Paper Info
Title
Energy-Time Efficient Task Offloading for Mobile Edge Computing in Hot-Spot Scenarios
Abstract
Mobile edge computing (MEC) provides a new ecosystem that enables cloud computing capabilities at the edge of mobile networks, which is characterized by ultra-low latency and high bandwidth as well as real-time access to radio network information leveraged by applications. Nevertheless, various challenges, especially the decision-making issues for task offloading, are yet to be properly addressed. In this paper, leveraging the insight from the relative evaluation method, we propose a metric to quantify the benefit on users' service experience enhancement by task offloading. Meanwhile, by comprehensively considering the energy cost, time cost and users' service experience enhancement throughout the task offloading process, we formulate the task offloading decision-making problem as a two-dimensional knapsack loading problem to maximize the cost efficiency of task offloading. To solve the optimization problem more efficiently, we propose a suboptimal heuristic algorithm with polynomial-time complexity. Compared with four baseline algorithms, simulation results demonstrate the cost efficiency improvement of our proposed scheme.
Year
DOI
Venue
2021
10.1109/ICC42927.2021.9500358
IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021)
DocType
ISSN
Citations 
Conference
1550-3607
0
PageRank 
References 
Authors
0.34
13
7
Name
Order
Citations
PageRank
Fanfan Wu100.34
Xiuhua Li213814.68
hui li332.76
Qilin Fan423.75
Linquan Zhu500.34
Xiaofei Wang668658.88
Victor C. M. Leung79717759.02