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Autonomic Failure Identification and Diagnosis for Building Dependable Cloud Computing Systems

Description: The increasingly popular cloud-computing paradigm provides on-demand access to computing and storage with the appearance of unlimited resources. Users are given access to a variety of data and software utilities to manage their work. Users rent virtual resources and pay for only what they use. In spite of the many benefits that cloud computing promises, the lack of dependability in shared virtualized infrastructures is a major obstacle for its wider adoption, especially for mission-critical applications. Virtualization and multi-tenancy increase system complexity and dynamicity. They introduce new sources of failure degrading the dependability of cloud computing systems. To assure cloud dependability, in my dissertation research, I develop autonomic failure identification and diagnosis techniques that are crucial for understanding emergent, cloud-wide phenomena and self-managing resource burdens for cloud availability and productivity enhancement. We study the runtime cloud performance data collected from a cloud test-bed and by using traces from production cloud systems. We define cloud signatures including those metrics that are most relevant to failure instances. We exploit profiled cloud performance data in both time and frequency domain to identify anomalous cloud behaviors and leverage cloud metric subspace analysis to automate the diagnosis of observed failures. We implement a prototype of the anomaly identification system and conduct the experiments in an on-campus cloud computing test-bed and by using the Google datacenter traces. Our experimental results show that our proposed anomaly detection mechanism can achieve 93% detection sensitivity while keeping the false positive rate as low as 6.1% and outperform other tested anomaly detection schemes. In addition, the anomaly detector adapts itself by recursively learning from these newly verified detection results to refine future detection.
Date: May 2014
Creator: Guan, Qiang
Partner: UNT Libraries

Process-Voltage-Temperature Aware Nanoscale Circuit Optimization

Description: Embedded systems which are targeted towards portable applications are required to have low power consumption because such portable devices are typically powered by batteries. During the memory accesses of such battery operated portable systems, including laptops, cell phones and other devices, a significant amount of power or energy is consumed which significantly affects the battery life. Therefore, efficient and leakage power saving cache designs are needed for longer operation of battery powered applications. Design engineers have limited control over many design parameters of the circuit and hence face many chal-lenges due to inherent process technology variations, particularly on static random access memory (SRAM) circuit design. As CMOS process technologies scale down deeper into the nanometer regime, the push for high performance and reliable systems becomes even more challenging. As a result, developing low-power designs while maintaining better performance of the circuit becomes a very difficult task. Furthermore, a major need for accurate analysis and optimization of various forms of total power dissipation and performance in nanoscale CMOS technologies, particularly in SRAMs, is another critical issue to be considered. This dissertation proposes power-leakage and static noise margin (SNM) analysis and methodologies to achieve optimized static random access memories (SRAMs). Alternate topologies of SRAMs, mainly a 7-transistor SRAM, are taken as a case study throughout this dissertation. The optimized cache designs are process-voltage-temperature (PVT) tolerant and consider individual cells as well as memory arrays.
Date: December 2010
Creator: Thakral, Garima
Partner: UNT Libraries

Toward a Data-Type-Based Real Time Geospatial Data Stream Management System

Description: The advent of sensory and communication technologies enables the generation and consumption of large volumes of streaming data. Many of these data streams are geo-referenced. Existing spatio-temporal databases and data stream management systems are not capable of handling real time queries on spatial extents. In this thesis, we investigated several fundamental research issues toward building a data-type-based real time geospatial data stream management system. The thesis makes contributions in the following areas: geo-stream data models, aggregation, window-based nearest neighbor operators, and query optimization strategies. The proposed geo-stream data model is based on second-order logic and multi-typed algebra. Both abstract and discrete data models are proposed and exemplified. I further propose two useful geo-stream operators, namely Region By and WNN, which abstract common aggregation and nearest neighbor queries as generalized data model constructs. Finally, I propose three query optimization algorithms based on spatial, temporal, and spatio-temporal constraints of geo-streams. I show the effectiveness of the data model through many query examples. The effectiveness and the efficiency of the algorithms are validated through extensive experiments on both synthetic and real data sets. This work established the fundamental building blocks toward a full-fledged geo-stream database management system and has potential impact in many applications such as hazard weather alerting and monitoring, traffic analysis, and environmental modeling.
Date: May 2011
Creator: Zhang, Chengyang
Partner: UNT Libraries

