Winner Price Monotonicity for Approximated Combinatorial Auctions
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
An open computing resource management framework for real-time computing
HiPC'08 Proceedings of the 15th international conference on High performance computing
An experimental analysis of biased parallel greedy approximation for combinatorial auctions
International Journal of Intelligent Information and Database Systems
Scheduling security-critical multimedia applications in heterogeneous networks
Computer Communications
Weight-balanced security-aware scheduling for real-time computational grid
International Journal of Grid and Utility Computing
CaPaS: an optimal security-aware cache replacement algorithm for cluster storage systems
International Journal of High Performance Systems Architecture
Security-aware scheduling model for computational grid
Concurrency and Computation: Practice & Experience
Resource Management in Real Time Distributed System with Security Constraints: A Review
International Journal of Distributed Systems and Technologies
Security Driven Scheduling Model for Computational Grid Using NSGA-II
Journal of Grid Computing
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Security is increasingly becoming an important issue in the design of real-time parallel applications, which are widely used in industry and academic organizations. However, existing schedulers for real-time parallel jobs on clusters generally do not factor in security requirements when making allocation and scheduling decisions. Aiming at improving security for real-time parallel applications, we develop two resource allocation schemes, called TAPADS (Task Allocation for Parallel Applications with Deadline and Security constraints) and SHARP (Security- and Heterogeneity-Aware Resource allocation for Parallel jobs), by taking into account applications"?timing and security requirements in addition to precedence constraints. In this paper we consider two types of computing platforms: homogeneous clusters and heterogeneous clusters. To facilitate the presentation of the new schemes, we build mathematical models to describe a system framework, security overhead, and parallel applications with deadline and security constraints. The proposed schemes are applied to heuristically find resource allocations that maximize the quality of security and the probability of meeting deadlines for parallel applications running on clusters. We conducted extensive experiments using real world applications and traces as well as synthetic benchmarks. Experimental results are presented to demonstrate the effectiveness and practicality of the proposed schemes.