Being as an integral part of data exchange in disaster management, Internet of Thing (IoT) is an essential component to update the disaster management information to all the connected nodes. In such scenarios, the nodes are deployed with a limited battery, batteries of these nodes are non-rechargeable and such networks consume huge energy in data exchange. Therefore, the practical implementation of such type of networks is a difficult task as routing avoids the paths and consume a tremendous amount of energy during collection/transmission of data. This paper proposes an optimized Genetic Algorithm (GA) based green data collection/transmission method for IoT based WSN in disaster management by satisfying multiple constraints i.e., optimizing intra-cluster distance, systematic utilization of node’s energy in the cluster and reducing hop count. The proposed direct data collection/transmission and movable sink strategies shorten the communication distance between the sink and cluster head (CH) which diminishes the hotspot problem. The direct data collection helps in transmitting data directly to the sink when the sinks are nearer to the sensor nodes with respect to CH. Further, the incorporated dynamic sensing range minimizes overlapping of sensing range of CH along with a significant decrement in the transmission energy. The simulation results show that the proposed protocol outperforms the existing protocols on the performance metrics namely network’s remaining energy, lifetime, stability period, and throughput per rounds.

中文翻译：

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灾害管理中基于物联网的无线传感器网络的绿色数据采集和传输方法


作为灾害管理数据交换的一个组成部分，物联网（IoT）是将灾害管理信息更新到所有连接节点的重要组成部分。在这种场景中，节点部署的电池有限，这些节点的电池是不可充电的，这样的网络在数据交换中消耗巨大的能量。因此，这种类型的网络的实际实现是一项艰巨的任务，因为路由避开了路径并且在数据收集/传输期间消耗了大量的能量。本文提出了一种基于遗传算法（GA）的优化绿色数据收集/传输方法，用于灾害管理中基于物联网的无线传感器网络，该方法满足多个约束，即优化簇内距离、系统地利用簇内节点能量和减少跳数。所提出的直接数据收集/传输和可移动接收器策略缩短了接收器和簇头（CH）之间的通信距离，从而减少了热点问题。当接收器相对于 CH 更靠近传感器节点时，直接数据收集有助于将数据直接传输到接收器。此外，所结合的动态感测范围最大限度地减少了 CH 感测范围的重叠以及传输能量的显着减少。仿真结果表明，所提出的协议在网络剩余能量、寿命、稳定期和每轮吞吐量等性能指标上优于现有协议。