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Service Chaining Placement Based on Satellite Mission Planning in Ground Station Networks

Gao, X; Liu, R; Kaushik, A; (2020) Service Chaining Placement Based on Satellite Mission Planning in Ground Station Networks. IEEE Transactions on Network and Service Management , 18 (3) pp. 3049-3063. 10.1109/TNSM.2020.3045432. Green open access

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Abstract

As the increase in satellite number and variety, satellite ground stations should be required to offer user services in a flexible and efficient manner. Network function virtualization (NFV) can provide a new paradigm to allocate network resources on-demand for user services over the underlying network. However, most of the existing work focuses on the virtual network function (VNF) placement and routing traffic problem for enterprise data center networks, the issue needs to further study in satellite communication scenarios. In this paper, we investigate the VNF placement and routing traffic problem in satellite ground station networks. We formulate the problem of resource allocation as an integer linear programming (ILP) model and the objective is to minimize the link resource utilization and the number of servers used. Considering the information about satellite orbit fixation and mission planning, we propose location-aware resource allocation (LARA) algorithms based on Greedy and IBM CPLEX 12.10, respectively. The proposed LARA algorithm can assist in deploying VNFs and routing traffic flows by predicting the running conditions of user services. We evaluate the performance of our proposed LARA algorithm in three networks of Fat-Tree, BCube, and VL2. Simulation results show that our proposed LARA algorithm performs better than that without prediction, and can effectively decrease the average resource utilization of satellite ground station networks.

Type: Article
Title: Service Chaining Placement Based on Satellite Mission Planning in Ground Station Networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TNSM.2020.3045432
Publisher version: https://doi.org/10.1109/TNSM.2020.3045432
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Satellites , Resource management , Planning , Prediction algorithms , Routing , Satellite ground stations , Servers
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10107368
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