Application of load balancing based on symmetric balanced incomplete block design to random networks
Information Sciences: an International Journal
Trace-based evaluation of job runtime and queue wait time predictions in grids
Proceedings of the 18th ACM international symposium on High performance distributed computing
Distributed load balancing over directed network topologies
ACC'09 Proceedings of the 2009 conference on American Control Conference
Mixture of ANFIS systems for CPU load prediction in metacomputing environment
Future Generation Computer Systems
Data warehouses in grids with high qos
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems
Journal of Parallel and Distributed Computing
ADNTIIC'11 Proceedings of the Second international conference on Advances in New Technologies, Interactive Interfaces and Communicability
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Connected world-widely distributed computers and data systems establish a global source of processing power and data, called, a grid. Key properties of a grid are the fact that computers providing processing power may connect and disconnect at any time, and that demands for processing power may highly fluctuate over time. This has raised the need for the development of applications that are robust against changing circumstances. In (A. M. Dobber et al., 2004) the impact of fluctuations in processing speeds on running times has been investigated, and it was found that dynamic load balancing methods provide a promising means to deal with the ever-changing environment in the grid. In this paper we demonstrate with extensive experiments in a real grid environment, Planetlab, that dynamic load balancing based on predictions via exponential smoothing indeed lead to significant reductions in running times of parallel applications in a randomly changing grid environment.