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An automatic subdigraph renovation plan for failure recovery of composite semantic Web services

Frontiers of Computer Science 2013年第6期7卷 894-913页

作者： hadi saboohi Sameem ABDUL KAREEM Department of Artificial Intelligence Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur 50603 Malaysia

A Web service-based system never fulfills a user＇s goal unless a failure recovery approach exists. It is inevitable that several Web services may either perish or fail before or during transactions. The completion of a composite process relies on the smooth execution of all constituent Web services. A mediator acts as an intermediary between providers and consumers to monitor the execution of these services. If a service fails, the mediator has to recover the whole composite process or else jeopardize achieving the intended goals. The atomic replacement of a perished Web service usually does not apply because the process of locating a matched Web service is unreliable. Even the system cannot depend on the replacement of the dead service with a com- posite service. In this paper, we propose an automatic renova- tion plan for failure recovery of composite semantic services based on an approach of subdigraph replacement. A replacement subdigraph is posed in lieu of an original subdigraph, which includes the failed service. The replacement is done in two separate phases, ofltine and online, to make the recovery faster. The ofitine phase foresees all possible subdigraphs, pre-calculates them, and ranks several possible replacements. The online phase compensates the unwanted effects and executes the replacement subdigraph in lieu of the original subdigraph. We have evaluated our approach during an experiment and have found that we could recover more than half of the simulated failures. These achievements show a significant improvement compared to current approaches

关键词： semantic Web service composite services fail- ure recovery subdigraph replacement

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On Density-Based Data Streams Clustering Algorithms: A Survey

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Journal of Computer Science & Technology 2014年第1期29卷 116-141页

作者： Amineh Amini Teh Ying Wah hadi saboohi IEEE Department of Information Systems Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur ACM

Clustering data streams has drawn lots of attention in the last few years due to their ever-growing presence. Data streams put additional challenges on clustering such as limited time and memory and one pass clustering. Furthermore, discovering clusters with arbitrary shapes is very important in data stream applications. Data streams are infinite and evolving over time, and we do not have any knowledge about the number of clusters. In a data stream environment due to various factors, some noise appears occasionally. Density-based method is a remarkable class in clustering data streams, which has the ability to discover arbitrary shape clusters and to detect noise. Furthermore, it does not need the nmnber of clusters in advance. Due to data stream characteristics, the traditional density-based clustering is not applicable. Recently, a lot of density-based clustering algorithms are extended for data streams. The main idea in these algorithms is using density- based methods in the clustering process and at the same time overcoming the constraints, which are put out by data streanFs nature. The purpose of this paper is to shed light on some algorithms in the literature on density-based clustering over data streams. We not only summarize the main density-based clustering algorithms on data streams, discuss their uniqueness and limitations, but also explain how they address the challenges in clustering data streams. Moreover, we investigate the evaluation metrics used in validating cluster quality and measuring algorithms＇ performance. It is hoped that this survey will serve as a steppingstone for researchers studying data streams clustering, particularly density-based algorithms.

关键词： data stream density-based clustering grid-based clustering micro-clustering

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