Dynamic resource allocation for virtual network function placement in satellite edge clouds

Gao, Xiangqiang, Liu, Rongke, Kaushik, Aryan and Zhang, Hangyu (2022) Dynamic resource allocation for virtual network function placement in satellite edge clouds. IEEE Transactions on Network Science and Engineering. p. 1. ISSN 2327-4697

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Abstract

Satellite edge computing has become a promising way to provide computing services for Internet of Things (IoT) users in remote areas, which are out of the coverage of terrestrial networks. Nevertheless, it is not suitable for large-scale IoT users due to the resource limitation of satellites. Cloud computing can provide sufficient available resources for IoT users, but it does not meet delay-sensitive services as high network latency. Satellite edge clouds can facilitate flexible service provisioning for numerous IoT users by incorporating the advantages of edge computing and cloud computing. In this paper, we investigate the dynamic resource allocation problem for virtual network function (VNF) placement in satellite edge clouds. The aim is to minimize the network bandwidth cost and the service end-to-end delay jointly. We formulate the VNF placement problem as an integer non-linear programming problem and then propose a distributed VNF placement (D-VNFP) algorithm to address it. The experiments are conducted to evaluate the performance of the proposed D-VNFP algorithm, where Viterbi and Game theory are considered as the baseline algorithms. The results show that the proposed D-VNFP algorithm is effective and efficient for solving the VNF placement problem in satellite edge clouds.

Item Type: Article
Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 14 Mar 2022 08:38
Last Modified: 11 Apr 2022 09:15
URI: http://sro.sussex.ac.uk/id/eprint/103224

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