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Vehicular delay-tolerant networks for smart grid data management using mobile edge computing

机译：使用移动边缘计算的智能电网数据管理车载容忍网络

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摘要

With the widespread popularity and usage of ICT around the world, there is increasing interest in replacing the traditional electric grid by the smart grid in the near future. Many smart devices exist in the smart grid environment. These devices may share their data with one another using the ICT-based infrastructure. The analysis of the data generated from various smart devices in the smart grid environment is one of the most challenging tasks to be performed as it varies with respect to parameters such as size, volume, velocity, and variety. The output of the data analysis needs to be transferred to the end users using various networks and smart appliances. But sometimes networks may become overloaded during such data transmissions to various smart devices. Consequently, significant delays may be incurred, which affect the overall performance of any implemented solution in this environment. We investigate the use of VDTNs as one of the solutions for data dissemination to various devices in the smart grid environment using mobile edge computing. VDTNs use the store-and-carry forward mechanism for message dissemination to various smart devices so that delays can be reduced during overloading and congestion situations in the core networks. As vehicles have high mobility, we propose mobile edge network support assisted by the cloud environment to manage the handoff and the processing of large data sets generated by various smart devices in the smart grid environment. In the proposed architecture, most of the computation for making decisions about charging and discharging is done by mobile devices such as vehicles located at the edge of the network (also called mobile edge computing). The computing and communication aspects are explored to analyze the impact of mobile edge computing on performance metrics such as message transmission delay, response time, and throughput to the end users using vehicles as the mobile nodes. Our empirical results demonstrate an improved performance 10-15 percent increase in throughput, 20 percent decrease in response time, and 10 percent decrease in the delay incurred with our proposed solution compared to existing state-ofthe- art solutions in the literature.
机译：随着ICT在世界范围内的广泛普及和使用，在不久的将来人们越来越有兴趣用智能电网代替传统电网。智能电网环境中存在许多智能设备。这些设备可以使用基于ICT的基础结构彼此共享数据。从智能电网环境中的各种智能设备生成的数据的分析是要执行的最具挑战性的任务之一，因为它的大小，体积，速度和种类等参数会有所不同。数据分析的输出需要使用各种网络和智能设备传输给最终用户。但是有时在将数据传输到各种智能设备期间，网络可能会变得过载。因此，可能会导致严重的延迟，这会影响此环境中任何已实施解决方案的整体性能。我们调查了使用VDTN作为使用移动边缘计算将数据分发到智能电网环境中各种设备的解决方案之一。 VDTN使用存储转发机制将消息传播到各种智能设备，从而可以减少核心网络中过载和拥塞情况下的延迟。由于车辆具有高移动性，我们建议在云环境的辅助下支持移动边缘网络，以管理智能电网环境中各种智能设备生成的大数据集的切换和处理。在所提出的架构中，用于做出关于充电和​​放电的决定的大多数计算是由诸如位于网络边缘的车辆之类的移动设备完成的（也称为移动边缘计算）。探索了计算和通信方面，以分析移动边缘计算对性能指标的影响，例如使用车辆作为移动节点的最终用户的消息传输延迟，响应时间和吞吐量。我们的经验结果表明，与现有的现有技术解决方案相比，我们提出的解决方案可将吞吐量提高10-15％，响应时间减少20％，并将延迟减少10％。

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