Locality-Preserving Clustering and Discovery of Resources in Wide-Area Distributed Computational Grids
In large-scale computational Grids, discovery of heterogeneous resources as a working group is crucial to achieving scalable performance. This paper presents a resource management scheme including a hierarchical cycloid overlay architecture, resource clustering and discovery algorithms for wide-area distributed Grid systems. The authors establish program/data locality by clustering resources based on their physical proximity and functional matching with user applications. They further develop dynamism-resilient resource management algorithm, cluster-token forwarding algorithm and deadline-driven resource management algorithms.