Abstract
As an emerging network architecture and technology, mobile edge computing (MEC) can alleviate the tension between the computation-intensive applications and the resource-constrained mobile devices. However, most available studies on computation offloading in MEC assume that the edge severs host various applications and can cope with all kinds of computation tasks, ignoring limited computing resources and storage capacities of the MEC architecture. To make full use of the available resources deployed on the edge servers, in this paper, we study the cross-server computation offloading problem to realize the collaboration among multiple edge servers for multi-task mobile edge computing, and propose a greedy approximation algorithm as our solution to minimize the overall consumed energy. Numerical results validate that our proposed method can not only give near-optimal solutions with much higher computational efficiency, but also scale well with the growing number of mobile devices and tasks.
Highlights
The past decade has witnessed wireless communications experiencing an explosive growth in terms of both the number of mobile devices (MDs) and services to be supported [1]
Given the multi-user multi-server multi-task mobile edge computing network architecture, we mainly study the problem of cross-server computation offloading, which considers how to improve the utility of the limited computation resources deployed on edge servers in MEC
We have elaborated the problem of cross-server multi-task computation task offloading for energy consumption minimization in MEC networks
Summary
The past decade has witnessed wireless communications experiencing an explosive growth in terms of both the number of mobile devices (MDs) and services to be supported [1]. Lots of new mobile applications (APPs) like interactive gaming, natural language processing, and face identification have emerged and attracted great attention [2]. These kinds of APPs usually require rich computation resource to process their large amount of data. The conflict between resource-hungry APPs and resource-constrained MDs poses an unexampled challenge to deploy the coming new generation mobile networks and Internet of Things (IoT). MEC integrates cloud computing functionalities into mobile systems efficiently by deploying MEC servers (MECSs) at the edge of pervasive wireless access networks
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