A worldwide flock of Condors: load sharing among workstation clusters
Future Generation Computer Systems - Special issue: resource management in distributed systems
Future Generation Computer Systems - Special issue on metacomputing
Condor-G: A Computation Management Agent for Multi-Institutional Grids
Cluster Computing
Enhanced Algorithms for Multi-site Scheduling
GRID '02 Proceedings of the Third International Workshop on Grid Computing
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
The EASY - LoadLeveler API Project
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Probabilistic performance guarantee for real-time tasks with varying computation times
RTAS '95 Proceedings of the Real-Time Technology and Applications Symposium
Slack Stealing Job Admission Control Scheduling
Slack Stealing Job Admission Control Scheduling
Job Superscheduler Architecture and Performance in Computational Grid Environments
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
The Journal of Supercomputing
An adaptive job allocation strategy for heterogeneous multi-cluster systems
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
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Cooperative resource sharing enables distinct organizations to form a federation of computing resources. The motivation behind cooperation is that organizations are likely to serve each other by trading unused CPU cycles given the existence of irregular usage patterns of their local resources. In this way, resource sharing would enable organizations to purchase resources at a feasible level while meeting peak computational throughput requirements. This federation results in community grid that must be managed. A functional broker is deployed to facilitate remote resource access within the community grid. A major issue is the problem of correlations in job arrivals caused by seasonal usage and/or coincident resource usage demand patterns. These correlations incur high levels of burstiness in job arrivals causing the job queue of the broker to grow to an extent such that its performance becomes severely impaired. Since job arrivals cannot be controlled, management strategies must be employed to admit jobs in a manner that can sustain a fair level of resource allocation performance at all participating organizations in the community. In this paper, we present a theoretical analysis of the problem of job traffic burstiness on resource allocation performance in order to elicit the general job management strategies to be employed. Based on the analysis, we define and justify a job management strategies for the resource broker to cope with overload conditions caused by job arrival correlations.