An improved multi-agent simulation methodology for modelling and evaluating wireless communication systems resource allocation algorithms

Multi-Agent Systems (MAS) constitute a well known approach in modelling dynamical real world systems. Recently, this technology has been applied to Wireless Communication Systems (WCS), where efficient resource allocation is a primary goal, for modelling the physical entities involved, like Base Stations (BS), service providers and network operators. This paper presents a novel approach in applying MAS methodology to WCS resource allocation by modelling more abstract entities involved in WCS operation, and especially the concurrent network procedures (services). Due to the concurrent nature of a WCS, MAS technology presents a suitable modelling solution. Services such as new call admission, handoff, user movement and call termination are independent to one another and may occur at the same time for many different users in the network. Thus, the required network procedures for supporting the above services act autonomously, interact with the network environment (gather information such as interference conditions), take decisions (e.g. call establishment), etc, and can be modelled as agents. Based on this novel simulation approach, the agent cooperation in terms of negotiation and agreement becomes a critical issue. To this end, two negotiation strategies are presented and evaluated in this research effort and among them the distributed negotiation and communication scheme between network agents is presented to be highly efficient in terms of network performance. The multi-agent concept adapted to the concurrent nature of large scale WCS is, also, discussed in this paper

Self-organising satellite constellation in geostationary Earth orbit

This paper presents a novel solution to the problem of autonomous task allocation for a self-organizing satellite constellation in Earth orbit. The method allows satellites to cluster themselves above targets on the Earth’s surface. This is achieved using Coupled Selection Equations (CSE) - a dynamical systems approach to combinatorial optimization whose solution tends asymptotically towards a Boolean matrix describing the pairings of satellites and targets which solves the relevant assignment problems. Satellite manoeuvers are actuated by an Artificial Potential Field method which incorporates the CSE output. Three demonstrations of the method’s efficacy are given - first with equal numbers of satellites and targets, then with a satellite surplus, including agent failures, and finally with a fractionated constellation. Finally, a large constellation of 100 satellites is simulated to demonstrate the utility of the method in future swarm mission scenarios. The method provides efficient solutions with quick convergence, is robust to satellite failures, and hence appears suitable for distributed, on-board autonomy