Tools and Techniques for Measuring and Improving Grid Performance
IWDC '02 Proceedings of the 4th International Workshop on Distributed Computing, Mobile and Wireless Computing
Collectives for multiple resource job scheduling across heterogeneous servers
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Job Superscheduler Architecture and Performance in Computational Grid Environments
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
A Heuristic Scheduling Strategy for Independent Tasks on Grid
HPCASIA '05 Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region
Multiple-resource request scheduling for differentiated QoS at website gateway
Computer Communications
Node localization for distributed simulation based on logical node group in simulation grid
Edutainment'10 Proceedings of the Entertainment for education, and 5th international conference on E-learning and games
Implementation of round robin policy in DNS for thresholding of distributed web server system
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Agent based load balancing scheme using affinity processor scheduling for multicore architectures
WSEAS Transactions on Computers
An enhanced load balancing mechanism based on deadline control on GridSim
Future Generation Computer Systems
Coordinating learning agents for multiple resource job scheduling
ALA'09 Proceedings of the Second international conference on Adaptive and Learning Agents
Load balancing non-uniform parallel computations
Proceedings of the 2013 workshop on Programming based on actors, agents, and decentralized control
Exploiting multi-core nodes in peer-to-peer grids
Journal of Parallel and Distributed Computing
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An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource size or balance may be different across servers. One approach to resource management for this grid is to layer a global load distribution system on top of the local job management systems at each site. Unfortunately, classical load distribution policies fail on two aspects when applied to a multi-resource server grid. First, simple load indices may not recognize that a resource imbalance exists at a server. Second, classical job selection policies do not actively correct such a resource imbalanced state. We show through simulation that new policies based on resource balancing perform consistently better than the classical load distribution policies.