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Computing Power Allocation and Traffic Scheduling for Edge Service Provisioning

Xiang, Z. (author)
Zhejiang University, CHN
Deng, S. (author)
Zhejiang University, CHN
Jiang, F. (author)
Zhejiang University, CHN
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Gao, H. (author)
Shanghai University, CHN
Taheri, Javid (author)
Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
Yin, J. (author)
Zhejiang University, CHN
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 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2020
2020
English.
In: Proceedings - 2020 IEEE 13th International Conference on Web Services, ICWS 2020. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728187860 ; , s. 394-403
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • The increasing number of mobile web services makes it convenient for users to complete complex tasks on their mobile devices. However, the latency brought by unstable wireless networks and the computation failures caused by constrained resources limit the development of mobile computing. A popular approach to solve this problem is to establish a mobile service provisioning system based on the mobile edge computing (MEC) paradigm, in which the latency can be reduced and the computation can be offloaded with the help of services deployed on nearby edge servers. However, as the edge servers are resource-limited, we should be more careful in allocating the edge resource to services, as well as designing the traffic scheduling strategy. In this paper, we investigate the edge-cloud cooperation mechanism in service provisioning as well as the billing model of it. To minimize the average service response time and make the expense acceptable, we model and formulate the performance-cost service provisioning problem as a joint optimization problem whose decision variables are the resource allocation strategy and traffic scheduling strategy. Then we propose an efficient online algorithm, called PCA- CATS, to decompose this problem into two individual subproblems. We conduct a series of experiments to evaluate the performance of our approach. The results show that PCA- CATS can easily balance the performance and expense with a factor V, and can reduce up to 53.3 % service response time as compared with the baselines.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

Mobile Edge Computing
Resource Allocation
Service Computing
Traffic Scheduling
Mobile telecommunication systems
Scheduling
Websites
Constrained resources
Cooperation mechanism
Decision variables
On-line algorithms
Resource allocation strategies
Service provisioning
Service response time
Web services

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ref (subject category)
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By the author/editor
Xiang, Z.
Deng, S.
Jiang, F.
Gao, H.
Taheri, Javid
Yin, J.
About the subject
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Electrical Engin ...
NATURAL SCIENCES
NATURAL SCIENCES
and Computer and Inf ...
and Computer Science ...
Articles in the publication
Proceedings - 20 ...
By the university
Karlstad University

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