Dynamic Resource Allocation for Virtual Network Function Placement in Satellite Edge Clouds

• Published in: IEEE transactions on network science and engineering Vol. 9; no. 4; pp. 2252 - 2265
• Main Authors: Gao, Xiangqiang, Liu, Rongke, Kaushik, Aryan, Zhang, Hangyu
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bandwidth; Cloud computing; Data centers; Delays; distributed algorithm; Edge computing; Game theory; Internet of Things; Linear programming; network bandwidth cost; Network latency; Nonlinear programming; Placement; Provisioning; Resource allocation; Resource management; Satellite edge clouds; Satellites; service end-to-end delay; virtual network function (VNF) placement; Virtual networks
• ISSN: 2327-4697; 2334-329X
• DOI: 10.1109/TNSE.2022.3159796

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.