2014
DOI: 10.1007/s10489-014-0617-y
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Discrete gbest-guided artificial bee colony algorithm for cloud service composition

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Cited by 71 publications
(33 citation statements)
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“…To tackle scalability issue, the swarm intelligent optimization algorithm with high efficiency and fast speed is widely used in the service composition problem field. In literature [1], the bee colony algorithm is applied. The introduction of time enhancement function establishes a trusted service composition model, thus transforming service composition problem into a nonlinear integer coding problem.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…To tackle scalability issue, the swarm intelligent optimization algorithm with high efficiency and fast speed is widely used in the service composition problem field. In literature [1], the bee colony algorithm is applied. The introduction of time enhancement function establishes a trusted service composition model, thus transforming service composition problem into a nonlinear integer coding problem.…”
Section: Related Workmentioning
confidence: 99%
“…1 and 2 are random variables evenly distributed over the interval [0,1]. is the inertia weight which measures the effect of the velocity of the migration on the next movement.…”
Section: Rdd Positionmentioning
confidence: 99%
See 1 more Smart Citation
“…A r a n g o a et al [24] found a solution to the decision-making system which is based on cloud environment in Water distribution systems. Huo et al [26] tackled the problem of facing a large number of cloud application services. S u g u n a and S u h a s i n i [27] analyzed the cloud efficient disaster recovery process.…”
Section: O G H a D D A M R M O G H A D D A M And C H E R I E T [22]mentioning
confidence: 99%
“…M a m u n et al [23] developed a cloud-based framework for identifying the Parkinson patients by their voice samples through their phones, thereby checking their Dysphonia over the cloud. Huo et al [26] introduced the Discrete Gbest-guided Artificial Bee Colony algorithm for optimizing the cloud service composition. S u g u n a and S u h a s i n i [27] performed the analysis of massive data storage process using the Enriched MultiObjective Optimization Model for Efficient Disaster Recovery in a cloud environment.…”
Section: Introductionmentioning
confidence: 99%