Trusted Dynamic Scheduling for Large-Scale Parallel Distributed Systems

Abstract

The terms parallel distributed systems, and grid and cloud computing, actually refer to slightly different things. But the underlying concept is the same. This is based on delivering computing resources through a large and often global network of computers. To meet the new requirements of a massive distributed computing paradigm, such as cloud, in this paper, a kind of trust mechanism-based task scheduling model was presented. Referring to the trust relationship models of social persons, trust relationship is built among computing nodes, and the trustworthiness of nodes is evaluated by utilizing the Bayesian cognitive method. Moreover, a benchmark is structured to span a range of parallelism and computing characteristics for evaluation the proposed method. Theoretical analysis and simulations prove that the proposed algorithm can efficiently meet the requirement of large-scale workloads in trust, sacrificing fewer time costs, and assuring the execution of tasks in a security way in parallel distributed computing environment.