Wireless Communications and Mobile Computing
Volume 2018, Article ID 6897523, 9 pages
https://doi.org/10.1155/2018/6897523
Data Processing Delay Optimization in Mobile Edge Computing
School of Information Science and Engineering, Qufu Normal University, Rizhao 276800, China
Correspondence should be addressed to Guangshun Li; moc.qq@58525703
Received 13 October 2017; Accepted 9 January 2018; Published 6 February 2018
Academic Editor: Shangguang Wang
Copyright © 2018 Guangshun Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
With the development of Internet of Things (IoT), the number of mobile terminal devices is increasing rapidly. Because of high transmission delay and limited bandwidth, in this paper, we propose a novel three-layer network architecture model which combines cloud computing and edge computing (abbreviated as CENAM). In edge computing layer, we propose a computational scheme of mutual cooperation between the edge devices and use the Kruskal algorithm to compute the minimum spanning tree of weighted undirected graph consisting of edge nodes, so as to reduce the communication delay between them. Then we divide and assign the tasks based on the constrained optimization problem and solve the computation delay of edge nodes by using the Lagrange multiplier method. In cloud computing layer, we focus on the balanced transmission method to solve the data transmission delay from edge devices to cloud servers and obtain an optimal allocation matrix, which reduces the data communication delay. Finally, according to the characteristics of cloud servers, we solve the computation delay of cloud computing layer. Simulation shows that the CENAM has better performance in data processing delay than traditional cloud computing.