Modeling Epidemics on Structured Populations: Effects of Socio-demographic Characteristics and Immune Response Quality

Description: Epidemiologists engage in the study of the distribution and determinants of health-related states or events in human populations. Eventually, they will apply that study to prevent and control problems and contingencies associated with the health of the population. Due to the spread of new pathogens and the emergence of new bio-terrorism threats, it has become imperative to develop new and expand existing techniques to equip public health providers with robust tools to predict and control health-related crises. In this dissertation, I explore the effects caused in the disease dynamics by the differences in individuals’ physiology and social/behavioral characteristics. Multiple computational and mathematical models were developed to quantify the effect of those factors on spatial and temporal variations of the disease epidemics. I developed statistical methods to measure the effects caused in the outbreak dynamics by the incorporation of heterogeneous demographics and social interactions to the individuals of the population. Specifically, I studied the relationship between demographics and the physiological characteristics of an individual when preparing for an infectious disease epidemic.
Date: August 2014
Creator: Reyes Silveyra, Jorge A.
Partner: UNT Libraries

Modeling and Analysis of Intentional And Unintentional Security Vulnerabilities in a Mobile Platform

Description: Mobile phones are one of the essential parts of modern life. Making a phone call is not the main purpose of a smart phone anymore, but merely one of many other features. Online social networking, chatting, short messaging, web browsing, navigating, and photography are some of the other features users enjoy in modern smartphones, most of which are provided by mobile apps. However, with this advancement, many security vulnerabilities have opened up in these devices. Malicious apps are a major threat for modern smartphones. According to Symantec Corp., by the middle of 2013, about 273,000 Android malware apps were identified. It is a complex issue to protect everyday users of mobile devices from the attacks of technologically competent hackers, illegitimate users, trolls, and eavesdroppers. This dissertation emphasizes the concept of intention identification. Then it looks into ways to utilize this intention identification concept to enforce security in a mobile phone platform. For instance, a battery monitoring app requiring SMS permissions indicates suspicious intention as battery monitoring usually does not need SMS permissions. Intention could be either the user's intention or the intention of an app. These intentions can be identified using their behavior or by using their source code. Regardless of the intention type, identifying it, evaluating it, and taking actions by using it to prevent any malicious intentions are the main goals of this research. The following four different security vulnerabilities are identified in this research: Malicious apps, spammers and lurkers in social networks, eavesdroppers in phone conversations, and compromised authentication. These four vulnerabilities are solved by detecting malware applications, identifying malicious users in a social network, enhancing the encryption system of a phone communication, and identifying user activities using electroencephalogram (EEG) for authentication. Each of these solutions are constructed using the idea of intention identification. Furthermore, many of ...
Date: December 2014
Creator: Fazeen, Mohamed & Issadeen, Mohamed
Partner: UNT Libraries

Privacy Management for Online Social Networks

Description: One in seven people in the world use online social networking for a variety of purposes -- to keep in touch with friends and family, to share special occasions, to broadcast announcements, and more. The majority of society has been bought into this new era of communication technology, which allows everyone on the internet to share information with friends. Since social networking has rapidly become a main form of communication, holes in privacy have become apparent. It has come to the point that the whole concept of sharing information requires restructuring. No longer are online social networks simply technology available for a niche market; they are in use by all of society. Thus it is important to not forget that a sense of privacy is inherent as an evolutionary by-product of social intelligence. In any context of society, privacy needs to be a part of the system in order to help users protect themselves from others. This dissertation attempts to address the lack of privacy management in online social networks by designing models which understand the social science behind how we form social groups and share information with each other. Social relationship strength was modeled using activity patterns, vocabulary usage, and behavioral patterns. In addition, automatic configuration for default privacy settings was proposed to help prevent new users from leaking personal information. This dissertation aims to mobilize a new era of social networking that understands social aspects of human network, and uses that knowledge to honor users' privacy.
Date: August 2013
Creator: Baatarjav, Enkh-Amgalan
Partner: UNT Libraries

