Task Allocation for Maximizing Reliability of Distributed Computer Systems
IEEE Transactions on Computers
Safety and Reliability Driven Task Allocation in Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Distributed functions allocation for reliability and delay optimization
ACM '86 Proceedings of 1986 ACM Fall joint computer conference
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
ICPP '00 Proceedings of the Proceedings of the 2000 International Conference on Parallel Processing
Scheduling methods for efficient utilization of cluster computing environments
Scheduling methods for efficient utilization of cluster computing environments
Measuring the Robustness of a Resource Allocation
IEEE Transactions on Parallel and Distributed Systems
A Stochastic Approach to Measuring the Robustness of Resource Allocations in Distributed Systems
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
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A notable requirement of clusters is to maximize its processing performance. Lots of work in this area has been done to optimize the system performance by improving certain metric such as reliability, availability, security and so on. However, most of them assumes that the system is running without interruption and seldom considers the system's intrinsic characteristics, such as failure rate, repair rate and lifetime. In this paper, we study how to achieve high availability based on residual lifetime analysis for the repairable heterogeneous clusters with makespan constraints. First, we provide an availability model based on addressing the cluster's residual lifetime model. Second, we give an objective function about the model and develop a heuristic scheduling algorithm to maximize the availability the makespan constraint. At last, we demonstrate these advantages through the extensive simulated experiments.