So-Grid: A Self-organizing Grid Featuring Bio-inspired Algorithms

This article presents So-Grid, a set of bio-inspired algorithms tailored to the decentralized construction of a Grid information system that features adaptive and self-organization characteristics. Such algorithms exploit the properties of swarm systems, in which a number of entities/agents perform simple operations at the local level, but together engender an advanced form of swarm intelligence at the global level. In particular, So-Grid provides two main functionalities: logical reorganization of resources, inspired by the behavior of some species of ants and termites that move and collect items within their environment, and resource discovery, inspired by the mechanisms through which ants searching for food sources are able to follow the pheromone traces left by other ants. These functionalities are correlated, since an intelligent dissemination can facilitate discovery. In the Grid environment, a number of ant-like agents autonomously travel the Grid through P2P interconnections and use biased probability functions to: (i) replicate resource descriptors in order to favor resource discovery; (ii) collect resource descriptors with similar characteristics in nearby Grid hosts; (iii) foster the dissemination of descriptors corresponding to fresh (recently updated) resources and to resources having high quality of service (QoS) characteristics. Simulation analysis shows that the So-Grid replication algorithm is capable of reducing the entropy of the system and efficiently disseminating content. Moreover, as descriptors are progressively reorganized and replicated, the So-Grid discovery algorithm allows users to reach Grid hosts that store information about a larger number of useful resources in a shorter amount of time. The proposed approach features characteristics, including self-organization, scalability and adaptivity, which make it useful for a dynamic and partially unreliable distributed system.