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Minimizing Convergecast Time and Energy Consumption in Green Internet of Things

机译:最大限度地降低绿色互联网中的收敛时间和能量消耗

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Real-time surveillance systems with green wireless sensor networks (WSNs) are vital for maintaining high energy efficiency in many situations. This paper considers a scenario utilizing green WSNs to monitor the situation of Internet of Things (IoT), which constitute one of the most crucial sources of electricity consumption in information and communications technologies (ICT). More specifically, we focus on optimizing the cluster structure to minimize the delay and energy consumption for aggregation convergecast in green WSNs. We first find the optimal value of the network cluster radius for minimizing the delay through theoretical analysis. We then propose a novel cluster network architecture in which clusters that are far from the sink are small, allowing inter-cluster data aggregation to be processed earlier, and clusters that are near the sink are relatively large to allow more time for intra-cluster data aggregation. Hence, the sensor nodes can be scheduled in consecutive time slots to reduce the number of state transitions, consequently achieving the goal of minimizing both delay and energy consumption. Simulation results indicate that the proposed Algorithm outperforms previously reported solutions in terms of both schedule length and lifetime, thereby demonstrating its effectiveness.
机译:具有绿色无线传感器网络(WSN)的实时监控系统对于在许多情况下保持高能量效率至关重要。本文考虑了利用绿色WSN来监测物联网(物联网)的情况的情况,该情况构成信息和通信技术(ICT)中最重要的电力消耗来源之一。更具体地,我们专注于优化群集结构,以最小化绿色WSN中聚合汇聚集聚的延迟和能耗。我们首先找到网络集群半径的最佳值,以最小化通过理论分析的延迟。然后,我们提出了一种新的群集网络架构,其中远离水槽的簇很小,允许更早地处理群集间数据聚合,并且靠近水槽的集群相对较大,以允许群集内部的更多时间聚合。因此,传感器节点可以在连续的时隙中调度,以减少状态转换的数量,从而实现最小化延迟和能量消耗的目标。仿真结果表明,所提出的算法在先前报告的解决方案方面以方案长度和寿命而言,从而证明其有效性。

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