Feedback scheduling of real-time divisible loads in clusters
ACM SIGBED Review - Special issue on the the 14th IEEE real-time and embedded technology and applications symposium (RTAS'08) WIP session
Real-time scheduling of divisible loads in cluster computing environments
Journal of Parallel and Distributed Computing
Enhanced real-time divisible load scheduling with different processor available times
HiPC'07 Proceedings of the 14th international conference on High performance computing
Multi-round real-time divisible load scheduling for clusters
HiPC'08 Proceedings of the 15th international conference on High performance computing
A survey of hard real-time scheduling for multiprocessor systems
ACM Computing Surveys (CSUR)
Scheduling real-time divisible loads with advance reservations
Real-Time Systems
Efficient real-time divisible load scheduling
Journal of Parallel and Distributed Computing
Resource Management in Real Time Distributed System with Security Constraints: A Review
International Journal of Distributed Systems and Technologies
International Journal of Parallel Programming
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Cluster computing has emerged as a new paradigm for solving large-scale problems. To enhance QoS and provide performance guarantees in cluster computing environments, various real-time scheduling algorithms and workload models have been investigated. Computational loads that can be arbitrarily divided into independent pieces represent many real-world applications. Divisible load theory (DLT) provides insight into distribution strategies for such computations. However, the problem of providing performance guarantees to divisible load applications has not yet been systematically studied. This paper investigates such algorithms for a cluster environment. Design parameters that affect the performance of these algorithms and scenarios when the choice of these parameters have significant effects are studied. A novel algorithmic approach integrating DLT and EDF (earliest deadline first) scheduling is proposed. For comparison, we also propose a heuristic algorithm. Intensive experimental results show that the application of DLT to real-time cluster-based scheduling leads to significantly better scheduling approaches.