Experiments with Scheduling Using Simulated Annealing in a Grid Environment
GRID '02 Proceedings of the Third International Workshop on Grid Computing
Fuzzy based resource management framework for high throughput computing
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Simulated Annealing for Grid Scheduling Problem
JVA '06 Proceedings of the IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing
Learning Cooperation in Collaborative Grid Environments to Improve Cover Load Balancing Delivery
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
An agents-based cooperative awareness model to cover load balancing delivery in grid environments
OTM'07 Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems - Volume Part I
OTM'07 Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems: CoopIS, DOA, ODBASE, GADA, and IS - Volume Part II
Dynamic job scheduling on the grid environment using the great deluge algorithm
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
An awareness-based learning model to deal with service collaboration in cloud computing
Transactions on computational collective intelligence I
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For achieving proper cooperation in Collaborative Distributed Environments (CDEs) the implementation of appropriate collaborative mechanisms in these dynamic distributed environments is essential. On one hand, awareness is a useful concept that allows users to be aware of others’ activities at every moment. On the other hand, properly covering the dynamic load-balancing problem is essential to proper cooperation among users in distributed environments. In this matter, Simulated Annealing (SA) is a well-known technique used to deal with load-balancing. This paper focuses on associating the concept of awareness with SA algorithm by presenting a new high-performance method named CAwaSA. Preliminary results show that CAwaSA is able, not only of finding a good solution for the problem (effectiveness) but also to do it in a reasonable amount of time (efficiency)