Capacity analysis method for MLSN based on improved DGA

Capacity analysis of satellite network, especially multilayer one, is of theoretical and practical significance for improving the network efficiency and strengthening the guaranteed ability of network services. However, existing solutions, which usually focus on Up/Down links (UDLs) of satellite network, without considering the characteristics of satellite network, e.g., dynamic topology, limited resources, periodicity, are not scalable for the capacity analysis of Inter-Satellite links (ISLs) of Multi-Layer Satellite Network (MLSN). In this paper, we present a capacity analysis method for MLSN based on an improved Distributed Genetic Algorithm (DGA). The improved DGA, as an intelligent optimization algorithm, is used to solve the problems of network capacity analysis. Moreover, the capacity analysis method is applied in the MLSN to analyze the network capacity and extensively evaluated. Simulation results demonstrate that the method can efficiently calculate the upper bound and lower bound of network capacity with faster convergence speed, higher searching precision and ability of avoiding premature convergence. In addition, we conclude that node failures lead to the decrease of network capacity and different constellation structures have different effects on the upper bound and lower bound of network capacity.

[1]  Ferit Yegenoglu,et al.  Next-generation satellite networks: architectures and implementations , 1999, IEEE Commun. Mag..

[2]  Hui Li,et al.  Adaptive Routing Strategy in Multi Layer Satellite Communication Networks , 2006, 2006 7th International Symposium on Antennas, Propagation & EM Theory.

[3]  Giacomo Morabito,et al.  Increasing Capacity Through the Use of the Timing Channel in Power-Constrained Satellite Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[4]  Zhu Cui.  Migration Strategy for Mobile Agent Based on Distributed Genetic Algorithm , 2007 .

[5]  James Cutler,et al.  Assessing the capacity of a federated ground station , 2010, 2010 IEEE Aerospace Conference.

[6]  Lu Jianhua.  Uplink multiple access interference and capacity of WCDMA GEO satellite communication system , 2010 .

[7]  Haitham S. Cruickshank,et al.  Delay- and Disruption-Tolerant Networking (DTN): An Alternative Solution for Future Satellite Networking Applications , 2011, Proceedings of the IEEE.

[8]  Pascal Bouvry,et al.  Improving Classical and Decentralized Differential Evolution With New Mutation Operator and Population Topologies , 2011, IEEE Transactions on Evolutionary Computation.

[9]  P. Truchly,et al.  Performance of multilayered satellite networks , 2012, Proceedings Elmar.

[10]  Nei Kato,et al.  Assessing packet delivery delay in multi-layered satellite networks , 2012, 2012 IEEE International Conference on Communications (ICC).

[11]  Xiang Chen,et al.  Capacity and loading analysis of digital channelized SATCOM system , 2012, 7th International Conference on Communications and Networking in China.

[12]  James W. Cutler,et al.  Models and Tools to Evaluate Space Communication Network Capacity , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[13]  Nei Kato,et al.  Packet Transfer Delay Minimization by Network-Wide Equalization of Unbalanced Traffic Load in Multi-Layered Satellite Networks , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[14]  Nei Kato,et al.  A Traffic Distribution Technique to Minimize Packet Delivery Delay in Multilayered Satellite Networks , 2013, IEEE Transactions on Vehicular Technology.

[15]  Chuan Wu,et al.  A Reverse Auction Based Allocation Mechanism in the Cloud Computing Environment , 2013 .

[16]  Yang Tie-ju,et al.  Spectrum Allocation Based on Improved Genetic Algorithm in Cognitive Radio System , 2014 .

[17]  Hui Cheng,et al.  QoS multicast routing protocol oriented to cognitive network using competitive coevolutionary algorithm , 2014, Expert Syst. Appl..