Paper Info
Title
Joint Computation Offloading and Resource Allocation for MEC-Enabled IoT Systems With Imperfect CSI
Abstract
Mobile-edge computing (MEC) is considered as a promising technology to reduce the energy consumption (EC) and task accomplishment latency of smart mobile user equipments (UEs) by offloading computation-intensive tasks to the nearby MEC servers. However, the Quality of Experience (QoE) for computation highly depends on the wireless channel conditions when computation tasks are offloaded to MEC servers. In this article, by considering the imperfect channel-state information (CSI), we study the joint offloading decision, transmit power, and computation resources to minimize the weighted sum of EC of all UEs while guaranteeing the probabilistic constraint in multiuser MEC-enabled Internet-of-Things (IoT) networks. This formulated optimization problem is a stochastic mixed-integer nonconvex problem and challenging to solve. To deal with it, we develop a low-complexity two-stage algorithm. In the first stage, we solve the relaxed version of the original problem to obtain offloading priorities of all UEs. In the second stage, we solve an iterative optimization problem to obtain a suboptimal offloading decision. As both stages include solving a series of nonconvex stochastic problems, we present a constrained stochastic successive convex approximation-based algorithm to obtain a near-optimal solution with low complexity. The numerical results demonstrate that the proposed algorithm provides comparable performance to existing approaches.
Year
DOI
Venue
2021
10.1109/JIOT.2020.3022802
IEEE Internet of Things Journal
Keywords
DocType
Volume
Computation offloading,optimization,resource allocation,stochastic programming
Journal
8
Issue
ISSN
Citations 
5
2327-4662
3
PageRank 
References 
Authors
0.37
0
5
Name
Order
Citations
PageRank
Jun Wang162570.64
Daquan Feng299444.97
Shengli Zhang347737.16
An Liu450046.79
Xiang-gen Xia55167410.80