得流行。在本文中，考虑了支持物联网的智能教室。然而，物联网节点受电池限制，因此，基于能效物联网的智能教室的开发和实施成为更具挑战性的问题。最近，许多集群和集群间数据聚合技术被实施以最小化物联网设备的能耗。然而，设计一个能源感知物联网协议被定义为一个 NP-hard 问题。因此，许多研究人员利用各种元启发式技术来实现能量感知协议。然而，通常元启发式技术存在各种问题，例如收敛过早、陷入局部最优、收敛速度差、因此，在本文中，考虑蚁群优化和交叉算子，为基于物联网的智能教室设计了一种集成的多目标优化。所提出的技术用于改进基于物联网的智能教室的集群间数据聚合。通过考虑各种性能指标进行了广泛的实验。比较分析表明，与竞争技术相比，所提出的协议取得了显着的成果。通过考虑各种性能指标进行了广泛的实验。比较分析表明，与竞争技术相比，所提出的协议取得了显着的成果。通过考虑各种性能指标进行了广泛的实验。比较分析表明，与竞争技术相比，所提出的协议取得了显着的成果。