Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing

Xiaolong Xu,Mengmeng Cui,Lianyong Qi,Yuan Xue,Yuan Yuan

doi:10.1155/2019/6180135

Xiaolong Xu, Mengmeng Cui + Show 3 more

Open Access

https://doi.org/10.1155/2019/6180135

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Abstract

By means of the complex systems, multiple renewable energy sources are integrated to provide energy supply for users. Considering that there are massive services needed to process in complex systems, the mobile services are offloaded from mobile devices to edge servers for efficient implementation. In spite of the benefits of complex systems and edge servers, massive resource requirements for implementing the increasing resource requests decrease the execution efficiency and affect the whole resource usage of edge servers. Therefore, it remains an issue to achieve dynamic scheduling of the computing resources across edge servers. With the consideration of this issue, a Balanced Resource Scheduling Method, named BRSM, for trade-offs between virtual machine (VM) migration cost and energy consumption of VM migrations for edge server management, named BRSM, is designed in this paper. Technically, we analyze the load conditions of edge servers and formulate the energy consumption of VM migrations and VM migration cost as a multi-objective optimization problem. Then, we propose a dynamic resource scheduling method for WMAN to deal with the multi-objective optimization problem. In addition, nondominated sorting genetic algorithm III (NSGA-III) is adopted to generate optimal resource scheduling strategies. Finally, we conduct experiment simulations to testify the efficiency of the proposed method BRSM.

Highlights

In recent years, fossil fuels are adopted in most energy systems, which generate a lot of harmful substances and pollute the environment [1, 2]
We aim to achieve the goal of minimizing the migration cost presented in (9) and reducing the energy consumption presented in (18) while meeting the capacity constraints of edge computing device (ECD). e problem is formulated by min, min
We specify the real-time conditions of edge servers and build the resource allocation record collection

Summary

Introduction

Fossil fuels are adopted in most energy systems, which generate a lot of harmful substances and pollute the environment [1, 2]. In order to save fuel and reduce pollution to the environment, renewable energy gradually replaces the fossil energy. Renewable energy is intermittent and di cult to control. Provided that the wind stops, wind power generation is di cult to continue. Erefore, it is of urgency to develop complex systems that integrate multiple renewable energy sources. Considering the intermittent nature of renewable energy, a large number of mobile devices are used in complex systems. E mobile devices are arranged to collect real-time environmental parameters to provide reliable references for strategy formulation Considering the intermittent nature of renewable energy, a large number of mobile devices are used in complex systems. e mobile devices are arranged to collect real-time environmental parameters to provide reliable references for strategy formulation

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Conclusion