Ant Routing Concepts for Dynamic Meshed Satellite Constellations

We propose ant routing as a powerful means to enhance communications in meshed regular and irregular satellite constellations. Ant routing resembles basic mechanisms from distributed swarm intelligence in biological systems, and turns out to become an appealing solution when routing becomes a crucial problem in a complex network scenario, where traditional (deterministic) techniques either fail completely or at least face intractable complexity. The principle is to divide forwarding of information elements (packets) from the pure routing and to let ant routing operate to gather routing information, while other techniques, such as MPLS, might be used for forwarding.

[1]  Tarek Saadawi,et al.  Ant routing algorithm for mobile ad-hoc networks (ARAMA) , 2003, Conference Proceedings of the 2003 IEEE International Performance, Computing, and Communications Conference, 2003..

[2]  Markus Werner,et al.  Topological design, routing and capacity dimensioning for ISL networks in broadband LEO satellite systems , 2001, Int. J. Satell. Commun. Netw..

[3]  M. Mohorcic,et al.  Developing aggregate traffic intensity model for performance evaluation of global satellite systems , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[4]  Markus Werner,et al.  ATM-Based Routing in LEO/MEO Satellite Networks with Intersatellite Links , 1997, IEEE J. Sel. Areas Commun..

[5]  Michael Hadjitheodosiou,et al.  OPTIMIZING COMMUNICATIONS FOR CONSTELLATION SPACE MISSIONS , 2003 .

[6]  Pamela Elizabeth Clark,et al.  USE OF SWARM INTELLIGENCE IN SPACECRAFT CONSTELLATIONS FOR THE RESOURCE EXPLORATION OF THE ASTEROID BELT , 2003 .

[7]  Anton Donner,et al.  Maximum Persistence Routing in Satellite Constellation Networks , 2004 .

[8]  Anton Donner,et al.  MPLS-based satellite constellation networks , 2004, IEEE Journal on Selected Areas in Communications.

[9]  Charles E. Perkins,et al.  Ad hoc On-Demand Distance Vector (AODV) Routing , 2001, RFC.

[10]  Eric C. Rosen,et al.  Multiprotocol Label Switching Architecture , 2001, RFC.

[11]  Muli Kifle,et al.  Toward a Dynamically Reconfigurable Computing and Communication System for Small Spacecraft , 2003 .

[12]  J. Walker.  Some circular orbit patterns providing continuous whole earth coverage. , 1970 .

[13]  Janet Bruten,et al.  Ant-like agents for load balancing in telecommunications networks , 1997, AGENTS '97.

[14]  Cheng Jin,et al.  MATE: MPLS adaptive traffic engineering , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[15]  Luca Maria Gambardella,et al.  Results of the first international contest on evolutionary optimisation (1st ICEO) , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[16]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[17]  Franz Oppacher,et al.  ASGA: Improving the Ant System by Integration with Genetic Algorithms , 1998 .

[18]  Gerard Maral,et al.  Routing in networks of intersatellite links , 2002 .

[19]  F. Oppacher,et al.  Connection Management by Ants : An Application of Mobile Agents in Network Management , 1998 .

[20]  Muckai K. Girish,et al.  Formulation of the traffic engineering problems in MPLS based IP networks , 2000, Proceedings ISCC 2000. Fifth IEEE Symposium on Computers and Communications.

[21]  Chen-Khong Tham,et al.  Mobile agents based routing protocol for mobile ad hoc networks , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.