Department of Computer and Information Science Works

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    Secure Authentication in Heterogeneous Wireless Networks
    (Hindawi, 2008-04-03) Durresi, Arjan; Durresi, Mimoza; Barolli, Leonard; Computer and Information Science, School of Science
    The convergence of cellular and IP technologies has pushed the integration of 3G and WLAN networks to the forefront. Gaining secure access to 3G services from 802.11 WLANs is a primary challenge for this new integrated wireless technology. Successful execution of 3G security algorithms can be limited to a specified area by encrypting a user's authentication challenge with spatial data defining his visited WLAN. With limited capacity to determine a user's location only to within a current cell and restrictions on accessing users' location due to privacy, 3G operators must rely on spatial data sent from visited WLANs to implement spatial authentication control. A potential risk is presented to 3G operators since no prior relationship or trust may exist with a WLAN owner. Algorithms to quantify the trust between all parties of 3G-WLAN integrated networks are presented to further secure user authentication. Ad-hoc serving networks and the trust relationships established between mobile users are explored to define stronger algorithms for 3G – WLAN user authentication.
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    ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining
    (BioMed Central, 2008-08-12) Huan, Tianxiao; Sivachenko, Andrey Y.; Harrison, Scott H.; Chen, Jake Yue; Computer and Information Science, School of Science
    Background New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. Results We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network. Conclusion The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.
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    Networked Biomedical System for Ubiquitous Health Monitoring
    (Hindawi, 2008-11-20) Durresi, Arjan; Durresi, Mimoza; Merkoci, Arben; Barolli, Leonard; Computer and Information Science, School of Science
    We propose a distributed system that enables global and ubiquitous health monitoring of patients. The biomedical data will be collected by wearable health diagnostic devices, which will include various types of sensors and will be transmitted towards the corresponding Health Monitoring Centers. The permanent medical data of patients will be kept in the corresponding Home Data Bases, while the measured biomedical data will be sent to the Visitor Health Monitor Center and Visitor Data Base that serves the area of present location of the patient. By combining the measured biomedical data and the permanent medical data, Health Medical Centers will be able to coordinate the needed actions and help the local medical teams to make quickly the best decisions that could be crucial for the patient health, and that can reduce the cost of health service.
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    Advances in Mobile Communications and Computing
    (Hindawi, 2009) Durresi, Arjan; Denko, Mieso; Computer and Information Science, School of Science
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    Advances in Wireless Networks
    (Hindawi, 2009-04-13) Durresi, Arjan; Denko, Mieso; Computer and Information Science, School of Science
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    Tools for Performance Assessment of OLSR Protocol
    (Hindawi, 2009-04-29) Ikeda, Makoto; Barolli, Leonard; De Marco, Giuseppe; Yang, Tao; Durresi, Arjan; Xhafa, Fatos; Computer and Information Science, School of Science
    In this paper, we evaluate the performance of Optimized Link State Routing (OLSR) protocol by experimental and simulation results. The experiments are carried out by using our implemented testbed and the simulations by using ns-2 simulator. We also designed and implemented a new interface for the ad-hoc network testbed in order to make more easier the experiments. The comparison between experimental and simulation results shows that for the same parameters set, in the simulation we did not notice any packet loss. On the other hand, in the experiments we experienced packet loss because of the environment effects and traffic interference.
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    Simulating Real-Time Aspects of Wireless Sensor Networks
    (Springer Verlag, 2009-12-22) Pagano, Paolo; Chitnis, Mangesh; Lipari, Giuseppe; Nastasi, Christian; Liang, Yao; Computer and Information Science, School of Science
    Wireless Sensor Networks (WSNs) technology has been mainly used in the applications with low-frequency sampling and little computational complexity. Recently, new classes of WSN-based applications with different characteristics are being considered, including process control, industrial automation and visual surveillance. Such new applications usually involve relatively heavy computations and also present real-time requirements as bounded end-to- end delay and guaranteed Quality of Service. It becomes then necessary to employ proper resource management policies, not only for communication resources but also jointly for computing resources, in the design and development of such WSN-based applications. In this context, simulation can play a critical role, together with analytical models, for validating a system design against the parameters of Quality of Service demanded for. In this paper, we present RTNS, a publicly available free simulation tool which includes Operating System aspects in wireless distributed applications. RTNS extends the well-known NS-2 simulator with models of the CPU, the Real-Time Operating System and the application tasks, to take into account delays due to the computation in addition to the communication. We demonstrate the benefits of RTNS by presenting our simulation study for a complex WSN-based multi-view vision system for real-time event detection.
