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

Abstract

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.

Keywords:

• Complex systems
• Dynamic resource discovery
• Adaptive
• Social networks
• Ecological networks

Acknowledgements

This work was supported in part by the Key Project of the National Nature Science Foundation of China (No. 60534020), the National Nature Science Foundation of China (No. 60474037 and 60004006) and Program for New Century Excellent Talents in University.