Towards Proactive Web Service Adaptation

Moustafa, Ahmed A.; Zhang, Minjie

doi:10.1007/978-3-642-31095-9_31

Cited by 11 publications

(6 citation statements)

References 17 publications

(21 reference statements)

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“…In the proposed algorithm, i.e., Algorithm 3, an action, i.e., Web service, is selected, based on the dominance relation between the Q-vectors, following the -greedy exploration strategy (Lines 1-6). Then, instead of repeatedly backing up the maximal expected rewards, i.e., as in the single objective case [13], it backs up the set of expected rewards that are maximal for some set of linear preferences (Lines 7-10).…”

Section: Multiple Policy Multi-objective Service Compositionmentioning

confidence: 99%

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Multi-Objective Service Composition in Uncertain Environments

Mostafa¹,

Zhang²

2024

IEEE Trans. Serv. Comput.

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Web services have the potential to offer the enterprises with the ability to compose internal and external business services in order to accomplish complex processes. Service composition then becomes an increasingly challenging issue when complex and critical applications are built upon services with different QoS criteria. However, most of the existing QoS-aware service composition techniques are simply based on the assumption that multiple QoS criteria, no matter whether these multiple criteria are conflicting or not, can be combined into a single criterion to be optimized, according to some utility functions. In practice, this can be very difficult as these utility functions or weights are not well-known a priori. In addition, the existing approaches are designed to work in certain environments, where the QoS parameters are well-known in advance. These approaches will render fruitless when facing uncertain and dynamic environments, e.g., cloud environments, where no prior knowledge of the QoS parameters is available. In this paper, two novel multi-objective approaches are proposed to handle QoS-aware Web service composition with conflicting objectives and various restrictions on the quality matrices. The proposed approaches use reinforcement learning in order to deal with the uncertainty characteristics inherent in open and dynamic environments. Experimental results reveal the ability of the proposed approaches to find a set of Pareto optimal solutions, which have the equivalent quality to satisfy multiple QoS-objectives with different user preferences.

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Section: Multiple Policy Multi-objective Service Compositionmentioning

confidence: 99%

“…The values of these learning parameters are decided based on previous empirical simulations conducted by the authors [13] as follows. The learning rate α is set to 1, the discount factor γ is set to 0.8 and the -greedy exploration strategy value is set to 0.7.…”

Section: Experiments Settingmentioning

confidence: 99%

Multi-Objective Service Composition in Uncertain Environments

Mostafa¹,

Zhang²

2024

IEEE Trans. Serv. Comput.

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“…However, their approach is contingent on the service provider; also, the author did not discuss the various hidden states or probabilistic insight of remote web services. Moustafa et al [23] proposed a proactive approach to web services composition (WSC), which uses the Markov Decision Process (MDP) to model WSC process and uses Q-learning for a Reinforcement Learning technique to adapt to dynamic change in the WSC environments proactively. This approach monitors the WSC to determine proactive adaptation by analyzing the web service execution log's historical data.…”

Section: Related Workmentioning

confidence: 99%

Towards Dynamic Reconfiguration of a Composite Web Service: An Approach Based on QoS Prediction

et al. 2021

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Service-oriented architecture provides the ability to combine several web services in order to fulfil a user-specific requirement. In dynamic environments, the appearance of several unforeseen events can destabilize the composite web service (CWS) and affect its quality. To deal with these issues, the composite web service must be dynamically reconfigured. Dynamic reconfiguration may be enhanced by avoiding the invocation of degraded web services by predicting QoS for the candidate web service. In this paper, we propose a dynamic reconfiguration method based on HMM (Hidden Markov Model) states to predict the imminent degradation in QoS and prevent the invocation of partner web services with degraded QoS values. PSO (Particle Swarm Optimization) and SFLA (Shuffled Frog Leaping Algorithm) are used to improve the prediction efficiency of HMM. Through extensive experiments on a real-world dataset, WS-Dream, the results demonstrate that the proposed approach can achieve better prediction accuracy. Moreover, we carried out a case study where we revealed that the proposed approach outperforms several state-of-the-art methods in terms of execution time.

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“…To adapt dynamically to composition environment, reinforcement policy is used in [10] to get optimal workflow. ProAdapt, is a framework that uses proactive adaptation of web services using exponentially weighed moving averages based upon prediction [4].…”

Section: Related Workmentioning

confidence: 99%

Managing Availability of web services in service oriented systems

Kahlon

Chahal

Kapur

et al. 2015

2015 Asia-Pacific Software Engineering Conference (APSEC)

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In real world Service Oriented Software Systems, changes to web services infrastructure are not an exception but a rule. Timely detection and a fast reaction to handle these changes are important to reduce the impact. This paper proposes an agent based framework to manage the situation when third party web services become unavailable. It uses the concept of mobile agents to monitor web services on the provider side. The framework is implemented using Advanced JAVA and JADE environment. Experimental analysis shows that the proposed solution is both effective and efficient. In future, the framework will be extended to include monitoring of other Quality of Service properties.

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Towards Proactive Web Service Adaptation

Cited by 11 publications

References 17 publications

Multi-Objective Service Composition in Uncertain Environments

Multi-Objective Service Composition in Uncertain Environments

Towards Dynamic Reconfiguration of a Composite Web Service: An Approach Based on QoS Prediction

Managing Availability of web services in service oriented systems

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