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    Architecture for Mobile Heterogeneous Multi Domain Networks
    (Hindawi, 2010-04-01) Durresi, Arjan; Zhang, Ping; Durresi, Mimoza; Barolli, Leonard; Computer and Information Science, School of Science
    Multi domain networks can be used in several scenarios including military, enterprize networks, emergency networks and many other cases. In such networks, each domain might be under its own administration. Therefore, the cooperation among domains is conditioned by individual domain policies regarding sharing information, such as network topology, connectivity, mobility, security, various service availability and so on. We propose a new architecture for Heterogeneous Multi Domain (HMD) networks, in which one the operations are subject to specific domain policies. We propose a hierarchical architecture, with an infrastructure of gateways at highest-control level that enables policy based interconnection, mobility and other services among domains. Gateways are responsible for translation among different communication protocols, including routing, signalling, and security. Besides the architecture, we discuss in more details the mobility and adaptive capacity of services in HMD. We discuss the HMD scalability and other advantages compared to existing architectural and mobility solutions. Furthermore, we analyze the dynamic availability at the control level of the hierarchy.
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    Electronic health information quality challenges and interventions to improve public health surveillance data and practice
    (Association of Schools of Public Health, 2013) Dixon, Brian E.; Siegel, Jason A.; Oemig, Tanya V.; Grannis, Shaun J.; Computer & Information Science, School of Science
    OBJECTIVE: We examined completeness, an attribute of data quality, in the context of electronic laboratory reporting (ELR) of notifiable disease information to public health agencies. METHODS: We extracted more than seven million ELR messages from multiple clinical information systems in two states. We calculated and compared the completeness of various data fields within the messages that were identified to be important to public health reporting processes. We compared unaltered, original messages from source systems with similar messages from another state as well as messages enriched by a health information exchange (HIE). Our analysis focused on calculating completeness (i.e., the number of nonmissing values) for fields deemed important for inclusion in notifiable disease case reports. RESULTS: The completeness of data fields for laboratory transactions varied across clinical information systems and jurisdictions. Fields identifying the patient and test results were usually complete (97%-100%). Fields containing patient demographics, patient contact information, and provider contact information were suboptimal (6%-89%). Transactions enhanced by the HIE were found to be more complete (increases ranged from 2% to 25%) than the original messages. CONCLUSION: ELR data from clinical information systems can be of suboptimal quality. Public health monitoring of data sources and augmentation of ELR message content using HIE services can improve data quality.
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    Batch Discovery of Recurring Rare Classes toward Identifying Anomalous Samples
    (ACM, 2014) Dundar, Murat; Yerebakan, Halid Ziya; Rajwa, Bartek; Computer and Information Science, School of Science
    We present a clustering algorithm for discovering rare yet significant recurring classes across a batch of samples in the presence of random effects. We model each sample data by an infinite mixture of Dirichlet-process Gaussian-mixture models (DPMs) with each DPM representing the noisy realization of its corresponding class distribution in a given sample. We introduce dependencies across multiple samples by placing a global Dirichlet process prior over individual DPMs. This hierarchical prior introduces a sharing mechanism across samples and allows for identifying local realizations of classes across samples. We use collapsed Gibbs sampler for inference to recover local DPMs and identify their class associations. We demonstrate the utility of the proposed algorithm, processing a flow cytometry data set containing two extremely rare cell populations, and report results that significantly outperform competing techniques. The source code of the proposed algorithm is available on the web via the link: http://cs.iupui.edu/~dundar/aspire.htm.