The available capacity of a privately owned workstation environment
Performance Evaluation
Exploiting process lifetime distributions for dynamic load balancing
ACM Transactions on Computer Systems (TOCS)
Future Generation Computer Systems - Special issue on metacomputing
Homeostatic and Tendency-Based CPU Load Predictions
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
The statistical properties of host load
Scientific Programming
Resource use pattern analysis for opportunistic grids
Proceedings of the 6th international workshop on Middleware for grid computing
Prediction of dynamical, nonlinear, and unstable process behavior
The Journal of Supercomputing
Achieving better performance through true best effort in scavenging grid computing
Proceedings of the 2008 Euro American Conference on Telematics and Information Systems
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Opportunistic grid computing middleware has as a main concern the need to guarantee that the performance of local applications running on the machines that donate resources is not affected. This concern, together with the fact that it happens in an extremely dynamic environment, causes the adoption of a treatment based on the best-effort principle for grid applications. This means that efficient application management schemes are usually not employed, which results in less than optimal performance as grid applications often need to be restarted due to (often temporary) resource claims by local user applications. This paper presents a method to improve the performance of grid applications, taking into account resource usage profiles for local applications, trying to identify when such resource claims are temporary and avoiding actions such as the migration of grid tasks. The proposed approach was implemented as part of the InteGrade middleware and its evaluation shows promising results for the efficient management of grid applications.