Comprehensive quality-aware automated semantic web service composition is an NP-hard problem, where service composition workflows are unknown, and comprehensive quality, i.e., Quality of services (QoS) and Quality of semantic matchmaking (QoSM) are simultaneously optimized. The objective of this problem is to find a solution with optimized or near-optimized overall QoS and QoSM within polynomial time over a service request. In this paper, we proposed novel memetic EDA-based approaches to tackle this problem. The proposed method investigates the effectiveness of several neighborhood structures of composite services by proposing domain-dependent local search operators. Apart from that, a joint strategy of the local search procedure is proposed to integrate with a modified EDA to reduce the overall computation time of our memetic approach. To better demonstrate the effectiveness and scalability of our approach, we create a more challenging, augmented version of the service composition benchmark based on WSC-08 bansal2008wsc and WSC-09 kona2009wsc . Experimental results on this benchmark show that one of our proposed memetic EDA-based approach (i.e., MEEDA-LOP) significantly outperforms existing state-of-the-art algorithms.
In the second category, service composition solutions are represented as permutations, which are then decoded into solutions represented as DAGs @cite_20 @cite_37 @cite_24 . PSO is utilized to find an optimized queue of services (i.e., a permutation), which can be decoded into a corresponding DAG-based composite service @cite_24 . @cite_20 extends @cite_24 to jointly optimize QoSM and QoS, where a weighted DAG is decoded, where edge weights correspond to matchmaking quality between services. These two PSO-based approaches rely on PSO to determine the weights of particle's position (that corresponding with a service) to form an ordered service queue. Optimizing QoSM and QoS simultaneously is more challenging than optimizing QoS only because the searching space has significantly increased, and it demands more effective and efficient searching techniques. Apart from that, it has been suggested that utilizing the indirect representation often contributes to a higher performance, compared to direct representation @cite_37 . It is due to that the search space is not unwittingly restricted by unconstrained random initialization of solutions and operators.
@cite_24 @cite_37 @cite_20
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Web services have become increasingly popular in recent years, and they are especially suitable to the process of Web service composition, which is when several services are combined to create an application that accomplishes a more complex task. In recent years, significant research efforts have been made on developing approaches for performing Quality of Service -aware Web service composition. Evolutionary computing (EC) techniques have been widely used for solving this problem, since they allow for the quality of compositions to be optimised, meanwhile also ensuring that the solutions produced have the required functionality. Existing EC-based composition approaches perform constrained optimisation to produce solutions that meet those requirements, however these constraints may hinder the effectiveness of the search. To address this issue, a novel framework based on an indirect representation is proposed in this work. The core idea is to first generate candidate service compositions encoded as sequences of services. Then, a decoding scheme is developed to transform any sequence of services into a corresponding feasible service composition. Given a service sequence, the decoding scheme builds the workflow from scratch by iteratively adding the services to proper positions of the workflow in the order of the sequence. This is beneficial because it allows the optimisation to be carried out in an unconstrained way, later enforcing functionality constraints during the decoding process. A number of encoding methods and corresponding search operators, including the PSO, GA, and GP-based methods, are proposed and tested, with results showing that the quality of the solutions produced by the proposed indirect approach is higher than that of a baseline direct representation-based approach for twelve out of the thirteen datasets considered. In particular, the method using the variable-length sequence representation has the most efficient execution time, while the fixed-length sequence produces the highest quality solutions. Automated Web service composition, which refers to the creation of a complex application from pre-existing building blocks (Web services), has been an active research topic in the past years. The advantage of having an automated composition system is that it allows users to create new applications simply by providing the required parameters, instead of having to manually assemble the services. Existing approaches to automated composition rely on planning techniques or evolutionary computing (EC) to modify and optimise composition solutions directly in their tree graph form, a complex process that requires several constraints to be considered before each alteration. To improve the search efficiency and simplify the checking of constraints, this work proposes an indirect Particle Swarm Optimisation (PSO)-based approach. The key idea of the indirect approach is to optimise a service queue which is then decoded into a composition solution by using a planning algorithm. This approach is compared to a previously proposed graph-based direct representation method, and experiment results show that the indirect representation can lead to a greater (or equivalent) quality while requiring a lower execution time. The analysis conducted shows that this is due to the design of the algorithms used for building and evaluating the fitness of solutions. Web service composition has been a prevailing research direction in recent years. There are two major challenges faced by researchers, semantic matchmaking and Quality of Service (QoS) optimisation. Semantic matchmaking aims to discover interoperable web services that can interact with each other by their resources described semantically. QoS optimisation aims to optimise the non-functional requirements of service users, such as minimum cost and maximum