Probabilistic Observation Prediction Model based E4 Scheduling Mechanism in Peer to Peer Grid Computing

Abstract

Peer to peer (P2P) grid computing is an Internet-based parallel computing paradigm to achieve tremendous computing power by voluntary peers. Since peers are not dedicated to a system, peers are free to leave and join autonomously during computation in this computing environment. A scheduling mechanism must cover the volatility of peers to support a reliable P2P grid computing system. Most existing P2P grid computing systems, however, suffer from blocked job execution and delayed makespan because they do not consider the volatile features of peers in the scheduling procedure. In order to improve system reliability, we propose a probabilistic observation prediction (POP) -based EA scheduling mechanism supporting three advanced scheduling policies: loose time constraint policy (LTCP), strict time constraint policy (STCP), and hybrid time constraint policy (HTCP). LTCP is for general use, STCP aims at minimizing makespan, and HTCP attempts to improve efficiency, and performance-to-cost ratio. All policies are based on stochastic modeling of peer state transition while endeavoring to manage the volatile features of peers