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Doctor of Philosophy with a Major in Computer Science

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https://hdl.handle.net/1853/72276
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search.filters.applied.f.advisor: Navathe, Shamkant B. ×

Publication Search Results

Now showing 1 - 3 of 3
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    Supporting Distributed Transaction Processing Over Mobile and Heterogeneous Platforms
    (Georgia Institute of Technology, 2005-11-28) Xie, Wanxia
    Recent advances in pervasive computing and peer-to-peer computing have opened up vast opportunities for developing collaborative applications. To benefit from these emerging technologies, there is a need for investigating techniques and tools that will allow development and deployment of these applications on mobile and heterogeneous platforms. To meet these challenging tasks, we need to address the typical characteristics of mobile peer-to-peer systems such as frequent disconnections, frequent network partitions, and peer heterogeneity. This research focuses on developing the necessary models, techniques and algorithms that will enable us to build and deploy collaborative applications in the Internet enabled, mobile peer-to-peer environments. This dissertation proposes a multi-state transaction model and develops a quality aware transaction processing framework to incorporate quality of service with transaction processing. It proposes adaptive ACID properties and develops a quality specification language to associate a quality level with transactions. In addition, this research develops a probabilistic concurrency control mechanism and a group based transaction commit protocol for mobile peer-to-peer systems that greatly reduces blockings in transactions and improves the transaction commit ratio. To the best of our knowledge, this is the first attempt to systematically support disconnection-tolerant and partition-tolerant transaction processing. This dissertation also develops a scalable directory service called PeerDS to support the above framework. It addresses the scalability and dynamism of the directory service from two aspects: peer-to-peer and push-pull hybrid interfaces. It also addresses peer heterogeneity and develops a new technique for load balancing in the peer-to-peer system. This technique comprises an improved routing algorithm for virtualized P2P overlay networks and a generalized Top-K server selection algorithm for load balancing, which could be optimized based on multiple factors such as proximity and cost. The proposed push-pull hybrid interfaces greatly reduce the overhead of directory servers caused by frequent queries from directory clients. In order to further improve the scalability of the push interface, this dissertation also studies and evaluates different filter indexing schemes through which the interests of each update could be calculated very efficiently. This dissertation was developed in conjunction with the middleware called System on Mobile Devices (SyD).
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    Text Mining Biomedical Literature for Genomic Knowledge Discovery
    (Georgia Institute of Technology, 2005-07-20) Liu, Ying
    The last decade has been marked by unprecedented growth in both the production of biomedical data and the amount of published literature discussing it. Almost every known or postulated piece of information pertaining to genes, proteins, and their role in biological processes is reported somewhere in the vast amount of published biomedical literature. We believe the ability to rapidly survey and analyze this literature and extract pertinent information constitutes a necessary step toward both the design and the interpretation of any large-scale experiment. Moreover, automated literature mining offers a yet untapped opportunity to integrate many fragments of information gathered by researchers from multiple fields of expertise into a complete picture exposing the interrelated roles of various genes, proteins, and chemical reactions in cells and organisms. In this thesis, we show that functional keywords in biomedical literature, particularly Medline, represent very valuable information and can be used to discover new genomic knowledge. To validate our claim we present an investigation into text mining biomedical literature to assist microarray data analysis, yeast gene function classification, and biomedical literature categorization. We conduct following studies: 1. We test sets of genes to discover common functional keywords among them and use these keywords to cluster them into groups; 2. We show that it is possible to link genes to diseases by an expert human interpretation of the functional keywords for the genes- none of these diseases are as yet mentioned in public databases; 3. By clustering genes based on commonality of functional keywords it is possible to group genes into meaningful clusters that reveal more information about their functions, link to diseases and roles in metabolism pathways; 4. Using extracted functional keywords, we are able to demonstrate that for yeast genes, we can make a better functional grouping of genes in comparison to available public microarray and phylogenetic databases; 5. We show an application of our approach to literature classification. Using functional keywords as features, we are able to extract epidemiological abstracts automatically from Medline with higher sensitivity and accuracy than a human expert.
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    Developing a Risk Management System for Information Systems Security Incidents
    (Georgia Institute of Technology, 2004-11-22) Farahmand, Fariborz
    The Internet and information systems have enabled businesses to reduce costs, attain greater market reach, and develop closer business partnerships along with improved customer relationships. However, using the Internet has led to new risks and concerns. This research provides a management perspective on the issues confronting CIOs and IT managers. It outlines the current state of the art of information security, the important issues confronting managers, security enforcement measure/techniques, and potential threats and attacks. It develops a model for classification of threats and control measures. It also develops a scheme for probabilistic evaluation of the impact of security threats with some illustrative examples. It involves validation of information assets and probabilities of success of attacks on those assets in organizations and evaluates the expected damages of these attacks. The research outlines some suggested control measures and presents some cost models for quantifying damages from these attacks and compares the tangible and intangible costs of these attacks. This research also develops a risk management system for information systems security incidents in five stages: 1- Resource and application value analysis, 2- Vulnerability and risk analysis, 3- Computation of losses due to threats and benefits of control measures, 4- Selection of control measures, and 5- Implementation of alternatives. The outcome of this research should help decision makers to select the appropriate control measure(s) to minimize damage or loss due to security incidents. Finally, some recommendations for future work are provided to improve the management of security in organizations.