Mobile, pervasive computing environments respond to users’ requirements by providing access to and composition of various services over networked devices. In such an environment, service composition needs to satisfy a request’s goal, and be mobile-aware even throughout service discovery and service execution. A composite service also needs to be adaptable to cope with the environment’s dynamic network topology. Existing composition solutions employ goal-oriented planning to provide flexible composition, and assign service providers at runtime, to avoid composition failure. However, these solutions have limited support for complex service flows and composite service adaptation. This paper proposes a self-organizing, goal-driven service model for task resolution and execution in mobile pervasive environments. In particular, it proposes a decentralized heuristic planning algorithm based on backward-chaining to support flexible service discovery. Further, we introduce an adaptation architecture that allows execution paths to dynamically adapt, which reduces failures, and lessens re-execution effort for failure recovery. Simulation results show the suitability of the proposed mechanism in pervasive computing environments where providers are mobile, and it is uncertain what services are available. Our evaluation additionally reveals the model’s limits with regard to network dynamism and resource constraints.

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Goal-Driven Service Composition in Mobile and Pervasive Computing

In today's economy, collaboration and co-development among organizations has evolved from the traditional format of static supply chains to the dynamic formation of federated organization networks. Networking among business partners has proven to yield lower costs, higher quality, larger service/product portfolio, faster delivery, and more agility. However, the pace by which these trend changes need to occur has raised the demand on ICT-enhanced support for inter-organization collaboration, establishing the area of collaborative networks (CNs). We particularly address in our research two forms of CNs, namely the VO (Virtual Organization) and the VBE (VO Breeding Environment). To enrich collaboration among potentially distributed partners, a challenging area for CN research is focused on new approaches to specification, sharing and integration of organizations business processes. Aiming to address this challenge, in our research the promising paradigm of Service Oriented Architecture (SOA) is investigated and applied as the base for enhancement of organizations collaboration. However, we argue that the current implementations of the SOA approach do not sufficiently support CN requirements and do not deliver the expected advantages for organizations sharing and integrating their business services. We therefore introduce a new reference framework - the service orientated collaborative networks (SOCN), as a customization of the traditional architecture and generic model of SOA, in order to efficiently support service oriented CNs.

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Enabling framework for service-oriented collaborative networks

Purpose




Web services play vital role in the development of emerging technologies such as Cloud computing and Internet of Things. Although, there is a close relationship among the discovery, selection and composition tasks of Web services, research community has treated these challenges at individual level rather to focus on them collectively for developing efficient solution, which is the purpose of this work. This paper aims to propose an approach to integrate the service discovery, selection and composition of Semantic Web services on runtime basis.




Design/methodology/approach




The proposed approach defined as a quality of service (QoS)-aware approach is based on QoS model to perform discovery, selection and composition tasks at runtime to enhance the user satisfaction and quality guarantee by incorporating non-functional parameters such as response time and throughput with the Web services and user request. In this paper, the proposed approach is based on ontology for semantic description of Web services, which provides interoperability and automation in the Web services tasks.




Findings




This work proposed an integrated framework of Web service discovery, selection and composition which supports end user to search, select and compose the Web services at runtime using semantic description and non-functional requirements. The proposed approach is evaluated by various data sets from the Web Service Challenge 2009 (WSC-2009) to show the efficiency of this work. A use case scenario of Healthcare Information System is implemented using proposed work to demonstrate the usability and requirement the proposed approach.




Originality/value




The main contribution of this paper is to develop an integrated approach of Semantic Web services discovery, selection and composition by using the non-functional requirements.

A QoS-aware approach for runtime discovery, selection and composition of semantic web services

Web mining is the application of data mining techniques to discover the user interesting patterns from the web server. The behaviors of web users are monitored for services composition from a similar set of services accessed by the user. Various mining techniques have been developed for mining user interesting patterns but still discovering the most interesting patterns with less time complexity is a major research area. In order to extract the interesting actionable patterns with less time complexity, Best First Decision Tree Based Extreme Gradient Boost Classification (BFDT-XGBC) technique is introduced. At first, the user accessed patterns are extracted from the server log. Then, the base learner called Best First Decision Tree is employed to identify user interesting web patterns. In a decision tree, the first node is selected through the information gain to make a decision for classifying the web patterns. The classification is performed based on the correlation between the two web patterns. The Pearson correlation coefficient is used for measuring the correlation between web patterns and it provides the results as positive and negative correlation. Based on the positive correlation measure, the web patterns are classified through the node in a best first decision tree. The output of each best first decision tree is taken as base learners. Then the several base learners are combined to provide strong classification results by applying Extreme Gradient Boost Classification in BFDT-XGBC technique. Extreme Gradient Boost classifier is employed to compute the loss function of all base learners for constructing the strong classifier. Thus the similar user interesting patterns are correctly identified with higher accuracy and minimal time. Experimental evaluation of proposed BFDT-XGBC technique and existing methods are carried out with the web server log files. The results reported that the BFDT-XGBC technique effectively discoverered the web user interesting patterns through Web pattern identification accuracy, computational time, false positive rate and space complexity. Based on the result observations, BFDT-XGBC technique is more efficient than the existing methods.

Extreme Gradient Boost Classification Based Interesting User Patterns Discovery for Web Service Composition

Cloud Computing has drawn much attention in industry due its efficient cost schema along with more prospects such as elasticity and scalability nature of Cloud Computing. One of the main service model of Cloud is Software as Service, where many Web services are published and hosted in Cloud. Many Web Services in Cloud offers the same functionality but with different Quality of Service (QoS). In addition, as individual web services are limited in their capability, which created the need for composing more than web service to create new functionality in the form of composite service to fulfill the requirement Cloud Consumer certain process. Therefore, a model is proposed to compose web services using fuzzy rule, where the selection of composed web services from Cloud based on QoS that fulfill user requirements and its constraints. Moreover, the proposed model is provided with module that is responsible for monitoring the execution of composed service in case of one the composed service become unavailable, the agent will replace the unavailable service with new service that match user requirements and the generated fuzzy rules and will come up with new composition plan.

Fuzzy rule based web service composition in cloud

Web service has become the technology of choice for service oriented computing to meet the interoperability demands in web applications. In the Internet era, the exponential addition of web services nominates the "quality of service" as essential parameter in discriminating the web services. In this paper, a user preference based web service ranking (UPWSR) algorithm is proposed to rank web services based on user preferences and QoS aspect of the web service. When the user's request cannot be fulfilled by a single atomic service, several existing services should be composed and delivered as a composition. The proposed framework allows the user to specify the local and global constraints for composite web services which improves flexibility. UPWSR algorithm identifies best fit services for each task in the user request and, by choosing the number of candidate services for each task, reduces the time to generate the composition plans. To tackle the problem of web service composition, QoS aware automatic web service composition (QAWSC) algorithm proposed in this paper is based on the QoS aspects of the web services and user preferences. The proposed framework allows user to provide feedback about the composite service which improves the reputation of the services.

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Suganya Viswanathan

Papers

An Automatic Web Service Composition Framework Using QoS-Based Web Service Ranking Algorithm