Ivana Ognjanovic, B. Mohabbati, D. Gašević, E. Bagheri, Marko Boskovic
{"title":"A Metaheuristic Approach for the Configuration of Business Process Families","authors":"Ivana Ognjanovic, B. Mohabbati, D. Gašević, E. Bagheri, Marko Boskovic","doi":"10.1109/SCC.2012.6","DOIUrl":"https://doi.org/10.1109/SCC.2012.6","url":null,"abstract":"Business process families provide an over-arching representation of the possible business processes of a target domain. They are defined by capturing the similarities and differences among the possible business processes of the target domain. To realize a business process family into a concrete business process model, the variability points of the business process family need to be bounded. The decision on how to bind these variation points boils down to the stakeholders' requirements and needs. Given specific requirements from the stakeholders, the business process family can be configured. This paper formally introduces and empirically evaluates a framework called ConfBPFM that utilizes standard techniques for identifying stakeholders' quality requirements and employs a metaheuristic search algorithm (i.e., Genetic Algorithms) to optimally configure a business process family.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129744152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Open Challenges for Consulting Service Lifecycle Management: What Service Research Should learn from Software Lifecycle Management","authors":"P. Mazzoleni, R. Goodwin, Clay E. Williams","doi":"10.1109/SCC.2012.111","DOIUrl":"https://doi.org/10.1109/SCC.2012.111","url":null,"abstract":"In the last two decades, research in software engineering has hada focus on software lifecycle management. Rather than a narrowfocus on programming languages environments and softwaredevelopment, researchers are considering the end-to-end lifecycleof software, including design, development, deployment, supportand retirement. Business IT consulting has a similar lifecyclefrom request for proposal, to proposal, delivery, on-goingoperation and retirement. For the past 5 years we have beenworking with IBM Global Business Services to address issues indelivering Business IT services. From this experience, we'veidentified a number of open challenges and have begun workingon solutions and a platform for addressing these challenges. Weare starting with lessons learned in software lifecyclemanagement, and building on them to address challengesparticular to service delivery. For example, like softwarelifecycle management, services lifecycle management requiressupport for end-to-end traceability, coordination between peopleworking on related activities and on hand offs between one phaseof a consulting project and the next. In this paper, we enumeratea set of open challenges for service lifecycle management. Wesuggest how lessons from software lifecycle management can beapplied and give a preliminary report on our implementation ofan open architecture environment to support services lifecycle management.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129773511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"High Performance Computing as a Service with Service Level Agreements","authors":"Roland Kübert, S. Wesner","doi":"10.1109/SCC.2012.43","DOIUrl":"https://doi.org/10.1109/SCC.2012.43","url":null,"abstract":"Cloud computing has been gaining popularity for quite some time in various areas, on the infrastructure, platform and application level. Recently, the possibility to provide high performance computing (HPC) as a service has been investigated in conjunction with the cloud computing paradigm. While this is a viable solution for applications that do not require HPC in the truest sense -- with supercomputers which offer paramount performance regarding computation, network interconnect and storage -- there are HPC applications which cannot be realized in this way. HPC as a service can be offered for these applications as well, but it requires a different approach than the usage of cloud computing. The enhancement of mostly best effort based HPC with long-term service level agreements (SLAs) is a potential solution. HPC providers then need not only to decide on which service levels to offer but need to closely investigate the framework conditions for these service levels. The scheduling of these service levels is a difficult task and we simulate a proposed algorithm for providing guarantees on waiting times and the implications on other jobs. We investigate the influence of setting a maximum allowed job size on prioritized jobs and conclude that it makes sense to restrict this size for both clients and provider.