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Composition-Driven IoT Service Provisioning in Distributed Edges
Zhejiang University, China..
Zhejiang University, China..
Zhejiang University, China..
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-9194-010X
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2018 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 54258-54269Article in journal (Refereed) Published
Abstract [en]

The increasing number of Internet of Thing (IoT) devices and services makes it convenient for people to sense the real world and makes optimal decisions or complete complex tasks with them. However, the latency brought by unstable wireless networks and computation failures caused by constrained resources limit the development of IoT. A popular approach to solve this problem is to establish an IoT service provision system based on a mobile edge computing (MEC) model. In the MEC model, plenty of edge servers are placed with access points via wireless networks. With the help of cached services on edge servers, the latency can be reduced, and the computation can be offloaded. The cache services must be carefully selected so that many requests can by satisfied without overloading resources in edge servers. This paper proposes an optimized service cache policy by taking advantage of the composability of services to improve the performance of service provision systems. We conduct a series of experiments to evaluate the performance of our approach. The result shows that our approach can improve the average response time of these IoT services.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2018. Vol. 6, p. 54258-54269
Keywords [en]
Mobile edge computing, Internet of Thing, service provisioning, service composition
National Category
Computer and Information Sciences
Research subject
Mathematics; Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-70056DOI: 10.1109/ACCESS.2018.2871475ISI: 000448016000001OAI: oai:DiVA.org:kau-70056DiVA, id: diva2:1261478
Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2019-12-19Bibliographically approved

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Taheri, Javid

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