Autonomic load balancing mechanisms in the P2P desktop grid

Abstract

Peer-to-Peer (P2P) desktop grid computing systems circumvent the performance bottleneck and limited scalability of centralized Grid architectures resulting in a massively scalable and robust system. We have designed a set of protocols that implement a distributed, decentralized desktop grid via P2P techniques. Incoming jobs having different types of resource requirements are matched with system nodes through proximity in an N-dimensional resource space. In this paper, we address problems that arise from static load balancing mechanisms for assigning jobs to nodes that can arise for various reasons, including the heterogeneity of the available nodes or the jobs to be run, and from stale information in the P2P system. We greatly improve upon our prior work by providing lightweight yet effective dynamic load balancing mechanisms to overcome load imbalances caused by the limitations of the initial static job assignment scheme. Unlike other systems, we can effectively support resource constraints of jobs during the course of redistribution since we simplify the problem of matchmaking through building a multi-dimensional resource space and mapping jobs and nodes to this space. Throughout extensive simulation results, we show that dynamic load balancing makes the overall system more scalable, by improving system throughput and response time with low additional overhead.