Extrapolating Subjectivity Research to Other Languages

Description: Socrates articulated it best, "Speak, so I may see you." Indeed, language represents an invisible probe into the mind. It is the medium through which we express our deepest thoughts, our aspirations, our views, our feelings, our inner reality. From the beginning of artificial intelligence, researchers have sought to impart human like understanding to machines. As much of our language represents a form of self expression, capturing thoughts, beliefs, evaluations, opinions, and emotions which are not available for scrutiny by an outside observer, in the field of natural language, research involving these aspects has crystallized under the name of subjectivity and sentiment analysis. While subjectivity classification labels text as either subjective or objective, sentiment classification further divides subjective text into either positive, negative or neutral. In this thesis, I investigate techniques of generating tools and resources for subjectivity analysis that do not rely on an existing natural language processing infrastructure in a given language. This constraint is motivated by the fact that the vast majority of human languages are scarce from an electronic point of view: they lack basic tools such as part-of-speech taggers, parsers, or basic resources such as electronic text, annotated corpora or lexica. This severely limits the implementation of techniques on par with those developed for English, and by applying methods that are lighter in the usage of text processing infrastructure, we are able to conduct multilingual subjectivity research in these languages as well. Since my aim is also to minimize the amount of manual work required to develop lexica or corpora in these languages, the techniques proposed employ a lever approach, where English often acts as the donor language (the fulcrum in a lever) and allows through a relatively minimal amount of effort to establish preliminary subjectivity research in a target language.
Date: May 2013
Creator: Banea, Carmen
Partner: UNT Libraries

Mobile agent security through multi-agent cryptographic protocols.

Description: An increasingly promising and widespread topic of research in distributed computing is the mobile agent paradigm: code travelling and performing computations on remote hosts in an autonomous manner. One of the biggest challenges faced by this new paradigm is security. The issue of protecting sensitive code and data carried by a mobile agent against tampering from a malicious host is particularly hard but important. Based on secure multi-party computation, a recent research direction shows the feasibility of a software-only solution to this problem, which had been deemed impossible by some researchers previously. The best result prior to this dissertation is a single-agent protocol which requires the participation of a trusted third party. Our research employs multi-agent protocols to eliminate the trusted third party, resulting in a protocol with minimum trust assumptions. This dissertation presents one of the first formal definitions of secure mobile agent computation, in which the privacy and integrity of the agent code and data as well as the data provided by the host are all protected. We present secure protocols for mobile agent computation against static, semi-honest or malicious adversaries without relying on any third party or trusting any specific participant in the system. The security of our protocols is formally proven through standard proof technique and according to our formal definition of security. Our second result is a more practical agent protocol with strong security against most real-world host attacks. The security features are carefully analyzed, and the practicality is demonstrated through implementation and experimental study on a real-world mobile agent platform. All these protocols rely heavily on well-established cryptographic primitives, such as encrypted circuits, threshold decryption, and oblivious transfer. Our study of these tools yields new contributions to the general field of cryptography. Particularly, we correct a well-known construction of the encrypted circuit and give ...
Date: May 2004
Creator: Xu, Ke
Partner: UNT Libraries

Split array and scalar data cache: A comprehensive study of data cache organization.

Description: Existing cache organization suffers from the inability to distinguish different types of localities, and non-selectively cache all data rather than making any attempt to take special advantage of the locality type. This causes unnecessary movement of data among the levels of the memory hierarchy and increases in miss ratio. In this dissertation I propose a split data cache architecture that will group memory accesses as scalar or array references according to their inherent locality and will subsequently map each group to a dedicated cache partition. In this system, because scalar and array references will no longer negatively affect each other, cache-interference is diminished, delivering better performance. Further improvement is achieved by the introduction of victim cache, prefetching, data flattening and reconfigurability to tune the array and scalar caches for specific application. The most significant contribution of my work is the introduction of novel cache architecture for embedded microprocessor platforms. My proposed cache architecture uses reconfigurability coupled with split data caches to reduce area and power consumed by cache memories while retaining performance gains. My results show excellent reductions in both memory size and memory access times, translating into reduced power consumption. Since there was a huge reduction in miss rates at L-1 caches, further power reduction is achieved by partially or completely shutting down L-2 data or L-2 instruction caches. The saving in cache sizes resulting from these designs can be used for other processor activities including instruction and data prefetching, branch-prediction buffers. The potential benefits of such techniques for embedded applications have been evaluated in my work. I also explore how my cache organization performs for non-numeric data structures. I propose a novel idea called "Data flattening" which is a profile based memory allocation technique to compress sparsely scattered pointer data into regular contiguous memory locations and explore the ...
Date: August 2007
Creator: Naz, Afrin
Partner: UNT Libraries