reliability. To meet the requirements of service users, both semantic matchmaking quality and QoS should be considered simultaneously. Most existing works on web service composition, however, focus only on one of these two aspects. Therefore, we propose a comprehensive quality model that takes both semantic matchmaking quality and QoS into account with the aim of achieving a more desirable balance of both sides. Further, we develop a PSO-based service composition approach with explicit support for the proposed comprehensive quality model. We also conduct experiments to explore the effectiveness of our PSO-based approach and the desirable balance achieved by using our comprehensive quality model. Abstract Documents in computer-readable form can be used to provide information about other documents, i.e. those they cite. To do this efficiently requires procedures for computer recognition of citing statements. This is not easy, especially for multi-sentence citing statements. Computer recognition procedures have been developed which are accurate to the following extent: 73 of the words in statements selected by computer procedures as being citing statements are words which are correctly attributable to the corresponding documents. The retrieval effectiveness of computer-recognized citing statements was tested in the following way. First, for eight retrieval requests in inorganiic chemistry, average recall by search of Chemical Abstracts Service indexing and Chemical Abstracts abstract text words was found to be 50 . Words from citing statements referring to the papers to be retrieved were then added to the index terms and abstract words as additional access points, and searching was repeated. Average recall increased to 70 . Only words from citing statements published within a year of the cited papers were used. The retrieval effect of citing statement words alone (published within a year) without index or abstract terms was the following: average recall was 40 . When just the words of the titles of the cited papers were added to those citing statement words, average recall increased to 50 . In recent years, quite a few search algorithms have been used to solve Web service composition problem. However, it is still lack of systematic analysis about these methods. In the paper, we attempt to analyze the effect of three typical meta-heuristic search algorithms. The experimental analysis is performed according to the search-based Web service composition framework. In the experiments, we mainly carry out the analysis as follows: different abstract service number, different candidate service number and different QoS constraint strength. Based on the above analysis, some guidelines of realizing Web service composition via search algorithms are yielded. For example, EDA is suitable for the composition problem with large abstract service number. PSO is more effective for the case of large candidate service number. GA is a good choose for the little-scale Web service composition problem. In addition, EDA can effectively settle the composition problem with strong QoS constraint. GA is suitable for the problem with medium constraint strength, and PSO has the poor ability to tackle the QoS constraint with high strength. The machine learning provides a theoretical and methodological framework to quantify the relationship between user OoE (Quality of Experience) and network QoS (Quality of Service). This paper presents an overview of QoE-QoS correlation models based on machine learning techniques. According to the learning type, we propose a categorization of correlation models. For each category, we review the main existing works by citing deployed learning methods and model parameters (QoE measurement, QoS parameters and service type). Moreover, the survey will provide researchers with the latest trends and findings in this field. Many enterprises have a growing interest in service composition to construct their business applications. With the increase of alternative services, Quality of Service (QoS) becomes an important indicator of obtaining optimal composite services. Due to the dynamic nature of the service environment, a composite service may not guarantee to deliver an overall optimal QoS. Re-optimization approaches have been developed to handle a dynamic environment. However, these approaches do not consider the diversity of alternative solutions, which may lead to better solutions. In this work, we introduce an adaptive approach, called estimation of distribution algorithm based on Restricted Boltzmann Machine (rEDA). rEDA effectively maintains the diversity of alternative solutions, by leveraging the inference ability of Restricted Boltzmann Machine to capture the potential solutions. It also provides a predictive guidance for the exploration of solution space, by considering the degree of how well a service contributes to the global QoS. The experimental evaluation shows that rEDA has a significant improvement on effectiveness and efficiency over existing approaches. Service-Oriented Architecture enables the composition of loosely coupled services provided with varying Quality of Service (QoS) levels. Given a composition, finding the set of services that optimizes some QoS attributes under given QoS constraints has been shown to be NP-hard. Therefore, heuristic algorithms are widely used, finding acceptable solutions in polynomial time. Still the time complexity of such algorithms can be prohibitive for real-time use, especially if the algorithms are required to run until they find near-optimal solutions. Thus, we propose a heuristic approach based on Hill-Climbing that makes effective use of an initial bias computed with Linear Programming, and works on a reduced search space. In our evaluation, we show that our approach finds near-optimal solutions and achieves a low time complexity. Motivated by the fact that most of the existing QoS service composition solutions have limited scalability, we develop a hierarchical-based solution framework to achieve scalability by means of topology abstraction and routing state aggregation. The paper presents and solves several unique challenges associated with the hierarchical-based QoS service composition solution in overlay networks, including topology formation (cluster detection and dynamic