ACPEC: A Resource Management Scheme Based on Ant Colony Algorithm for Power Edge Computing

Zhu Liu,Nan Zhang,Xuesong Qiu,Xin Liu

doi:10.1155/2021/4868618

Abstract

With the development of power IoTs (Internet of Things) technology, more and more intelligent devices access the network. Cloud computing is used to provide the resource storage and task computing services for power network. However, there are many problems with traditional cloud computing such as the long-time delay and resource bottleneck. Therefore, in this paper, a two-level resource management scheme is put forward based on the idea of edge computing. Furthermore, a new task scheduling algorithm is presented based on the ant colony algorithm, which realized the resource sharing and dynamic scheduling. The data of simulation show that this algorithm has a good effect on the performance of task execution time, power consumption, and so on.

Highlights

Introduction of Ant ColonyAlgorithm. e ant colony algorithm is a novel simulated evolvement algorithm solving complicated combinatorial optimization problem, and its typical feature is swarm intelligence
For the new resource management scheme, the computing tasks can be executed in local nodes, and the time delay can be decreased compared with cloud computing
According to the characteristic of edge computing, we present a task allocation algorithm based on the ant colony algorithm in this paper. e resources of the local edge nodes

Summary

Background

With the rapid development of smart grid, plenty of power equipment accesses into the Internet. e demand for power services shows exponential growth trend. Cloud data center can integrate and manage the data and resources coming from different business systems in power grid uniformly, and these data and resources are the basic of resource sharing for smart grid. The computation latency of these tasks can be shortened and the requirements of users on computation capability and power supply can be reduced [6]. A new two-level resource management scheme is proposed based on edge computing. For the new resource management scheme, the computing tasks can be executed in local nodes, and the time delay can be decreased compared with cloud computing. Security and Communication Networks can be used for providing computation-intensive tasks by resource sharing and cooperation

Related Work

The Power Resource Management Scheme Based on Edge Computing

Introduction

Simulations

Findings

Conclusion