WFRF:(Jiang Z)
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Computing Power Allocation and Traffic Scheduling for Edge Service Provisioning
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- Xiang, Z. (författare)
- Zhejiang University, CHN
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- Deng, S. (författare)
- Zhejiang University, CHN
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- Jiang, F. (författare)
- Zhejiang University, CHN
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- (creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2020
- 2020
- Engelska.
- Ingår i: Proceedings - 2020 IEEE 13th International Conference on Web Services, ICWS 2020. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728187860 ; , s. 394-403
- Konferensbidrag (refereegranskat)
Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- 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)
Nyckelord
- 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
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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- Proceedings - 2020 IEEE 13th International Conference on Web Services, ICWS 2020 (Sök värdpublikationen i LIBRIS)
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