Energy-Efficient Controller Placement in Software-Defined Satellite-Terrestrial Integrated Network

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 21; p. 5561
• Main Authors: Wei, Linhui, Chang, Chen, Liu, Yu, Wang, Yumei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2022
• Subjects: Algorithms; Communication; controller placement; Controllers; Data links; Energy consumption; Energy efficiency; Flow control; Heuristic; Internet of Things; Iridium; Iridium network; Latency; Linear programming; Low earth orbit satellites; Network latency; Network topologies; Optimization; Placement; Remote sensing; Satellite networks; satellite-terrestrial integrated network; Satellites; Simulated annealing; Simulation; Software; Software-defined networking; Topology; Traffic control; Unmanned aerial vehicles; Wireless access points
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs14215561

The satellite-terrestrial integrated network (STIN), as an integration of the satellite network and terrestrial, has become a promising architecture to support global coverage and ubiquitous connection. The architecture of software-defined networking (SDN) is utilized to intelligently coordinate the global STIN, in which the placement schemes of SDN controllers, including the locations, number, and roles, would produce various performances. However, the uneven distribution of global users leads to the unbalanced energy consumption of satellite resources, which brings a heavy burden for satellites to maintain the control flows for network management. To provide green communication for international economic trade in the countries along the Belt and Road, in this paper, we focus on the energy-efficient controller placement (EECP) problem in the software-defined STIN. The satellite gateways are located in the countries along the Belt and Road, which accounts for a large number of traffic demands and a dense population. The controllers are deployed on the LEO satellites, where each LEO satellite is a candidate controller. The energy consumption for the control paths and the user data links is modeled and then formulated as the flow processing-oriented optimization problem. A modified simulated annealing placement (MSAP) algorithm is developed to solve the EECP problem, in which we use the greedy way to obtain the initial set of controllers, and then the final optimal controller placement result is obtained by the simulated annealing algorithm. Extensive simulations are conducted on the simulated Iridium satellite network topology and statistics data. Compared with other algorithms, the results show that MSAP reduces network energy consumption by 20% and average latency by 25%.