An Annotated Bibliography of Mobile Agents in Networks

Description: The purpose of this thesis is to present a comprehensive colligation of applications of mobile agents in networks, and provide a baseline association of these systems. This work has been motivated by the fact that mobile agent systems have been deemed proficuous alternatives in system applications. Several mobile agent systems have been developed to provide scalable and cogent solutions in network-centric applications. This thesis examines some existing mobile agent systems in core networking areas, in particular, those of network and resource management, routing, and the provision of fault tolerance and security. The inherent features of these systems are discussed with respect to their specific functionalities. The applicability and efficacy of mobile agents are further considered in the specific areas mentioned above. Although an initial foray into a collation of this nature, the goal of this annotated bibliography is to provide a generic referential view of mobile agent systems in network applications.
Date: December 2002
Creator: Sriraman, Sandhya
Partner: UNT Libraries

Chemical Information Bulletin, Volume 60, Number 1, Spring 2008

Description: Created as a supplement for "the regular journals of the American Chemical Society," this publication contains annotated bibliographies of chemical documentation literature as well as information about meetings, conferences, awards, scholarships, and other news from the American Chemical Society (ACS) Division of Chemical Information (CINF).
Date: Spring 2008
Creator: American Chemical Society. Division of Chemical Information.
Partner: UNT Libraries

A Multi-Variate Analysis of SMTP Paths and Relays to Restrict Spam and Phishing Attacks in Emails

Description: The classifier discussed in this thesis considers the path traversed by an email (instead of its content) and reputation of the relays, features inaccessible to spammers. Groups of spammers and individual behaviors of a spammer in a given domain were analyzed to yield association patterns, which were then used to identify similar spammers. Unsolicited and phishing emails were successfully isolated from legitimate emails, using analysis results. Spammers and phishers are also categorized into serial spammers/phishers, recent spammers/phishers, prospective spammers/phishers, and suspects. Legitimate emails and trusted domains are classified into socially close (family members, friends), socially distinct (strangers etc), and opt-outs (resolved false positives and false negatives). Overall this classifier resulted in far less false positives when compared to current filters like SpamAssassin, achieving a 98.65% precision, which is well comparable to the precisions achieved by SPF, DNSRBL blacklists.
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Date: December 2006
Creator: Palla, Srikanth
Partner: UNT Libraries

An Integrated Architecture for Ad Hoc Grids

Description: Extensive research has been conducted by the grid community to enable large-scale collaborations in pre-configured environments. grid collaborations can vary in scale and motivation resulting in a coarse classification of grids: national grid, project grid, enterprise grid, and volunteer grid. Despite the differences in scope and scale, all the traditional grids in practice share some common assumptions. They support mutually collaborative communities, adopt a centralized control for membership, and assume a well-defined non-changing collaboration. To support grid applications that do not confirm to these assumptions, we propose the concept of ad hoc grids. In the context of this research, we propose a novel architecture for ad hoc grids that integrates a suite of component frameworks. Specifically, our architecture combines the community management framework, security framework, abstraction framework, quality of service framework, and reputation framework. The overarching objective of our integrated architecture is to support a variety of grid applications in a self-controlled fashion with the help of a self-organizing ad hoc community. We introduce mechanisms in our architecture that successfully isolates malicious elements from the community, inherently improving the quality of grid services and extracting deterministic quality assurances from the underlying infrastructure. We also emphasize on the technology-independence of our architecture, thereby offering the requisite platform for technology interoperability. The feasibility of the proposed architecture is verified with a high-quality ad hoc grid implementation. Additionally, we have analyzed the performance and behavior of ad hoc grids with respect to several control parameters.
Date: May 2006
Creator: Amin, Kaizar Abdul Husain
Partner: UNT Libraries