reclustering), QoS and service state aggregation and distribution, and QoS service path computation in a hierarchically structured network topology. In our framework, we (1) cluster network nodes based on their Internet distances and maintain clustering optimality at low cost by means of local reclustering operations when dealing with dynamic membership; (2) use data clustering and Bloom filter techniques to jointly reduce complexity of data representation associated with services within a cluster; and (3) investigate a top-down approach for computing QoS service paths in a hierarchical topology. The run-time binding of web services has been recently put forward in order to support rapid and dynamic web service compositions. With the growing number of alternative web services that provide the same functionality but differ in quality parameters, the service composition becomes a decision problem on which component services should be selected such that user's end-to-end QoS requirements (e.g. availability, response time) and preferences (e.g. price) are satisfied. Although very efficient, local selection strategy fails short in handling global QoS requirements. Solutions based on global optimization, on the other hand, can handle global constraints, but their poor performance renders them inappropriate for applications with dynamic and real-time requirements. In this paper we address this problem and propose a solution that combines global optimization with local selection techniques to benefit from the advantages of both worlds. The proposed solution consists of two steps: first, we use mixed integer programming (MIP) to find the optimal decomposition of global QoS constraints into local constraints. Second, we use distributed local selection to find the best web services that satisfy these local constraints. The results of experimental evaluation indicate that our approach significantly outperforms existing solutions in terms of computation time while achieving close-to-optimal results. Next generation networks are envisioned to support dynamic and customizable service compositions at Internet scale. To facilitate the communication between distributed software components, on-demand and QoS-aware network service composition across large scale networks emerges as a key research challenge. This paper presents a fast QoS-aware service composition algorithm for selecting a set of interconnected domains with specific service classes. We further show how such algorithm can be used to support network adaptation and service mobility. In simulation studies performed on large scale networks, the algorithm exhibits very high probability of finding the optimal solution within short execution time. In addition, we present a distributed service composition framework utilizing this algorithm. Scholars are increasingly citing electronic “web references” which are not preserved in libraries or full text archives. WebCite is a new standard for citing web references. To “webcite” a document involves archiving the cited Web page through www.webcitation.org and citing the WebCite permalink instead of (or in addition to) the unstable live Web page. This journal has amended its “instructions for authors” accordingly, asking authors to archive cited Web pages before submitting a manuscript. Almost 200 other journals are already using the system. We discuss the rationale for WebCite, its technology, and how scholars, editors, and publishers can benefit from the service. Citing scholars initiate an archiving process of all cited Web references, ideally before they submit a manuscript. Authors of online documents and websites which are expected to be cited by others can ensure that their work is permanently available by creating an archived copy using WebCite and providing the citation information including the WebCite link on their Web document(s). Editors should ask their authors to cache all cited Web addresses (Uniform Resource Locators, or URLs) “prospectively” before submitting their manuscripts to their journal. Editors and publishers should also instruct their copyeditors to cache cited Web material if the author has not done so already. Finally, WebCite can process publisher submitted “citing articles” (submitted for example as eXtensible Markup Language [XML] documents) to automatically archive all cited Web pages shortly before or on publication. Finally, WebCite can act as a focussed crawler, caching retrospectively references of already published articles. Copyright issues are addressed by honouring respective Internet standards (robot exclusion files, no-cache and no-archive tags). Long-term preservation is ensured by agreements with libraries and digital preservation organizations. The resulting WebCite Index may also have applications for research assessment exercises, being able to measure the impact of Web services and published Web documents through access and Web citation metrics. @PARASPLIT [J Med Internet Res 2005;7(5):e60] Services in cloud computing can be categorized into two groups: Application services and Utility Computing Services. Compositions in the application level are similar to the Web service compositions in SOC (Service-Oriented Computing). Compositions in the utility level are similar to the task matching and scheduling in grid computing. Contributions of this paper include: 1) An extensible QoS model is proposed to calculate the QoS values of services in cloud computing. 2) A genetic-algorithm-based approach is proposed to compose services in cloud computing. 