Task allocation for maximizing reliability of distributed systems: a simulated annealing approach

Authors:
Gamal Attiya;Yskandar Hamam
Affiliations:
ESIEE Paris, Laboratory A2SI, Noisy-Le-Grand, France;ESIEE Paris, Laboratory A2SI, Noisy-Le-Grand, France
Venue:
Journal of Parallel and Distributed Computing
Year:
2006

Citing 10
Cited 12

Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing

Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Task Allocation for Maximizing Reliability of Distributed Computer Systems

IEEE Transactions on Computers
Genetic algorithm based approach for file allocation on distributed systems

Computers and Operations Research - Special issue on genetic algorithms
Task Allocation Algorithms for Maximizing Reliability of Distributed Computing Systems

IEEE Transactions on Computers
Allocating Task Interaction Graphs to Processors in Heterogeneous Networks

IEEE Transactions on Parallel and Distributed Systems
Algorithms for reliability-oriented module allocation in distributed computing systems

Journal of Systems and Software
Maximizing reliability of distributed computing system with task allocation using simple genetic algorithm

Journal of Systems Architecture: the EUROMICRO Journal
Optimal Task Assignment in Heterogeneous Distributed Computing Systems

IEEE Concurrency
Reliability and cost optimization in distributed computing systems

Computers and Operations Research
A fast algorithm for reliability-oriented task assignment in a distributed system

Computer Communications

Static resource allocation for heterogeneous computing environments with tasks having dependencies, priorities, deadlines, and multiple versions

Journal of Parallel and Distributed Computing
Cost-oriented task allocation and hardware redundancy policies in heterogeneous distributed computing systems considering software reliability

Computers and Industrial Engineering
Optimizing the fault tolerance capabilities of distributed real-time systems

ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
The decision model of task allocation for constrained stochastic distributed systems

Computers and Industrial Engineering
Task allocation for maximizing reliability of distributed computing systems using honeybee mating optimization

Journal of Systems and Software
Task assignment in heterogeneous computing systems using an effective iterated greedy algorithm

Journal of Systems and Software
Task scheduling using Bayesian optimization algorithm for heterogeneous computing environments

Applied Soft Computing
Multi-objective workflow grid scheduling based on discrete particle swarm optimization

SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Resource augmentation for fault-tolerance feasibility of real-time tasks under error bursts

Proceedings of the 20th International Conference on Real-Time and Network Systems
Maximal profit service task partition and distribution in computer grid

Computers and Industrial Engineering
An effective iterated greedy algorithm for reliability-oriented task allocation in distributed computing systems

Journal of Parallel and Distributed Computing
Task assignment for minimizing application completion time using honeybee mating optimization

Frontiers of Computer Science: Selected Publications from Chinese Universities

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses the problem of task allocation in heterogeneous distributed systems with the goal of maximizing the system reliability. It first develops an allocation model for reliability based on a cost function representing the unreliability caused by the execution of tasks on the system processors and the unreliability caused by the interprocessor communication time subject to constraints imposed by both the application and the system resources. It then presents a heuristic algorithm derived from the well-known simulated annealing (SA) technique to quickly solve the mentioned problem. The performance of the proposed algorithm is evaluated through experimental studies on a large number of randomly generated instances. Indeed, the quality of solutions are compared with those derived by using the branch-and-bound (BB) technique.