Generalized Portable SHMEM Library for High Performance Computing

Description: This dissertation describes the efforts to design and implement the Generalized Portable SHMEM library, GPSHMEM, as well as supplementary tools. There are two major components of the GPSHMEM project: the GPSHMEM library itself and the Fortran 77 source-to-source translator. The rest of this thesis is divided into two parts. Part I introduces the shared memory model and the distributed shared memory model. It explains the motivation behind GPSHMEM and presents its functionality and performance results. Part II is entirely devoted to the Fortran 77 translator call fgpp. The need for such a tool is demonstrated, functionality goals are stated, and the design issues are presented along with the development of the solutions.
Date: August 5, 2003
Creator: Parzyszek, Krzysztof
Partner: UNT Libraries Government Documents Department

Analysis and Performance of a Cyber-Human System and Protocols for Geographically Separated Collaborators

Description: This dissertation provides an innovative mechanism to collaborate two geographically separated people on a physical task and a novel method to measure Complexity Index (CI) and calculate Minimal Complexity Index (MCI) of a collaboration protocol. The protocol is represented as a structure, and the information content of it is measured in bits to understand the complex nature of the protocol. Using the complexity metrics, one can analyze the performance of a collaborative system and a collaboration protocol. Security and privacy of the consumers are vital while seeking remote help; this dissertation also provides a novel authorization framework for dynamic access control of resources on an input-constrained appliance used for completing the physical task. Using the innovative Collaborative Appliance for REmote-help (CARE) and with the support of a remotely located expert, fifty-nine subjects with minimal or no prior mechanical knowledge are able to elevate a car for replacing a tire in an average time of six minutes and 53 seconds and with an average protocol complexity of 171.6 bits. Moreover, thirty subjects with minimal or no prior plumbing knowledge are able to change the cartridge of a faucet in an average time of ten minutes and with an average protocol complexity of 250.6 bits. Our experiments and results show that one can use the developed mechanism and methods for expanding the protocols for a variety of home, vehicle, and appliance repairs and installations.
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Date: December 2017
Creator: Jonnada, Srikanth
Partner: UNT Libraries

Location Estimation and Geo-Correlated Information Trends

Description: A tremendous amount of information is being shared every day on social media sites such as Facebook, Twitter or Google+. However, only a small portion of users provide their location information, which can be helpful in targeted advertising and many other services. Current methods in location estimation using social relationships consider social friendship as a simple binary relationship. However, social closeness between users and structure of friends have strong implications on geographic distances. In the first task, we introduce new measures to evaluate the social closeness between users and structure of friends. Then we propose models that use them for location estimation. Compared with the models which take the friend relation as a binary feature, social closeness can help identify which friend of a user is more important and friend structure can help to determine significance level of locations, thus improving the accuracy of the location estimation models. A confidence iteration method is further introduced to improve estimation accuracy and overcome the problem of scarce location information. We evaluate our methods on two different datasets, Twitter and Gowalla. The results show that our model can improve the estimation accuracy by 5% - 20% compared with state-of-the-art friend-based models. In the second task, we also propose a Local Event Discovery and Summarization (LEDS) framework to detect local events from Twitter. Many existing algorithms for event detection focus on larger-scale events and are not sensitive to smaller-scale local events. Most of the local events detected by these methods are major events like important sports, shows, or big natural disasters. In this work, we propose the LEDS framework to detect both bigger and smaller events. LEDS contains three key steps: 1) Detecting possible event related terms by monitoring abnormal distribution in different locations and times; 2) Clustering tweets based on their key terms, ...
Date: December 2017
Creator: Liu, Zhi
Partner: UNT Libraries

Computational Methods to Optimize High-Consequence Variants of the Vehicle Routing Problem for Relief Networks in Humanitarian Logistics

