Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques

The goal of QoS-aware service composition is to generate optimal composite services that satisfy the QoS requirements defined by clients. However, when compositions contain more than one execution path (i.e., multiple path's compositions), it is difficult to generate a composite service that simultaneously optimizes all the execution paths involved in the composite service at the same time while meeting the QoS requirements. This issue brings us to the challenge of solving the QoS-aware service composition problem, so called an optimization problem. A further research challenge is the determination of the QoS characteristics that can be considered as selection criteria. In this thesis, a smart QoS-aware service composition approach is proposed. The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. This mechanism is performed in two steps. First, the runtime path prediction method predicts, at runtime, and just before the actual composition, execution, the execution path that will potentially be executed. Second, both the constructive procedure (CP) and the complementary procedure (CCP) heuristic algorithms computed the optimization considering only the execution path that has been predicted by the runtime path prediction method for criteria selection, eight QoS characteristics are suggested after investigating related works on the area of web service and web service composition. Furthermore, prioritizing the selected QoS criteria is suggested in order to assist clients when choosing the right criteria. Experiments via WEKA tool and simulation prototype were conducted to evaluate the methods used. For the runtime path prediction method, the results showed that the path prediction method achieved promising prediction accuracy, and the number of paths involved in the prediction did not affect the accuracy. For the optimization mechanism, the evaluation was conducted by comparing the mechanism with relevant optimization techniques. The simulation results showed that the proposed optimization mechanism outperforms the relevant optimization techniques by (1) generating the highest overall QoS ratio solutions, (2) consuming the smallest computation time, and (3) producing the lowest percentage of constraints violated number

AN INNOVATIVE FRAMEWORK FOR AUTO DYNAMIC SELECTION AND COMPOSITION OF WEB SERVICES

With the availability of ample amount of Web Services similar in functionality and varying in Quality of Service (QoS) over the web, it is essentially required to get the best-suited candidate services for the resultant composite service. QoS plays a decisive role in selecting web Services individually and Composite Web Service as a whole. Certainly, composition is one of the key properties of service-orientation to create new as well as advanced level services, by re-using the existing ones. In distributed environments, services having no quality guarantees, adversely affects the composition outcome. To find the best candidate services for the composition, researchers have opted either Users’ feedback or Providers’ published information but none of them have considered both of them together. In our approach, we have taken into consideration both the things (Users’ feedback and Providers’ published information) together in order to find the best candidate web services by cross verifying both of the information to ascertain the quality of the candidate web services. An innovative framework for the composition of web services along with the detailed methodology and algorithm has been discussed in the second half of the paper

Location-aware scalable service composition.

The problem of service composition is the process of assigning resources to services from a pool of available ones in the shortest possible time so that the overall quality of service is maximized. This article provides solutions for the composition problem that takes into account its scalability, services’ locations, and users’ restrictions, which are key for the management of applications using state-of-the-art technologies. The provided solutions use different techniques, including genetic algorithms and heuristics. We provide an extensive experimental evaluation, which shows the pros and cons of each of them, and allows us to characterize the preferred option for each specific problem. Since no solution dominates the others, we propose a decision tree, based on our results, to select the best composition algorithm in each situation.Spanish Government projects TED2021-130666B-I00 and PID2021-125527NB-I00. Funding for open access charge: Universidad de Málaga / CBUA

Privacy-preserved security-conscious framework to enhance web service composition

The emergence of loosely coupled and platform-independent Service-Oriented Computing (SOC) has encouraged the development of large computing infrastructures like the Internet, thus enabling organizations to share information and offer valueadded services tailored to a wide range of user needs. Web Service Composition (WSC) has a pivotal role in realizing the vision of implementing just about any complex business processes. Although service composition assures cost-effective means of integrating applications over the Internet, it remains a significant challenge from various perspectives. Security and privacy are among the barriers preventing a more extensive application of WSC. First, users possess limited prior knowledge of security concepts. Second, WSC is hindered by having to identify the security required to protect critical user information. Therefore, the security available to users is usually not in accordance with their requirements. Moreover, the correlation between user input and orchestration architecture model is neglected in WSC with respect to selecting a high performance composition execution process. The proposed framework provides not only the opportunity to securely select services for use in the composition process but also handles service users’ privacy requirements. All possible user input states are modelled with respect to the extracted user privacy preferences and security requirements. The proposed approach supports the mathematical modelling of centralized and decentralized orchestration regarding service provider privacy and security policies. The output is then utilized to compare and screen the candidate composition routes and to select the most secure composition route based on user requests. The D-optimal design is employed to select the best subset of all possible experiments and optimize the security conscious of privacy-preserving service composition. A Choreography Index Table (CIT) is constructed for selecting a suitable orchestration model for each user input and to recommend the selected model to the choreographed level. Results are promising that indicate the proposed framework can enhance the choreographed level of the Web service composition process in making adequate decisions to respond to user requests in terms of higher security and privacy. Moreover, the results reflect a significant value compared to conventional WSC, and WSC optimality was increased by an average of 50% using the proposed CIT

Semantics-aware planning methodology for automatic web service composition

Service-Oriented Computing (SOC) has been a major research topic in the past years. It is based on the idea of composing distributed applications even in heterogeneous environments by discovering and invoking network-available Web Services to accomplish some complex tasks when no existing service can satisfy the user request. Service-Oriented Architecture (SOA) is a key design principle to facilitate building of these autonomous, platform-independent Web Services. However, in distributed environments, the use of services without considering their underlying semantics, either functional semantics or quality guarantees can negatively affect a composition process by raising intermittent failures or leading to slow performance. More recently, Artificial Intelligence (AI) Planning technologies have been exploited to facilitate the automated composition. But most of the AI planning based algorithms do not scale well when the number of Web Services increases, and there is no guarantee that a solution for a composition problem will be found even if it exists. AI Planning Graph tries to address various limitations in traditional AI planning by providing a unique search space in a directed layered graph. However, the existing AI Planning Graph algorithm only focuses on finding complete solutions without taking account of other services which are not achieving the goals. It will result in the failure of creating such a graph in the case that many services are available, despite most of them being irrelevant to the goals. This dissertation puts forward a concept of building a more intelligent planning mechanism which should be a combination of semantics-aware service selection and a goal-directed planning algorithm. Based on this concept, a new planning system so-called Semantics Enhanced web service Mining (SEwsMining) has been developed. Semantic-aware service selection is achieved by calculating on-demand multi-attributes semantics similarity based on semantic annotations (QWSMO-Lite). The planning algorithm is a substantial revision of the AI GraphPlan algorithm. To reduce the size of planning graph, a bi-directional planning strategy has been developed