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129414405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Selecting Skyline Web Services from Uncertain QoS","authors":"Karim Benouaret, D. Benslimane, A. Hadjali","doi":"10.1109/SCC.2012.84","DOIUrl":"https://doi.org/10.1109/SCC.2012.84","url":null,"abstract":"Quality of service (QoS) has been considered as a significant criterion for selecting among functionally similar Web services. Recent approaches focus on computing the skyline over a set of QoS attributes. This can completely free users from assigning weights to QoS attributes. However, these approaches are not sufficient in a dynamic Web service environment where the delivered QoS by a Web service is inherently uncertain. In this paper, we tackle the problem of skyline on uncertain QoS. We represent each QoS attribute of a Web service using a possibility distribution and introduce two skyline extensions on uncertain QoS called pos-dominant skyline and nec-dominant skyline. We then develop appropriate algorithms to efficiently compute both the pos-dominant skyline and nec-dominant skyline. Finally, we present our experimental results that show both the effectiveness of the introduced skyline extensions and the efficiency of the proposed algorithms.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128636169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On Graph Reduction for QoS Prediction of Very Large Web Service Compositions","authors":"A. Goldman, Yanik Ngoko","doi":"10.1109/SCC.2012.21","DOIUrl":"https://doi.org/10.1109/SCC.2012.21","url":null,"abstract":"In this paper, we investigate the question of QoS prediction of Web Service Composition (WSC) implementing a business process. We focus on the graph reduction technique and the prediction of the Service Response Time. In the graph reduction technique, we assume that a Web Service Composition can be represented as a graph. The main thesis is that the QoS of such a graph graph can be obtained from a composition of the ones of its nodes. Multiple graph reduction algorithms have been proposed in the literature. Our contribution is twofold. We propose first a fast algorithm based on graph reduction for the prediction of the Service Response Time of a Web Service Composition. In comparison to those existing in the literature, this algorithm uses less memory space and has a better time complexity. The obtained improvements are in particular significant on very large Web Service Composition where the number of services is huge. Our second contribution is an analysis of the graph reduction technique for QoS prediction that takes into account the unfolding of services. In such cases, we show that the prediction of QoS can lead to a NP-complete problem. We also provide an integer programming model for predicting the Service Response Time in this case.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121839535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Keletso J. Letsholo, Erol-Valeriu Chioasca, Liping Zhao
{"title":"An Integration Framework for Multi-perspective Business Process Modeling","authors":"Keletso J. Letsholo, Erol-Valeriu Chioasca, Liping Zhao","doi":"10.1109/SCC.2012.29","DOIUrl":"https://doi.org/10.1109/SCC.2012.29","url":null,"abstract":"In their current scope, existing business process modeling methods and techniques lack comprehensive constructs for representing some of the essential business concepts, including business goals, non-functional requirements and resources. Chances are, there will never be a single technique that adequately captures all the business concepts on a single diagram. This paper has two related purposes: First, it evaluates the modeling capabilities of process modeling techniques against the Zachman Framework. Second, it proposes a multi-perspective integration framework for bridging the identified gaps using other requirements modeling techniques such as goal-oriented and data-oriented techniques. A real world case study is then used to demonstrate the integration process. Ultimately, our framework aims at supporting the creation of comprehensive models and facilitating a common understanding of business perspectives regardless of how they are represented.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122023107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yohei Murakami, Masahiro Tanaka, Arif Bramantoro, K. Zettsu
{"title":"Data-Centered Service Composition for Information Analysis","authors":"Yohei Murakami, Masahiro Tanaka, Arif Bramantoro, K. Zettsu","doi":"10.1109/SCC.2012.88","DOIUrl":"https://doi.org/10.1109/SCC.2012.88","url":null,"abstract":"In e-Science, many scientific workflow management systems have been developed to integrate distributed computation resources, data sets, and mining algorithms. Users usually modify and rerun a workflow while repeating procedures: preprocess of data, selection of features, modification of data, selection of mining algorithms, generation of models, and evaluation of the models. These procedures are continued until the domain knowledge is acquired. However, as the size of the data increases, the execution time of the workflow becomes longer and longer, which drives up the cost of rerunning the modified workflow. As a result, it becomes hard to quickly obtain the analysis result. In this research, we avoided the rerun of the workflow by storing service invocation results on a platform and realized data-centered service composition by adding and deleting rules to be fired. To validate the effectiveness of our proposed platform, we created two rule-based services to analyze real-time data: stream message data and sensing data.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116114112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meng Zhang, Xudong Liu, Richong Zhang, Hailong Sun
