An Energy Efficient Approach for Service Chaining Placement in Satellite Ground Station Networks

Abstract

In this paper, we investigate the service chaining placement problem for user requests in satellite ground station networks with minimum energy cost, which consists of server energy, switch energy, and link energy. We build the Server-Switch-Link energy model and formulate the energy optimization problem as an integer nonlinear programming problem. To address this problem, we implement a prediction-aided Greedy (PA-Greedy) algorithm depending on satellite mission planning in satellite control centers. We conduct the experiments to evaluate the proposed energy model and PA-Greedy algorithm in Fat-Tree networks, and compare the performance with the baseline Greedy algorithm and two energy models of Server-Link and Server. In a Fat-Tree network with 16 servers, the proposed Server-Switch-Link energy model with the PA-Greedy algorithm can reduce energy consumption by 17.28% when compared with the baseline Greedy algorithm, and outperform these Server-Link and Server energy models by 47.10% and 62.91%, respectively