3) A comparison is presented between the proposed approach and other algorithms, i.e., exhaustive search algorithms and random selection algorithms. Service-Oriented Computing (SOC) enables the composition of loosely coupled services provided with varying Quality of Service (QoS) levels. Selecting a (near-)optimal set of services for a composition in terms of QoS is crucial when many functionally equivalent services are available. With the advent of Cloud Computing, both the number of such services and their distribution across the network are rising rapidly, increasing the impact of the network on the QoS of such compositions. Despite this, current approaches do not differentiate between the QoS of services themselves and the QoS of the network. Therefore, the computed latency differs substantially from the actual latency, resulting in suboptimal QoS for service compositions in the cloud. Thus, we propose a network-aware approach that handles the QoS of services and the QoS of the network independently. First, we build a network model in order to estimate the network latency between arbitrary services and potential users. Our selection algorithm then leverages this model to find compositions that will result in a low latency given an employed execution policy. In our evaluation, we show that our approach efficiently computes compositions with much lower latency than current approaches. Service Oriented Architectures allow service brokers to execute business processes composed of network-accessible loosely-coupled services offered by a multitude of service providers, at different Quality of Service (QoS) and cost levels. To optimize their revenue and the offered QoS level, service brokers need to solve the problem of finding the set of service providers that minimizes the total execution time of the business process subject to cost and execution time constraints. This optimization problem is clearly NP-hard. Optimized algorithms that find the optimal solution without having to explore the entire solution space have been proposed to solve problems of moderate size. A heuristic search of the sub-optimal solution scales to problems of large size and is appropriate for runtime service selection. This paper evaluates the performance of three heuristic service selection algorithms that are candidates for implementation in scalable service brokers. Our goal is to identify which algorithm provides the solution closest to the optimal and how many selections are evaluated to find the solution. The comparison is made over a wide range of parameters including the complexity of the business process topology and the the tightness of the QoS and cost constraints. A new form of document coupling called co-citation is defined as the frequency with which two documents are cited together. The co-citation frequency of two scientific papers can be determined by comparing lists of citing documents in the Science Citation Index and counting identical entries. Networks of co-cited papers can be generated for specific scientific specialties, and an example is drawn from the literature of particle physics. Co-citation patterns are found to differ significantly from bibliographic coupling patterns, but to agree generally with patterns of direct citation. Clusters of co-cited papers provide a new way to study the specialty structure of science. They may provide a new approach to indexing and to the creation of SDI profiles. Run-time service discovery and late-binding constitute some of the most challenging issues of service-oriented software engineering. For late-binding to be effective in the case of composite services, a QoS-aware composition mechanism is needed. This means determining the set of services that, once composed, not only will perform the required functionality, but also will best contribute to achieve the level of QoS promised in service level agreements (SLAs). However, QoS-aware composition relies on estimated QoS values and workflow execution paths previously obtained using a monitoring mechanism. At run-time, the actual QoS values may deviate from the estimations, or the execution path may not be the one foreseen. These changes could increase the risk of breaking SLAs and obtaining a poor QoS. Such a risk could be avoided by replanning the service bindings of the workflow slice still to be executed. This paper proposes an approach to trigger and perform composite service replanning during execution. An evaluation has been performed simulating execution and replanning on a set of composite service workflows. We extend the service abstraction in the Open Grid Services Architecture ogsa for Quality of Service (QoS) properties. The realization of QoS often requires mechanisms such as advance or on-demand reservation of resources, varying in type and implementation, and independently controlled and monitored. propose the GARA FostKessl99 architecture. The GARA library provides a restricted representation scheme for encoding resource properties and the associated monitoring of Service Level Agreements (SLAs). Our focus is on the application layer, whereby a given service may indicate the QoS properties it can offer, or where a service may search for other services based on particular QoS properties. In recent times, automated business processes and web services have become ubiquitous in diverse application spaces. Efficient composition of web services in real time while providing necessary QoS guarantees is a computationally complex problem and several heuristic based approaches have been proposed to compose services optimally. In this paper, we present the design of a scalable but approximate QoS-aware service composition mechanism which balances the computational complexity of service composition with the QoS guarantees of the composed service and achieves scalability for dynamic service composition. We present experimental results to show the efficiency of our proposed mechanism. Web service composition has become a promising technique to build powerful business applications by making use of distributed services with different functions. Due to the explosion in the volume of data, providing efficient approaches to composing data intensive services will become more and more important in the field of service-oriented computing. Meanwhile, as numerous web services have been emerging to offer identical or similar functionality, web service composition is usually performed with end-to-end Quality of Service QoS properties which are adopted to describe the non-functional properties e.g., response time, execution cost, reliability, etc. of a web service. In this paper, a hybrid approach that integrates the use of genetic programming and tabu search to QoS-aware data intensive service composition is proposed. The performance of the proposed approach is evaluated using the publicly available benchmark datasets. A full set of experimental results show that a significant improvement of our approach over that obtained by the simple genetic programming method and several traditional optimization methods, has been achieved.