Database Management Systems (DBMSs) are an integral part of many applications. Web-based applications, such as e-commerce sites, are faced with highly variable workloads. The number of customers browsing and purchasing items varies throughout the day and business managers can further complicate the workload by requesting complex reports on sales data. This means the load on a database system can fluctuate dramatically with a sudden influx of requests or a request involving a complex query. If there are too many requests operating in the DBMS concurrently, then resources are strained and performance drops. To keep the DBMS’s performance consistent across varying loads, a load control system can be used. This thesis investigates the concept of a load control system based on regulating individual resource usage in a predictive manner. For the purpose of this proof-of- concept study, we focus on a specific resource; namely, the sort heap. A method of estimating sort heap usage based on the query execution plan is presented and several scheduling methods based on these estimations are proposed. A prototype load control system is used to evaluate and compare the scheduling methods. Experiments show that it is possible to both estimate sort heap requirements and to control sort heap usage using our load control system. / Thesis (Master, Computing) -- Queen's University, 2011-06-09 11:02:31.595

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With the rapid development of information technology, applications referring to the Internet of things are booming. Applications that gather information from sensors and affect the context environment with actuators can provide customized and intelligent behaviour to users. These applications have become widely used nowadays in daily life and have initiated the multi-dimensional range query demand referring to the Internet of things. As the data information is fully distributed and the devices like sensors, mobile phones, etc., has limited resources and finite energy, supporting efficient range query is a tough challenge. In this paper, we have proposed a distributed range query framework for Internet of things. In order to save energy costs and reduce the network traffic, we suggest a reporting data range mechanism in the sensing peers, which choose to report a data range and report again only when the peer senses an abnormal data instead of the common moving data method. In addition, we selected some strong peers to be used as the super peers to create a data index by collecting the reporting data range, which will be used for performing range queries. The study has shown that our proposal framework could reduce resource costs in the less strong peers like sensors and mobile phones, and reduce network traffic among all the peers within the network, as well as support a range query function. According the evaluation results, the reporting data range method could greatly reduce the data migration times and save energy costs, and the data index could significantly reduce accessing unnecessary peers and diminish the network traffic.

This thesis demonstrates the adequacy of an object-oriented approach to the construction of distributed metainformation systems: systems that facilitate information use by maintaining some information about the information. Computer systems are increasingly being used to store information objects and make them accessible via network. This access, however, still relies on an adequate metainformation system: there must be an effective means of specifying relevant information objects. Moreover, distribution requires the metainformation system to cope well with intermittent availability of network resources. Typical metainformation systems developed to date permit information objects to be specified by expressing knowledge about their syntactic properties, such as keywords. Within this approach, however, query results are potentially too large to be transmitted, stored and treated, at reasonable cost and time. Users are therefore finding it difficult to navigate their way through the masses of information available. In contrast, this thesis is based on the principle that a metainformation system IS more effective if it permits information objects to be specified according to their semantic properties, and that this helps managing, filtering and navigating information. Of particular interest is object orientation because it is the stateof- the-art approach to both the representation of information semantics and the Abstract 11 design of reliable systems. The thesis presents the design and implementation of a programming toolkit for the construction of metainformation systems, where information objects can be any entity that contains information, the notion of views permits organising the information space, transactional access is employed to obtain consistency, and replication is employed to obtain high availability and scalability.

This work is an attempt to enhance query classification in call routing applications. A new method has been introduced to learn weights from training data by means of a regression model. This work has investigated applying the tf-idf weighting method, but the approach is not limited to a specific method and can be used for any weighting scheme. Empirical evaluations with several classifiers including Support Vector Machines (SVM), Maximum Entropy, Naive Bayes, and k-Nearest Neighbor (k-NN) show substantial improvement in both macro and micro F1 measures.

Social network sites are becoming increasingly popular and useful as well as relevant means for serious social research. However, despite their user appeal and wide adoption, the current generation of sites are hard to query and explore, offering limited views of local network neighbourhoods. Moreover these sites are disconnected islands of information due to application and interface differences. We describe SociQL: a query language along with a prototype implementation that enables for the representation, querying and exploration of disparate social networks. Unlike generic web query languages, SociQL is designed to support the examination of sociological questions, incorporating social theory and integration of networks that form a single unified source of information. The thesis discusses the design and rationale for the elements in the language, and reports on our experiences in querying real social network sites with it.

Uncertainty is inherent in many novel and important applications such as market surveillance, information extraction sensor data analysis, etc. In the recent a few decades, uncertain data has attracted considerable research attention. There are various factors that cause the uncertainty, for instance randomness or incompleteness of data, limitations of equipment and delay or loss in data transfer. A probabilistic threshold range aggregate (PRTA) query retrieves summarized information about the uncertain objects in the database satisfying a range query, with respect to a given probability threshold. This thesis is trying to address and handle this important type of query which there is no previous work studying on. We formulate the problem in both discrete and continuous uncertain data model and develop a novel index structure, asU-tree (aggregate-based sampling-auxiliary U-tree) which not only supports exact query answering but also provides approximate results with accuracy guarantee if efficiency is more concerned. The new asU-tree structure is totally dynamic. Query processing algorithms for both exact answer and approximate answer based on this new index structure are also proposed. An extensive experimental study shows that asU-tree is very efficient and effective over real and synthetic datasets.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: reordering predicates; multi-join operator; sliding windows; window predicates; join algorithm; continuous queries. Includes bibliographical references (p. 101-103).

Thesis (M.S.) in Spatial Information Science and Engineering--University of Maine, 2003. / Includes vita. Includes bibliographical references (leaves 86-91).