Statistics: concepts and applications
Statistics: concepts and applications
Characterizations of parallelism in applications and their use in scheduling
SIGMETRICS '89 Proceedings of the 1989 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Using parallel program characteristics in dynamic processor allocation policies
Performance Evaluation
Exploiting process lifetime distributions for dynamic load balancing
ACM Transactions on Computer Systems (TOCS)
Processor allocation in multiprogrammed distributed-memory parallel computer systems
Journal of Parallel and Distributed Computing
An Opportunity Cost Approach for Job Assignment in a Scalable Computing Cluster
IEEE Transactions on Parallel and Distributed Systems
SBAC-PAD '04 Proceedings of the 16th Symposium on Computer Architecture and High Performance Computing
RouteGA: A Grid Load Balancing Algorithm with Genetic Support
AINA '07 Proceedings of the 21st International Conference on Advanced Networking and Applications
Improving scheduling decisions by using knowledge about parallel applications resource usage
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
Enhancing the efficiency of resource usage on opportunistic grids
Proceedings of the 7th International Workshop on Middleware for Grids, Clouds and e-Science
International Journal of Computational Science and Engineering
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Process scheduling techniques consider the current load situation to allocate computing resources. Those techniques make approximations such as the average of communication, processing, and memory access to improve the process scheduling, although processes may present different behaviors during their whole execution. They may start with high communication requirements and later just processing. By discovering how processes behave over time, we believe it is possible to improve the resource allocation. This has motivated this paper which adopts chaos theory concepts and nonlinear prediction techniques in order to model and predict process behavior. Results confirm the radial basis function technique which presents good predictions and also low processing demands show what is essential in a real distributed environment.