Adaptive load sharing in homogeneous distributed systems
IEEE Transactions on Software Engineering
Adaptive Optimal Load Balancing in a Nonhomogeneous Multiserver System with a Central Job Scheduler
IEEE Transactions on Computers
A Dynamic Load-Balancing Policy with a Central Job Dispatcher (LBC)
IEEE Transactions on Software Engineering
Customized dynamic load balancing for a network of workstations
Journal of Parallel and Distributed Computing
Observations on Using Genetic Algorithms for Dynamic Load-Balancing
IEEE Transactions on Parallel and Distributed Systems
Distributed Operating Systems: The Logical Design
Distributed Operating Systems: The Logical Design
Strategies for Dynamic Load Balancing on Highly Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
A Simulation Study of Dynamic Load Balancing for Network-based Parallel Processing
ISPAN '97 Proceedings of the 1997 International Symposium on Parallel Architectures, Algorithms and Networks
(R) A Study of a Non-Linear Optimization Problem Using a Distributed Genetic Algorithm
ICPP '96 Proceedings of the Proceedings of the 1996 International Conference on Parallel Processing - Volume 2
A scalable cellular implementation of parallel genetic programming
IEEE Transactions on Evolutionary Computation
Evolutionary programming techniques for economic load dispatch
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Generating robust and flexible job shop schedules using genetic algorithms
IEEE Transactions on Evolutionary Computation
Instantiation of a Generic Model for Load Balancing with Intelligent Algorithms
IWSOS '08 Proceedings of the 3rd International Workshop on Self-Organizing Systems
A Space-Based Generic Pattern for Self-Initiative Load Balancing Agents
ESAW '09 Proceedings of the 10th International Workshop on Engineering Societies in the Agents World X
Replica-aided load balancing in overlay networks
Journal of Network and Computer Applications
Hi-index | 12.05 |
A computer simulation model that investigated the contribution made by evolutionary learning techniques on load-balancing problems was proposed. Three parameters for controlling the load-balancing activity of a node were used. The system was tested in different distributed systems, including different processing and communication speeds as well as network structures. Our experimental results showed that the system demonstrated an effective learning capability in balancing load among different processing nodes. It also showed that each of these three parameters played an important role in contributing to load-balancing, and that the system performance increased upon increasing the number of parameter changes simultaneously. The contribution made by evolutionary learning was significant as the variety of node processing speeds increased.