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A request dispatching method for efficient use of renewable energy in fog computing environments

机译:一种有效利用雾计算环境中可再生能源的请求调度方法

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In the emerging era of Internet of Things (IoT), fog computing plays a critical role in serving delay-sensitive and location-aware applications. As a result, fog nodes are envisioned to be heavily deployed and form future distributed data centers. Powering fog nodes with green energy sources (such as solar and wind), not only helps in environmental and CO_2 emission control but also paves the way towards a "sustainable IoT technology". However, the downside of green energy is its variation and unpredictability, which needs to be engineered. In this paper, we use the Lyapunov optimization technique to derive algorithms for dynamic dispatching of the users' requests among the nearby fog nodes and remote data centers. The proposed algorithms take into account the time constraints of the requests and maintain the system stability while efficiently utilize the available green energy sources. Exhaustive simulation results, based on solar radiation data supplied by the Australian Bureau of Meteorology, confirm the efficiency of the proposed algorithms. In particular, in terms of service time, the number of deadline misses and green energy utilization, the proposed algorithms outperform the state-of-the-art alternative up to 6%, 17% and 12%, respectively.
机译:在新兴时期的物联网(物联网)中,雾计算在服务延迟敏感和位置感知应用程序中起着关键作用。因此,雾节点被设想为大量部署并形成未来的分布式数据中心。用绿色能源(如太阳能和风)为雾节点供电,不仅有助于环境和CO_2排放控制,而且还铺平了朝向“可持续物联网技术”的方式。然而,绿色能源的缺点是其变化和不可预测性,需要设计。在本文中,我们使用Lyapunov优化技术来导出用于动态调度附近的雾节点和远程数据中心的用户请求的算法。所提出的算法考虑了请求的时间限制,并在有效地利用可用的绿色能源时保持系统稳定性。令人遗憾的仿真结果,基于澳大利亚气象局提供的太阳辐射数据,确认了所提出的算法的效率。特别是在服务时间方面,截止日期未命中和绿色能量利用的数量,所提出的算法优于最先进的替代方案,分别高达6%,17%和12%。

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