arrow
Return

Optimal Task Offloading Scheduling for Energy Efficient D2D Cooperative Computing

delete2019-10-01
delete34
PRE
AI
Q
Qijie Lin
王丰 cover
王丰 (Feng Wang) *
J
Jie Xu
DOI:10.1109/LCOMM.2019.2931719delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This letter investigates energy-efficient computation offloading designs for device-to-device (D2D) cooperative computing between the two users, in which each user has time-varying computation task arrivals. In this setup, the two users can dynamically exchange the computation loads via D2D offloading for reducing the overall energy consumption. In particular, we minimize the weighted sum-energy consumption of both users over a finite time horizon, by jointly optimizing their local computing and task exchange (offloading) decisions over time, subject to the newly introduced task causality and completion constraints. By applying the convex optimization technique, we obtain the well-structured optimal solution to this problem. Numerical results show that by enabling bidirectional computation sharing between the users, the proposed D2D cooperative computing design significantly reduces the system energy consumption, as compared with other benchmark schemes.
Keywords:
Mobile edge computing (MEC)
cooperative computing
device-to-device offloading
convex optimization
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Communications Letters cover
IEEE Communications Letters
IF:
4.4
Papers:
1.3W
Citations:
2.2W

Organization

G
guangdong university of technology
Scholars:
3.0W
Papers: 2.0W
Citations: 36