Probability, statistics, and queueing theory with computer science applications
Probability, statistics, and queueing theory with computer science applications
Task Allocation Algorithms for Maximizing Reliability of Distributed Computing Systems
IEEE Transactions on Computers
Safety and Reliability Driven Task Allocation in Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Period-Based Load Partitioning and Assignment for Large Real-Time Applications
IEEE Transactions on Computers
Parallel Computer Architecture: A Hardware/Software Approach
Parallel Computer Architecture: A Hardware/Software Approach
Task Allocation for Distributed Multimedia Processing on Wirelessly Networked Handheld Devices
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
Automatic Clustering of Software Systems Using a Genetic Algorithm
STEP '99 Proceedings of the Software Technology and Engineering Practice
Hierarchical Performance Modeling for Distributed System Architectures
ISCC '00 Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)
Analysis of coordinated load sharing for large distributed systems
International Journal of Computers and Applications
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A key phase in the design process of software for distributed systems is the allocation of the software components to the available hard-ware. A problem arises when a software/hardware mismatch occurs. This paper presents a solution to that problem by introducing a technique that guarantees efficient allocation of predefined scheduled object-oriented software components to the available hardware based on genetic algorithm. The allocation is to be made dynamically in a system with a predefined schedule. We thus modified the parameters of the genetic search technique to allow converging to the best solution in a relatively short time to be suitable for the dynamicity of the allocation. The performance of the allocation technique is evaluated in terms of the time cost (CPU clock pulses for more generality) required for the GA search to converge to the optimal allocation structure of the software components. The results obtained by the proposed technique are compared against the results from the branch-and-bound search technique. The experimental results indicate the effectiveness of the proposed technique in reaching the optimal allocation in considerable time, showing that it requires much less time than branch-and-bound.