Description: Optimization of relief networks in humanitarian logistics often exemplifies the need for solutions that are feasible given a hard constraint on time. For instance, the distribution of medical countermeasures immediately following a biological disaster event must be completed within a short time-frame. When these supplies are not distributed within the maximum time allowed, the severity of the disaster is quickly exacerbated. Therefore emergency response plans that fail to facilitate the transportation of these supplies in the time allowed are simply not acceptable. As a result, all optimization solutions that fail to satisfy this criterion would be deemed infeasible. This creates a conflict with the priority optimization objective in most variants of the generic vehicle routing problem (VRP). Instead of efficiently maximizing usage of vehicle resources available to construct a feasible solution, these variants ordinarily prioritize the construction of a minimum cost set of vehicle routes. Research presented in this dissertation focuses on the design and analysis of efficient computational methods for optimizing high-consequence variants of the VRP for relief networks. The conflict between prioritizing the minimization of the number of vehicles required or the minimization of total travel time is demonstrated. The optimization of the time and capacity constraints in the context of minimizing the required vehicles are independently examined. An efficient meta-heuristic algorithm based on a continuous spatial partitioning scheme is presented for constructing a minimized set of vehicle routes in practical instances of the VRP that include critically high-cost penalties. Multiple optimization priority strategies that extend this algorithm are examined and compared in a large-scale bio-emergency case study. The algorithms designed from this research are implemented and integrated into an existing computational framework that is currently used by public health officials. These computational tools enhance an emergency response planner's ability to derive a set of vehicle routes specifically ...
Date: August 2018
Creator: Urbanovsky, Joshua C
Partner: UNT Libraries

Dataflow Processing in Memory Achieves Significant Energy Efficiency

Description: The large difference between processor CPU cycle time and memory access time, often referred to as the memory wall, severely limits the performance of streaming applications. Some data centers have shown servers being idle three out of four clocks. High performance instruction sequenced systems are not energy efficient. The execute stage of even simple pipeline processors only use 9% of the pipeline's total energy. A hybrid dataflow system within a memory module is shown to have 7.2 times the performance with 368 times better energy efficiency than an Intel Xeon server processor on the analyzed benchmarks. The dataflow implementation exploits the inherent parallelism and pipelining of the application to improve performance without the overhead functions of caching, instruction fetch, instruction decode, instruction scheduling, reorder buffers, and speculative execution used by high performance out-of-order processors. Coarse grain reconfigurable logic in an energy efficient silicon process provides flexibility to implement multiple algorithms in a low energy solution. Integrating the logic within a 3D stacked memory module provides lower latency and higher bandwidth access to memory while operating independently from the host system processor.
Date: August 2018
Creator: Shelor, Charles F.
Partner: UNT Libraries

Ontology Based Security Threat Assessment and Mitigation for Cloud Systems

Description: A malicious actor often relies on security vulnerabilities of IT systems to launch a cyber attack. Most cloud services are supported by an orchestration of large and complex systems which are prone to vulnerabilities, making threat assessment very challenging. In this research, I developed formal and practical ontology-based techniques that enable automated evaluation of a cloud system's security threats. I use an architecture for threat assessment of cloud systems that leverages a dynamically generated ontology knowledge base. I created an ontology model and represented the components of a cloud system. These ontologies are designed for a set of domains that covers some cloud's aspects and information technology products' cyber threat data. The inputs to our architecture are the configurations of cloud assets and components specification (which encompass the desired assessment procedures) and the outputs are actionable threat assessment results. The focus of this work is on ways of enumerating, assessing, and mitigating emerging cyber security threats. A research toolkit system has been developed to evaluate our architecture. We expect our techniques to be leveraged by any cloud provider or consumer in closing the gap of identifying and remediating known or impending security threats facing their cloud's assets.
Date: December 2018
Creator: Kamongi, Patrick
Partner: UNT Libraries

Theory, modeling, and simulation annual report, 1992

Description: This report briefly discusses research on the following topics: development of electronic structure methods; modeling molecular processes in clusters; modeling molecular processes in solution; modeling molecular processes in separations chemistry; modeling interfacial molecular processes; modeling molecular processes in the atmosphere; methods for periodic calculations on solids; chemistry and physics of minerals; graphical user interfaces for computational chemistry codes; visualization and analysis of molecular simulations; integrated computational chemistry environment; and benchmark computations.
Date: May 1, 1993
Partner: UNT Libraries Government Documents Department