{"title":"A Web Service Recommendation Approach Based on QoS Prediction Using Fuzzy Clustering","authors":"Meng Zhang, Xudong Liu, Richong Zhang, Hailong Sun","doi":"10.1109/SCC.2012.24","DOIUrl":"https://doi.org/10.1109/SCC.2012.24","url":null,"abstract":"Web services, as loosely-coupled software systems, are increasingly being published to the web and there are a large number of services with similar functions. Therefore, service users compare the non-functional properties of services, e.g., Quality of Service (QoS), when they make service selection. This paper aims at generating a more comprehensive web service recommendation to users with a novel approach to fulfill more accurate prediction of unknown services' QoS values. We accomplish the QoS prediction by using fuzzy clustering method with calculating the users' similarity. Our approach improves the prediction accuracy and this is confirmed by comparing experiments with other methods. In addition, the quality of web services is considered as a multi-dimensional object, and each dimension is one aspect of the web service's non-functional properties. We also provide an application example to demonstrate how to utilize our approach to rank services by a score function and map multi-dimensional QoS properties into a single dimensional value.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126686636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yu Xu, Jianxun Liu, Mingdong Tang, Buqing Cao, Xiaoqing Frank Liu
{"title":"An Efficient Search Strategy for Service Provider Selection in Complex Social Networks","authors":"Yu Xu, Jianxun Liu, Mingdong Tang, Buqing Cao, Xiaoqing Frank Liu","doi":"10.1109/SCC.2012.31","DOIUrl":"https://doi.org/10.1109/SCC.2012.31","url":null,"abstract":"The trustworthiness of service providers plays an important role when a consumer selects a service. This paper studies the problem of how to efficiently search and select trustworthy service providers for users in social networks consisting of service providers and consumers. A trust value between two participants can be derived by existing methods from the optimal trust path between them in a social network. When more than one trust factors are taken into consideration, the exact optimal trust path selection algorithm is NP-complete. Although several heuristic algorithms have been proposed to find approximate solutions, their time complexities are still too high to be acceptable in practice, especially when they are used in very large scale social networks. Focusing on reducing trust path searching time, this paper proposes an efficient preprocessing-based search strategy. It exploits structural properties of the social networks and builds an advanced data structure from preprocessing, which can be used to simplify and accelerate the trust path searching. Experimental results show our strategy is very efficient and nearly achieves a constant time complexity. The computed trustworthiness based on our method has excellent performance close to that of the best existing heuristic algorithm.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120958707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jinhui Yao, Wei Tan, S. Nepal, Shiping Chen, Jia Zhang, D. D. Roure, C. Goble
{"title":"ReputationNet: A Reputation Engine to Enhance ServiceMap by Recommending Trusted Services","authors":"Jinhui Yao, Wei Tan, S. Nepal, Shiping Chen, Jia Zhang, D. D. Roure, C. Goble","doi":"10.1109/SCC.2012.73","DOIUrl":"https://doi.org/10.1109/SCC.2012.73","url":null,"abstract":"The concept of Service Oriented Architecture (SOA) enables flexible and dynamic collaborations among different service providers. Backed up by SOA, scientific workflows can bring together various scientific computing tools and resources all offered as services to answer complex research questions. However, studies conducted on my Experiment show that although the sharing of service-based capabilities opens a gateway to resource reuse, in practice, the degree of reuse is very low. This motivates us to propose ServiceMap to provide navigation support through the network of services in building scientific workflows. In this paper, we propose an extension of ServiceMap, i.e., ReputationNet that incorporates the reputation of services/workflows and their publishers to reinforce its capability in terms of service and workflow recommendations. We develop a novel model of the reputation aspects of the services/workflows, and we propose heuristic algorithms to provide service recommendations based on reputations. Experiments have been conducted with workflows on my Experiment to evaluate the effectiveness and validity of the ReputationNet approach for service recommendations.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127711897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}