Dimitrios Skoutas

Selecting skyline services for QoS-based web service composition

Web service composition enables seamless and dynamic integration of business applications on the web. The performance of the composed application is determined by the performance of the involved web services. Therefore, non-functional, quality of service aspects are crucial for selecting the web services to take part in the composition. Identifying the best candidate web services from a set of functionally-equivalent services is a multi-criteria decision making problem. The selected services should optimize the overall QoS of the composed application, while satisfying all the constraints specified by the client on individual QoS parameters. In this paper, we propose an approach based on the notion of skyline to effectively and efficiently select services for composition, reducing the number of candidate services to be considered. We also discuss how a provider can improve its service to become more competitive and increase its potential of being included in composite applications. We evaluate our approach experimentally using both real and synthetically generated datasets.

Ontology-Based Conceptual Design of ETL Processes for Both Structured and Semi-Structured Data

One of the main tasks in the early stages of a data warehouse project is the identification of the appropriate transformations and the specification of inter-schema mappings from the data sources to the data warehouse. In this article, we propose an ontology-based approach to facilitate the conceptual design of the back stage of a data warehouse. A graph-based representation is used as a conceptual model for the datastores, so that both structured and semi-structured data are supported and handled in a uniform way. The proposed approach is based on the use of Semantic Web technologies to semantically annotate the data sources and the data warehouse, so that mappings between them can be inferred, thereby resolving the issue of heterogeneity. Specifically, a suitable application ontology is created and used to annotate the datastores. The language used for describing the ontology is OWL-DL. Based on the provided annotations, a DL reasoner is employed to infer semantic correspondences and conflicts among the datastores, and to propose a set of conceptual operations for transforming data from the source datastores to the data warehouse.

Ranking and Clustering Web Services Using Multicriteria Dominance Relationships

As the web is increasingly used not only to find answers to specific information needs but also to carry out various tasks, enhancing the capabilities of current web search engines with effective and efficient techniques for web service retrieval and selection becomes an important issue. Existing service matchmakers typically determine the relevance between a web service advertisement and a service request by computing an overall score that aggregates individual matching scores among the various parameters in their descriptions. Two main drawbacks characterize such approaches. First, there is no single matching criterion that is optimal for determining the similarity between parameters. Instead, there are numerous approaches ranging from Information Retrieval similarity measures up to semantic logic-based inference rules. Second, the reduction of individual scores to an overall similarity leads to significant information loss. Determining appropriate weights for these intermediate scores requires knowledge of user preferences, which is often not possible or easy to acquire. Instead, using a typical aggregation function, such as the average or the minimum of the degrees of match across the service parameters, introduces undesired bias, which often reduces the accuracy of the retrieval process. Consequently, several services, e.g., those having a single unmatched parameter, may be excluded from the result set, while being potentially good candidates. In this work, we present two complementary approaches that overcome the aforementioned deficiencies. First, we propose a methodology for ranking the relevant services for a given request, introducing objective measures based on dominance relationships defined among the services. Second, we investigate methods for clustering the relevant services in a way that reveals and reflects the different trade-offs between the matched parameters. We demonstrate the effectiveness and the efficiency of our proposed techniques and algorithms through extensive experimental evaluation on both real requests and relevance sets, as well as on synthetic scenarios.

Designing ETL processes using semantic web technologies

One of the most important tasks performed in the early stages of a data warehouse project is the analysis of the structure and content of the existing data sources and their intentional mapping to a common data model. Establishing the appropriate mappings between the attributes of the data sources and the attributes of the data warehouse tables is critical in specifying the required transformations in an ETL workflow. The selected data model should besuitable for facilitating the redefinition and revision efforts, typically occurring during the early phases of a data warehouse project, and serve as the means of communication between the involved parties. In this paper, we argue that ontologies constitute a very suitable model for this purpose and show how the usage of ontologies can enable a high degree of automation regarding the construction of an ETL design.

Efficient task replication and management for adaptive fault tolerance in mobile Grid environments

Fault tolerant Grid computing is of vital importance as the Grid and Mobile computing worlds converge to the Mobile Grid computing paradigm. We present an efficient scheme based on task replication, which utilizes the Weibull reliability function for the Grid resources so as to estimate the number of replicas that are going to be scheduled in order to guarantee a specific fault tolerance level for the Grid environment. The additional workload that is produced by the replication is handled by a resource management scheme which is based on the knapsack formulation and which aims to maximize the utilization and profit of the Grid infrastructure. The proposed model has been evaluated through simulation and has shown its efficiency for being used in a middleware approach in future mobile Grid environments.

