Genetic Algorithm for Independent Job Scheduling in Grid Computing
Alternative metrics PlumXhttp://hdl.handle.net/11012/179200
MetadataShow full item record
Grid computing refers to the infrastructure which connects geographically distributed computers ownedby various organizations allowing their resources, such as computational power and storage capabilities, to beshared, selected, and aggregated. Job scheduling is the problem of mapping a set of jobs to a set of resources.It is considered one of the main steps to e ciently utilise the maximum capabilities of grid computing systems.The problem under question has been highlighted as an NP-complete problem and hence meta-heuristic methodsrepresent good candidates to address it. In this paper, a genetic algorithm with a new mutation procedure tosolve the problem of independent job scheduling in grid computing is presented. A known static benchmark forthe problem is used to evaluate the proposed method in terms of minimizing the makespan by carrying out anumber of experiments. The obtained results show that the proposed algorithm performs better than some knownalgorithms taken from the literature.
Document typePeer reviewed
SourceMendel. 2017 vol. 23, č. 1, s. 65-72. ISSN 1803-3814
- Vol. 23, No. 1