A New Allocation Scheme for Parallel Applications with Deadline and Security Constraints on Clusters

Abstract

Parallel applications with deadline and security constraints are emerging in various areas like education, information technology, and business. However, conventional job schedulers for clusters generally do not take security requirements of realtime parallel applications into account when making allocation decisions. In this paper, we address the issue of allocating tasks of parallel applications on clusters subject to timing and security constraints in addition to precedence relationships. A task allocation scheme, or TAPADS (task allocation for parallel applications with deadline and security constraints), is developed to find an optimal allocation that maximizes quality of security and the probability of meeting deadlines for parallel applications. In addition, we proposed mathematical models to describe a system framework, parallel applications with deadline and security constraints, and security overheads. Experimental results show that TAPADS significantly improves the performance of clusters in terms of quality of security and schedulability over three existing allocation schemes