Decentralized proactive resource allocation for maximizing throughput of P2P Grid

Peer-to-peer Desktop Grids provide integrated computational resources by leveraging autonomous desktop computers located at the edge of the Internet to offer high computing power. The arbitrary arrival and serving rates of tasks on peers impedes the high throughput in large-scale P2P Grids. We propose a novel autonomous resource allocation scheme, which can maximize the throughput of self-organizing P2P Grid systems. Our design possesses three key features: (1) high adaptability to dynamic environment by proactive and convex-optimal estimation of nodes’ volatile states; (2) minimized task migration conflict probability (upper bound can be limited to 2%) of over-utilized nodes individually shifting surplus loads; (3) a load-status conscious gossip protocol for optimizing distributed resource discovery effect. Based on a real-life user’s workload and capacity distribution, the simulation results show that our approach could get significantly improved throughput with 23.6–47.1% reduction on unprocessed workload compared to other methods. We also observe high scalability of our solution under dynamic peer-churning situations.

► We devise a proactive model to optimize system throughput for P2P Grid system.
► Avg load level is proved to fully reflect throughput of large-scale P2P Grid.
► Node’s surplus load amount to shift is optimized using convex-optimization.
► Load balancing is devised combining the efficient proactive load prediction model.
► Task migration conflict is minimized with small conflict probability upperbound.