ZTE Communications ›› 2017, Vol. 15 ›› Issue (4): 3-11.doi: 10.3969/j.issn.1673-5188.2017.04.001

• Special Topic • Previous Articles     Next Articles

A Transparent and User-Centric Approach to Unify Resource Management and Code Scheduling of Local, Edge, and Cloud

ZHOU Yuezhi1, ZHANG Di1, ZHANG Yaoxue2   

  1. 1. Tsinghua University, Beijing 100084, China
    2. Central South University, Changsha 410083, China
  • Received:2017-05-10 Online:2017-10-25 Published:2019-12-02
  • About author:ZHOU Yuezhi (zhouyz@mail.tsinghua.edu.cn) is an associate professor in the Department of Computer Science and Technology, Tsinghua University, China. His research interests include distributed system, mobile network, and transparent computing system.|ZHANG Di (dizhang@tsinghua.edu.cn) is a postdoctoral researcher in the Department of Computer Science and Technology, Tsinghua University, China. His research interests include distributed system, mobile network, and transparent computing system.|ZHANG Yaoxue (zyx@csu.edu.cn) is a professor in the School of Information Science and Engineering, Central South University, China. His research interests include transparent computing, pervasive computing, and big data.
  • Supported by:
    This work was supported in part by Initiative Scientific Research Program in Tsinghua University under Grant(No. 20161080066);in part by International Science & Technology Cooperation Program of China under Grant(No. 2013DFB10070)

Abstract:

Recently, several novel computing paradigms are proposed, e.g., fog computing and edge computing. In such more decentralized computing paradigms, the location and resource for code execution and data storage of end applications could also be optionally distributed among different places or machines. In this paper, we position that this situation requires a new transparent and user-centric approach to unify the resource management and code scheduling from the perspective of end users. We elaborate our vision and propose a software-defined code scheduling framework. The proposed framework allows the code execution or data storage of end applications to be adaptively done at appropriate machines under the help of a performance and capacity monitoring facility, intelligently improving application performance for end users. A pilot system and preliminary results show the advantage of the framework and thus the advocated vision for end users.

Key words: cloud computing, fog computing, edge computing, mobile edge computing, resource management and code scheduling