Genetic algorithm-based optimization of service composition and deployment

Vanrompay, Yves; Rigole, Peter; Berbers, Yolande

doi:10.1145/1387309.1387313

Cited by 25 publications

(17 citation statements)

References 5 publications

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“…Genetic-based techniques for selecting the optimal Web service composition have been proposed in [2,5,10,11,14,[20][21][22] (see Table 1). In the approaches presented in Table 1, a genetic individual is mapped on a composition solution encoded using discrete representations (e.g.…”

Section: Non-hybrid Nature-inspired Techniquesmentioning

confidence: 99%

Hybridization of Cuckoo Search and Firefly Algorithms for Selecting the Optimal Solution in Semantic Web Service Composition

Salomie

Chifu

Pop

2013

Cuckoo Search and Firefly Algorithm

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This chapter investigates how the Cuckoo Search and Firefly Algorithm can be hybridized for performance improvement in the context of selecting the optimal or near-optimal solution in semantic Web service composition. Cuckoo Search and Firefly Algorithm are hybridized with genetic, reinforcement learning and tabu principles to achieve a proper exploration and exploitation of the search process. The hybrid algorithms are applied on an enhanced planning graph which models the service composition search space for a given user request. The problem of finding the optimal solution encoded in the enhanced planning graph can be reduced to identifying a configuration of semantic Web services, out of a very large set of possible configurations, which maximizes a fitness function which considers semantics and

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Section: Non-hybrid Nature-inspired Techniquesmentioning

confidence: 99%

Hybridization of Cuckoo Search and Firefly Algorithms for Selecting the Optimal Solution in Semantic Web Service Composition

Salomie

Chifu

Pop

2013

Cuckoo Search and Firefly Algorithm

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“…Genetic algorithm (GA) [13] is an efficient Search method based on principles of Population genetic.GA is a tool to solve complex combinatorial optimization problems. It is based on the mechanism of evolution and solving intractable optimization Problem.…”

Section: Web Service Selection Based On Genetic Algorithmmentioning

confidence: 99%

A Gravitational Search Algorithm for effective Web Service Selection for Composition with enhanced QoS in SOA

Palanikkumar¹,

Anbuselvan²,

Rithu³

2012

IJCA

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Web services selection and composition is a new software development paradigm to achieve service oriented computing. QoS of compound service is a key factor for satisfying the users" needs. The services selection algorithm based on quality of services is a combinatorial optimization problem. For Web services selection for composition based on QoS, the optimization algorithms can solve it well. Genetic Algorithm and Gravitational Search Algorithm are proposed to solve this issue. In order to meet the QoS requirements of consumers, this paper presents the QoS calculation of non functional requirements such as cost, availability, reliability and execution time. To verify the effectiveness in latency of Web Services selection the above two algorithms are compared. Results indicate the Gravitational Search Algorithm improves the latency over the Genetic algorithm.

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“…To cope with this issue, other approaches propose heuristic-based solutions (e.g., WS-HEU and WFlow [5], Genetic algorithm [8,9,6,7,10,11,12]) aiming to find near-optimal compositions, i.e., compositions that respect global QoS constraints and maximize a QoS utility function. Yu et al [5] present two heuristics, WS-HEU and WFlow, for the service selection problem.…”

Section: Related Workmentioning

confidence: 99%

“…Other approaches [8,9,6,7,10,11,12] present heuristics based on a genetic algorithm. The application of such algorithm to the service selection problem presents two main drawbacks: first, the order in which service candidates are checked is randomly chosen (e.g., Crossing [6]), whereas in our approach we aim at checking services in an ordered way to optimize the timeliness and the optimality of our algorithm.…”

Section: Related Workmentioning

confidence: 99%

QoS-Aware Service Composition in Dynamic Service Oriented Environments

et al. 2009

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Abstract. QoS-aware service composition is a key requirement in Service Oriented Computing (SOC) since it enables fulfilling complex user tasks while meeting Quality of Service (QoS) constraints. A challenging issue towards this purpose is the selection of the best set of services to compose, meeting global QoS constraints imposed by the user, which is known to be a NP-hard problem. This challenge becomes even more relevant when it is considered in the context of dynamic service environments. Indeed, two specific issues arise. First, required tasks are fulfilled on the fly, thus the time available for services' selection and composition is limited. Second, service compositions have to be adaptive so that they can cope with changing conditions of the environment. In this paper, we present an efficient service selection algorithm that provides the appropriate ground for QoS-aware composition in dynamic service environments. Our algorithm is formed as a guided heuristic. The paper also presents a set of experiments conducted to evaluate the efficiency of our algorithm, which shows its timeliness and optimality.

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Genetic algorithm-based optimization of service composition and deployment

Cited by 25 publications

References 5 publications

Hybridization of Cuckoo Search and Firefly Algorithms for Selecting the Optimal Solution in Semantic Web Service Composition

Hybridization of Cuckoo Search and Firefly Algorithms for Selecting the Optimal Solution in Semantic Web Service Composition

A Gravitational Search Algorithm for effective Web Service Selection for Composition with enhanced QoS in SOA

QoS-Aware Service Composition in Dynamic Service Oriented Environments

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