Multi-objective Service Composition with Time- and Input-Dependent QoS

Wagner, Florian; Klein, Adrian; Klöpper, Benjamin; Ishikawa, Fuyuki; Honiden, Shinichi

doi:10.1109/icws.2012.40

Cited by 46 publications

(39 citation statements)

References 22 publications

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“…Wagner et al [121] Alternative services Multiple solutions Genetic algorithm -/-Custom synthetic problems Birchmeier [122] Multiple solutions A * and beam search /--Rodriguez-Mier et al [108] Multiple solutions A * Backward search / Web Service Challenge 2008…”

Section: Web Service Composition Methodsmentioning

confidence: 99%

“…Wagner et al [121] propose a multi-objective optimization method that outputs multiple alternative solutions to WSC problems through the use of Hierarchical Workflow Graphs (HWG). The problem is solved through a genetic algorithm, with the QoS elements considered being the cost of web services, the required time to output a response, and their reliability.…”

Section: Middle Ground Methodsmentioning

confidence: 99%

“…Then, a genetic algorithm computes a Paretooptimal set, among which one solution is chosen based on the input QoS preferences. The method was evaluated using synthetic problems created by Wagner et al, [121] for which optimal solutions could not be computed efficiently even for small problems. Instead, an approximation of optimal solutions is generated.…”

Section: Middle Ground Methodsmentioning

confidence: 99%

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Non-deterministic planning methods for automated web service composition

Markou

Refanidis

2015

AIR

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Web service composition (WSC) is the task of generating new composite web services that exhibit functionalities not supported by any single web service. In its simplest form this is achieved by linking existing web services in sequence. More complex forms link services in parallel or use alternative paths. WSC can be considered a planning task, with the web services being the planning operators and the initial state and the goals being provided by the user. Particularly, since web services operate in a stochastic environment, their output is not predictable, and the problem is formulated as a non-deterministic planning one. This article presents a critical, comprehensive and up-to-date review of the literature concerning alternative non-deterministic planning methods, including probabilistic planning, determinization methods, planning in the belief state space and translationbased methods. Furthermore, the article reviews existing implementations of WSC systems, employing a variety of planning approaches, and discusses the degree in which the current achievements from the non-deterministic planning field have been adopted successfully. To the best of our knowledge, this is the first review of its kind, one that provides a thorough introduction to the vast area of automated web service composition.

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Section: Web Service Composition Methodsmentioning

confidence: 99%

Section: Middle Ground Methodsmentioning

confidence: 99%

Section: Middle Ground Methodsmentioning

confidence: 99%

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Non-deterministic planning methods for automated web service composition

Markou

Refanidis

2015

AIR

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“…In service-oriented applications, each of them is generally designed as a workflow that contains several abstract services and several concrete services. Every concrete service encapsulates information resource and function of application component, workflow specifies the logic relationships among services [11]. When an application is deployed in cloud environment, each abstract service in the application can be deployed with one or more service instances.…”

Section: Introductionmentioning

confidence: 99%

A Composite Service Selection Method Supporting Service-Sharing across Multi-SLAs

Zhang

Bin

2015

2015 IEEE World Congress on Services

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In cloud computing environments, each serviceoriented application is often instantiated with multiple workflow instances, and each of them provides a specific QoS level for a particular user category. In recent researches, most of works deploy service instances for each workflow independently, and the sharing of service instance is not considered across compositions related with different SLAs. This may cause several high-performance service instances are exclusively accessed by specific workflow instances, which can incur the following two issues: First, the remaining service instances cannot satisfy SLA for other users when high-performance ones are monopolized by some requests. Second, the utilization ratio of high-performance services will be decreased. To address these problems, a service composition model supporting the instances sharing in multiple SLA environments is provided in this paper. Since the QoSaware service composition problem is known as NP-hard, which needs a significant amount of computation time to discover optimal solutions, a solving method based on multi-objective genetic algorithm, called MSCS, is proposed to solve it heuristically. The effectiveness of this approach is demonstrated via experiments.

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“…Most researches evaluate service by data on server side. For example [4] use execute time on server side to compute, not response time on client side. So the result must be narrow and not comprise uncertainty of internet and intuitive customer experience.…”

Section: Related Workmentioning

confidence: 99%

Evaluation and Analysis of Web Service Based on Heavy Tailed Distribution

Yuan¹,

Huang²,

Bin³

2015

Proceedings of the 2015 International Conference on Applied Science and Engineering Innovation

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Abstract. More and more web services are composited together to accomplish more complicated tasks. Replaceable web services with same function need to be evaluated effectively, so as to select the best one. This paper selects better service by response time, which is easy to collect on client side machine. According to collected data, this paper points out that response time jumps periodically in a long time period, and in a short time period the response time shows heavy tailed distribution which contains normal distribution. This paper puts forward that if we use tail weight of response time distribution, together with average value of response time, we will evaluate more precisely the web service reflecting uncertainty of web networks. This paper gives method of computing tail weight and comprehensive evaluation metric. Experiments show the validity of the method. The method can also be used for evaluation of web services, web services composition, and cloud service.

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Multi-objective Service Composition with Time- and Input-Dependent QoS

Cited by 46 publications

References 22 publications

Non-deterministic planning methods for automated web service composition

Non-deterministic planning methods for automated web service composition

A Composite Service Selection Method Supporting Service-Sharing across Multi-SLAs

Evaluation and Analysis of Web Service Based on Heavy Tailed Distribution

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