Proceedings: Fourth Workshop on Mining Scientific Datasets

Description: Commercial applications of data mining in areas such as e-commerce, market-basket analysis, text-mining, and web-mining have taken on a central focus in the JCDD community. However, there is a significant amount of innovative data mining work taking place in the context of scientific and engineering applications that is not well represented in the mainstream KDD conferences. For example, scientific data mining techniques are being developed and applied to diverse fields such as remote sensing, physics, chemistry, biology, astronomy, structural mechanics, computational fluid dynamics etc. In these areas, data mining frequently complements and enhances existing analysis methods based on statistics, exploratory data analysis, and domain-specific approaches. On the surface, it may appear that data from one scientific field, say genomics, is very different from another field, such as physics. However, despite their diversity, there is much that is common across the mining of scientific and engineering data. For example, techniques used to identify objects in images are very similar, regardless of whether the images came from a remote sensing application, a physics experiment, an astronomy observation, or a medical study. Further, with data mining being applied to new types of data, such as mesh data from scientific simulations, there is the opportunity to apply and extend data mining to new scientific domains. This one-day workshop brings together data miners analyzing science data and scientists from diverse fields to share their experiences, learn how techniques developed in one field can be applied in another, and better understand some of the newer techniques being developed in the KDD community. This is the fourth workshop on the topic of Mining Scientific Data sets; for information on earlier workshops, see http://www.ahpcrc.org/conferences/. This workshop continues the tradition of addressing challenging problems in a field where the diversity of applications is matched only by the opportunities that ...
Date: July 24, 2001
Creator: Kamath, C
Partner: UNT Libraries Government Documents Department

Radio Resource Control Approaches for LTE-Advanced Femtocell Networks

Description: The architecture of mobile networks has dramatically evolved in order to fulfill the growing demands on wireless services and data. The radio resources, which are used by the current mobile networks, are limited while the users demands are substantially increasing. In the future, tremendous Internet applications are expected to be served by mobile networks. Therefore, increasing the capacity of mobile networks has become a vital issue. Heterogeneous networks (HetNets) have been considered as a promising paradigm for future mobile networks. Accordingly, the concept of small cell has been introduced in order to increase the capacity of the mobile networks. A femtocell network is a kind of small cell networks. Femtocells are deployed within macrocells coverage. Femtocells cover small areas and operate with low transmission power while providing high capacity. Also, UEs can be offloaded from macrocells to femtocells. Thus, the capacity can be increased. However, this will introduce different technical challenges. The interference has become one of the key challenges for deploying femtocells within a certain macrocells coverage. Undesirable impact of the interference can degrade the performance of the mobile networks. Therefore, radio resource management mechanisms are needed in order to address key challenges of deploying femtocells. The objective of this work is to introduce radio resource control approaches, which are used to increase mobile networks' capacity and alleviate undesirable impact of the interference. In addition, proposed radio resource control approaches ensure the coexistence between macrocell and femtocells based on LTE-Advanced environment. Firstly, a novel mechanism is proposed in order to address the interference challenge. The proposed approach mitigates the impact of interference based on controlling radio sub-channels' assignment and dynamically adjusting the transmission power. Secondly, a dynamic strategy is proposed for the FFR mechanism. In the FFR mechanism, the whole spectrum is divided into four fixed sub-channels and each ...
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Date: August 2018
Creator: Alotaibi, Sultan Radhi
Partner: UNT Libraries

Final Report: Legion Core Object Model, March 1, 1996 - September 30, 1999

Description: The model specifies the composition and functionality of Legion's core objects - those objects that cooperate to create, locate, manage, and remove objects from the legion project. In particular, the object model facilitates a flexible extensible implementation, provides a single persistent name space, grants site autonomy to participating organizations, and scales to millions of sites and trillions of objects. Further, it offers a framework that is well suited to providing mechanisms for high performance, security, fault tolerance and commerce.
Date: September 30, 1999
Creator: Grimshaw, Andrew S.
Partner: UNT Libraries Government Documents Department