An adaptive social network-inspired approach to resource discovery for the complex grid systems

This paper applies the principles and concepts in social networks to designing a decentralized, survivable and adaptive resource discovery approach in complex grid systems. The simulation results show that our approach can: (i) form relationship among clusters and significantly improve the discovery performance; (ii) adapt well to different resource distributions and user request patterns; (iii) survive from the changes of dynamic environments, including variable-biased user requests and agent amounts as well as partial failure of the agents. Our approach is not only a beneficial experience on dynamic resource discovery of complex grid systems, but also a further attempt to exploit one type of complex systems-inspired approach to build useful services in another type of complex systems.