Object-oriented analysis and design with applications (2nd ed.)
Object-oriented analysis and design with applications (2nd ed.)
The Unified Modeling Language user guide
The Unified Modeling Language user guide
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
On Customizing the UML for Modeling Performance-Oriented Applications
UML '02 Proceedings of the 5th International Conference on The Unified Modeling Language
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Performance evaluation for object oriented software systems
ACM SIGSOFT Software Engineering Notes
Applying genetic algorithms to decision making in autonomic computing systems
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
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Distributed computing has now become one of the most efficient network system configurations to exhibit parallelism in loosely coupled systems. These systems are known for better reliability, availability, scalability and robustness, intended to provide high performance computing in a very efficient manner. The composition of distributed systems consists of multiple autonomous computers that can be geographically dispersed and interconnected with each other to provide optimum resource utilization. The degree of resource utilization is one of the key criteria for evaluating the performance of such systems. We propose a genetic-algorithm-based approach to load optimization in a distributed computing environment. Genetics algorithm has been adapted from the biological gene theory. Since it shows the existence of the fittest chromosome from the sample chromosomes population, it may be used to find the most optimum solution for any problem. This research work demonstrates the implication of genetic algorithms to optimize the overall waiting time for a set of processes to be executed on a set of servers. In order to understand the design complexity, we modeled the proposed approach using UML class and sequence diagrams. The results of the proposed model have been found beneficial when implemented and tested under various test scenarios using C++.