Paper Info
Title
Online task scheduling for edge computing based on repeated stackelberg game.
Abstract
A key function of an edge service provider (ESP) is to dynamically allocate resources to tasks existing at the edges upon request. This is, however, a challenging task due to a number of several factors: real-time decision-making without any prior knowledge of future arrivals, tasks’ satisfactions provided by requests, and utilization of resources. To address these challenges, we propose an online scheduling that maps various tasks to the given relevant resources based on a repeated Stackelberg game. First, we model this problem as a long-term vs. short-term repeated Stackelberg game. In particular, for each round of the game, acting as a short-term leader, a user with a request first decides the unit prices for processing tasks within the relevant budget to maximize current total satisfaction of tasks. Then, based on the prices offered by different users in different rounds, to maximize the long-term profits earned from users, the ESP acts as the follower whose strategy is matching resources with tasks, and splitting those tasks among different edge centers owning various types of resources (edge mobile devices). The Stackelberg equilibrium between the ESP and the users is obtained using our proposed algorithms. Finally, we evaluate the effectiveness of our proposal, in terms of task distributions.
Year
DOI
Venue
2018
10.1016/j.jpdc.2018.07.019
Journal of Parallel and Distributed Computing
Keywords
Field
DocType
Allocation scheduling,Repeated Stackelberg game,Equilibrium,Edge computing resourcing
Edge computing,Scheduling (computing),Computer science,Computer network,Service provider,Mobile device,Stackelberg competition,Distributed computing,Profit (economics)
Journal
Volume
ISSN
Citations 
122
0743-7315
5
PageRank 
References 
Authors
0.39
19
6
Name
Order
Citations
PageRank
Yingmo Jie1163.26
Xinyu Tang216413.01
Kim-Kwang Raymond Choo34103362.49
Shenghao Su4111.82
Mingchu Li546978.10
Cheng Guo6479.84