A Ranking Mechanism for SemanticWeb Service Discovery

This paper presents an approach for ranking semantic Web service advertisements with respect to a service request. The use of recall and precision is proposed as suitable measures for determining the degree of match between the request and the advertisement. Ranking is based on the use of the domain ontology to infer the semantic similarity between the parameters of the request and the advertisement. The proposed approach is applicable to several types of ontologies, ranging from simple taxonomies to highly expressive ontologies, such as OWL ontologies.

Top- k dominant web services under multi-criteria matching

As we move from a Web of data to a Web of services, enhancing the capabilities of the current Web search engines with effective and efficient techniques for Web services retrieval and selection becomes an important issue. Traditionally, the relevance of a Web service advertisement to a service request is determined by computing an overall score that aggregates individual matching scores among the various parameters in their descriptions. Two drawbacks characterize such approaches. First, there is no single matching criterion that is optimal for determining the similarity between parameters. Instead, there are numerous approaches ranging from using Information Retrieval similarity metrics up to semantic logic-based inference rules. Second, the reduction of individual scores to an overall similarity leads to significant information loss. Since there is no consensus on how to weight these scores, existing methods are typically pessimistic, adopting a worst-case scenario. As a consequence, several services, e.g., those having a single unrelated parameter, can be excluded from the result set, even though they are potentially good alternatives. In this work, we present a methodology that overcomes both deficiencies. Given a request, we introduce an objective measure that assigns a dominance score to each advertised Web service. This score takes into consideration all the available criteria for each parameter in the request. We investigate three distinct definitions of dominance score, and we devise efficient algorithms that retrieve the top-k most dominant Web services in each case. Extensive experimental evaluation on real requests and relevance sets, as well as on synthetically generated scenarios, demonstrates both the effectiveness of the proposed technique and the efficiency of the algorithms.

Efficient Semantic Web Service Discovery in Centralized and P2P Environments

Efficient and scalable discovery mechanisms are critical for enabling service-oriented architectures on the Semantic Web. The majority of currently existing approaches focuses on centralized architectures, and deals with efficiency typically by pre-computing and storing the results of the semantic matcher for all possible query concepts. Such approaches, however, fail to scale with respect to the number of service advertisements and the size of the ontologies involved. On the other hand, this paper presents an efficient and scalable index-based method for Semantic Web service discovery that allows for fast selection of services at query time and is suitable for both centralized and P2P environments. We employ a novel encoding of the service descriptions, allowing the match between a request and an advertisement to be evaluated in constant time, and we index these representations to prune the search space, reducing the number of comparisons required. Given a desired ranking function, the search algorithm can retrieve the top-k matches progressively, i.e., better matches are computed and returned first, thereby further reducing the search engines response time. We also show how this search can be performed efficiently in a suitable structured P2P overlay network. The benefits of the proposed method are demonstrated through experimental evaluation on both real and synthetic data.

Exploiting User Feedback to Improve Semantic Web Service Discovery

State-of-the-art discovery of Semantic Web services is based on hybrid algorithms that combine semantic and syntactic matchmaking. These approaches are purely based on similarity measures between parameters of a service request and available service descriptions, which, however, fail to completely capture the actual functionality of the service or the quality of the results returned by it. On the other hand, with the advent of Web 2.0, active user participation and collaboration has become an increasingly popular trend. Users often rate or group relevant items, thus providing valuable information that can be taken into account to further improve the accuracy of search results. In this paper, we tackle this issue, by proposing a method that combines multiple matching criteria with user feedback to further improve the results of the matchmaker. We extend a previously proposed dominance-based approach for service discovery, and describe how user feedback is incorporated in the matchmaking process. We evaluate the performance of our approach using a publicly available collection of OWL-S services.

Representation of conceptual ETL designs in natural language using Semantic Web technology

Extract-Transform-Load (ETL) processes constitute the back stage of Data Warehouse architectures. Several studies characterize the ETL design as a time-consuming and error-prone procedure. A critical phase in the ETL lifecycle involves the early communications and design steps that aim at producing a conceptual ETL design. Various research approaches have dealt with the conceptual modeling of ETL processes, but all share two inconveniences: they require intensive human effort from the designers to create them, as well as technical knowledge from the business people to understand them. In this paper, we focus on the second aspect and provide a method for the representation of a conceptual ETL design as a narrative, which is the most natural means of communication and does not require particular technical skills or familiarity with any specific model. Specifically, this work builds upon previously proposed techniques that automate the conceptual design by leveraging Semantic Web technology. The key idea is to map the involved data stores, either source or target, to a domain ontology and then, to use a reasoner for producing the ETL design. We discuss how linguistic techniques can be used for the establishment of a common application vocabulary. We present a flexible and customizable template-based mechanism for the representation of the ETL design as a narrative. Finally, we discuss issues related to the production of meaningful reports and we provide implementation details.