Vadde Usha, Kompalli Vijaya Sri
Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradash, India.
Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India.
PeerJ Comput Sci. 2022 Jul 19;8:e1035. doi: 10.7717/peerj-cs.1035. eCollection 2022.
The Internet of Things (IoT) concept evolved into a slew of applications. To satisfy the requests of these applications, using cloud computing is troublesome because of the high latency caused by the distance between IoT devices and cloud resources. Fog computing has become promising with its geographically distributed infrastructure for providing resources using fog nodes near IoT devices, thereby reducing the bandwidth and latency. A geographical distribution, heterogeneity and resource constraints of fog nodes introduce the key challenge of placing application modules/services in such a large scale infrastructure. In this work, we propose an improved version of the JAYA approach for optimal placement of modules that minimizes the energy consumption of a fog landscape. We analyzed the performance in terms of energy consumption, network usage, delays and execution time. Using iFogSim, we ran simulations and observed that our approach reduces on average 31% of the energy consumption compared to modern methods.
物联网（IoT）概念已演变成一系列应用。为满足这些应用的需求，使用云计算会很麻烦，因为物联网设备与云资源之间的距离会导致高延迟。雾计算凭借其地理分布式基础设施变得很有前景，该基础设施可使用物联网设备附近的雾节点来提供资源，从而减少带宽和延迟。雾节点的地理分布、异构性和资源约束给在如此大规模基础设施中放置应用模块/服务带来了关键挑战。在这项工作中，我们提出了JAYA方法的改进版本，用于模块的最优放置，以最小化雾环境的能耗。我们从能耗、网络使用、延迟和执行时间方面分析了性能。使用iFogSim，我们进行了模拟，观察到与现代方法相比，我们的方法平均可降低31%的能耗。
