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Low-latency and Res...
Low-latency and Resource-efficient Service Function Chaining Orchestration in Network Function Virtualization
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- Sun, Gang (författare)
- Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China
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- Xu, Zhu (författare)
- Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China
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- Yu, Hongfang (författare)
- Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China
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- Chen, Xi (författare)
- School of Computer Science and Technology, Southwest Minzu University, Chengdu, China
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- Chang, Victor (författare)
- School of Computing & Digital Technologies, Teesside University, Middlesbrough, UK
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- Vasilakos, Athanasios (författare)
- Luleå tekniska universitet,Datavetenskap
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(creator_code:org_t)
- IEEE, 2020
- 2020
- Engelska.
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 7:7, s. 5760-5772
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Recently, network function virtualization (NFV) has been proposed to solve the dilemma faced by traditional networks and to improve network performance through hardware and software decoupling. The deployment of the service function chain (SFC) is a key technology that affects the performance of virtual network function (VNF). The key issue in the deployment of SFCs is proposing effective algorithms to achieve efficient use of resources. In this paper, we propose a service function chain deployment optimization (SFCDO) algorithm based on a breadth-first search (BFS). The algorithm first uses a BFS based algorithm to find the shortest path between the source node and the destination node. Then, based on the shortest path, the path with the fewest hops is preferentially chosen to implement the SFC deployment. Finally, we compare the performances with the greedy and simulated annealing (G-SA) algorithm. The experiment results show that the proposed algorithm is optimized in terms of end-to-end delay and bandwidth resource consumption. In addition, we also consider the load rate of the nodes to achieve network load balancing.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Medieteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Media and Communication Technology (hsv//eng)
Nyckelord
- Network function virtualization
- Service function chain
- End-to-end delay
- Resource consumption
- Pervasive Mobile Computing
- Distribuerade datorsystem
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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