Task Allocation for Maximizing Reliability of Distributed Computer Systems
IEEE Transactions on Computers
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
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
Journal of Parallel and Distributed Computing
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
Grid Computing
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
Toward a Realistic Task Scheduling Model
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
An Online Scheduling Algorithm for Assigning Jobs in the Computational Grid
IEICE - Transactions on Information and Systems
Dynamic resource allocation heuristics that manage tradeoff between makespan and robustness
The Journal of Supercomputing
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A notable requirement of heterogeneous parallel and distributed computing systems is to maximize their processing performance and agreed upon QoS. Lots of work in this field has been done to optimize the system performance by improving certain metrics such as reliability, robustness, security, and so on. However, most of them assume that systems are running without interruption all the time and seldom consider 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 heterogeneous distributed computational systems with considering their essential features. First, we provide an availability model taking into account system's expected residual lifetime. Second, we propose an objective function about the model and develop a heuristic scheduling algorithm to maximize the availability with the makespan constraint. At last, we demonstrate these advantages through the extensive simulated experiments.