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Impact Factor:4.341
DOI number:10.1109/TCCN.2020.3018159
Affiliation of Author(s):School of ComputerScience and Information Engineering, Hefei University of Technology
Journal:IEEE Transactions on Cognitive Communications and Networking
Funded by:National Natural Science Foundation of China under Grants 61971176, and 61901156, Anhui Provincial N
Key Words:Mobile edge computing, collaborative offloading, delivery rate
Abstract:Mobile edge computing (MEC) is an emerging computing paradigm for enabling low-latency, high bandwidth and agile mobile services by deploying computing platform at the edge of network. In order to improve the cloud-edge-end processing efficiency of the tasks within the limited computation and communication capabilities, in this article, we investigate the collaborative computation offloading, computation and communication resource allocation scheme, and develop a collaborative computing framework that the tasks of mobile devices (MDs) can be partially processed at the terminals, edge nodes (EN) and cloud center (CC). Then, we propose the pipeline-based offloading scheme, where both MDs and ENs can offload computation intensive tasks to a particular EN and CC, according to their computation and communication capacities, respectively. Based on the proposed pipeline offloading strategy, a sum latency of all MDs minimization problem is formulated with the consideration of the offloading strategy, computation resource, delivery rate and power allocation, which is a non-convex problem and difficult to deal with. To solve the optimization problem, by using the classic successive convex approximation (SCA) approach, we transform the non-convex optimization problem into the convex one. Finally, simulation results indicate that the proposed collaboration offloading scheme with the pipeline strategy is efficient and outperforms other offloading schemes.
Co-author:Hao Zhou,Yibo Yi
First Author:Caihong Kai
Indexed by:Journal paper
Correspondence Author:Wei Huang
Discipline:Engineering
Document Type:J
Volume:7
Issue:2
Page Number:624 - 634
ISSN No.:2332-7731
Translation or Not:no
Date of Publication:2020-08-20
Included Journals:SCI、EI