Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
The grid
Scheduling in a Grid Computing Environment Using Genetic Algorithms
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A probabilistic scheduling heuristic for computational grids
Multiagent and Grid Systems
Immediate mode scheduling in grid systems
International Journal of Web and Grid Services
Batch mode scheduling in grid systems
International Journal of Web and Grid Services
Genetic algorithm in grid scheduling with multiple objectives
AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Scheduling Parallel Tasks with Communication Overhead in an Environment with Multiple Machines
IEICE - Transactions on Information and Systems
Efficient annealing -inspired genetic algorithm for information retrieval from web-document
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
An innovative perspective on mapping in grids
BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
A dyeing workshop hierarchical scheduling strategy based on genetic algorithm and multi-agent system
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Computational models and heuristic methods for Grid scheduling problems
Future Generation Computer Systems
An adaptive multisite mapping for computationally intensive grid applications
Future Generation Computer Systems
Tackling the grid job planning and resource allocation problem using a hybrid evolutionary algorithm
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Grid scheduling optimization under conditions of uncertainty
NPC'07 Proceedings of the 2007 IFIP international conference on Network and parallel computing
Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm
Future Generation Computer Systems
A rotary chaotic PSO algorithm for trustworthy scheduling of a grid workflow
Computers and Operations Research
Multisite co-allocation algorithms for computational grid
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Tackling trust issues in virtual organization load balancing
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
A task duplication based scheduling algorithm on GA in grid computing systems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Solving scheduling problems in grid resource management using an evolutionary algorithm
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part II
The study of improved grid resource scheduling algorithm
ICICA'11 Proceedings of the Second international conference on Information Computing and Applications
Information Sciences: an International Journal
A new approach to the job scheduling problem in computational grids
Cluster Computing
Observations on Effect of IPC in GA Based Scheduling on Computational Grid
International Journal of Grid and High Performance Computing
Double auction-inspired meta-scheduling of parallel applications on global grids
Journal of Parallel and Distributed Computing
Future Generation Computer Systems
A novel scheduling model for computational grid using quantum genetic algorithm
The Journal of Supercomputing
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The computing GRID infrastructure could benefit of techniques that can improve the over-all throughput of the system. It is possible that job submission will include different ontology in resource requests due to the generality of the GRID infrastructure. Such flexible resource request could offer the opportunity to optimize several parameters, from network load to job costs in relation to due time, more generally the quality of services. We present the result of the simulation of GRID jobs allocation. The search strategy for this input case does not converge to the optimal case inside the limited number of trial performed, in contrast with previous work on up to 24 jobs [Scheduling in a Grid Computing Environment using Genetic Algorithms, in: Proceedings of the International Parallel and Distributed Processing Symposium: IPDPS 2002 Workshops]. The benefits of the usage of the genetic algorithms to improve the quality of the scheduling is discussed. The simulation has been obtained using an environment GGAS suitable to study the scheduling of jobs in a distributed group of parallel machines. The modular structure of GGAS allows to expand its functionalities to include other first level schedule policy with respect to the FCFS that is considered. The result of this paper suggests the usage of local search strategy to improve the convergence when the number of jobs to be considered is as big as in real world operation.