Browsing by Subject "Networks"
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Item An empirical study of the relations between leadership, social support networks, task autonomy and emotions in a technical work environment(Texas A&M University, 2006-04-12) Wickliff, Tanya Verniece DugatThe world in which we live is hyper-dynamic with multiple inputs, outputs and expectations. As it relates to the fast pace of corporate America, customers want products and services within a tighter market window, with no defects and for lower costs. Stakeholders insist that managers do more with less human and financial resources yet more aggressive technological and sales goals. These realities translate into a more complex work environment in that the emotional toll of pending economic outcomes act to motivate or paralyze the very engine designed to produce the desired outcomes the employees. The body of work presented in this dissertation directly addresses the empirical relationship between the perceptions of the work context factors of leadership, task autonomy and social support networks with respect to the positive and negative emotions of the employees of the engineering firm that participated in this study. The empirical results from this research indicate that a positive and significant interrelationship does exist among the factors examined in this study. The employees studied included 249 middle to upper level managers of whom 78.7% were men and 21.3% were women. The range of years of experience for the participants varied from new hire to more than 20 years. Homogeneity of Variance tests confirms the validity of comparative analysis for the segmented data population. Multivariate statistics were used to address the four research questions. The strongest correlations occurred for the subgroups of women and non-managers with respect to the relationship of social support networks and positive emotions. Until now, there has been no empirical research linking the social support networks factor directly to emotions.Item Are you part of the network? : characterizing process couplings and feedbacks in a river delta using information theory(2015-05) Sendrowski, Alicia Paige; Passlacqua, Paola; Gilbert, RobertRiver deltas are highly interconnected systems consisting of channels and inter-channel islands. They result from complex interactions between fluxes of water, sediment, nutrients, energy, and biota. Given the importance of deltas in a social, economic, and ecological context, the understanding of delta function and evolution is of utmost importance. This work aims to use statistical methods to gain insights into delta system processes across spatial and temporal scales. Specifically, understanding the effect of discharge, wind, and tidal forcing on delta variables is a key question. An information theoretic approach was used to identify environmental controls on island and channel inundation, and channel turbidities, in Wax Lake Delta, a naturally prograding delta in coastal Louisiana, USA. Continuous water level data were collected on the islands during summer 2014 and in the channels during winter 2014. Channel turbidities were also collected in winter 2014. Information theory statistics, such as transfer entropy and mutual information, were calculated for all variables to characterize controls on depth and turbidity in terms of strength, direction, and scale. Discharge, wind, and tidal forcing were found to be very dependent on spatial location in the delta. The more upstream locations see increasing influence from discharge in both islands and channels, with tidal influence increasing downstream. Channels are less affected by tides than islands. Wind influence is more complex and varies across space and time for both water level and turbidity. Recalculating information theory metrics under conditions of low and high discharge reveals a higher tidal influence in low flows and a higher wind influence during high flows. The implications for this work are the future construction of a process network, which will show the major flow paths of energy, water, sediments, and nutrients through the system, leading to enhanced metrics that aid in delta system restoration.Item Collaborative intrusion prevention(2009-12) Chung, Pak Ho; Mok, Aloysius Ka-LauIntrusion Prevention Systems (IPSs) have long been proposed as a defense against attacks that propagate too fast for any manual response to be useful. While purely-network-based IPSs have the advantage of being easy to install and manage, research have shown that this class of systems are vulnerable to evasion [70, 65], and can be tricked into filtering normal traffic and create more harm than good [12, 13]. Based on these researches, we believe information about how the attacked hosts process the malicious input is essential to an effective and reliable IPS. In existing IPSs, honeypots are usually used to collect such information. The collected information will then be analyzed to generate countermeasures against the observed attack. Unfortunately, techniques that allow the honeypots in a network to be identified ([5, 71]) can render these IPSs useless. In particular, attacks can be designed to avoid targeting the identified honeypots. As a result, the IPSs will have no information about the attacks, and thus no countermeasure will ever be generated. The use of honeypots is also creating other practical issues which limit the usefulness/feasibility of many host-based IPSs. We propose to solve these problems by duplicating the detection and analysis capability on every protected system; i.e., turning every host into a honeypot.Item Embodied rhetoric : memory and delivery in networked writing(2010-12) Jones, John Mark, 1978-; Syverson, Margaret A., 1948-; Walker, Jeffrey; Davis, Diane; Bremen, Brian A.; Selfe, Cynthia L.Whereas the traditional rhetorical practices of memory and delivery were directly connected to the body of the speaker, I argue that when communication is embodied on digital networks, the processes underlying memory and delivery—the coordination of individual and text and the use of embodied affordances to present a text, respectively— are expressed in different ways. Resonance, or the act of bringing two structures into coordination with each other, and switching, or the act of making connections between two networks, fulfill the role of memory in digital networks, coordinating the actions of different networks. Similarly, the protocol, or the technical and cultural rules of networks, and the program, or the emergent behavior, of a network must be taken into account by writers who wish to achieve rhetorical ends. Using three case studies of network formation on the microblogging service Twitter, I show how the acts of resonance and switching, along with the protocol and program of these networks, influence network formation, the types of communication generated by networks, and how those networks are received by outsiders.Item Enabling information-centric networking : architecture, protocols, and applications(2010-08) Cho, Tae Won, 1978-; Zhang, Yin, doctor of computer science; Gouda, Mohamed; Mooney, Raymond; Ramakrishnan, K.K.; Qiu, LiliAs the Internet is becoming information-centric, network services increasingly demand scalable and efficient communication of information between a multitude of information producers and large groups of interested information consumers. Such information-centric services are growing rapidly in use and deployment. Examples of deployed services that are information-centric include: IPTV, MMORPG, VoD, video conferencing, file sharing, software updates, RSS dissemination, online markets, and grid computing. To effectively support future information-centric services, the network infrastructure for multi-point communication has to address a number of significant challenges: (i) how to understand massive information-centric groups in a scalable manner, (ii) how to analyze and predict the evolution of those groups in an accurate and efficient way, and (iii) how to disseminate content from information producers to a vast number of groups with potentially long-lived membership and highly diverse, dynamic group activity levels? This dissertation proposes novel architecture and protocols that effectively address the above challenges in supporting multi-point communication for future information-centric network services. In doing so, we make the following three major contributions: (1) We develop a novel technique called Proximity Embedding (PE) that can approximate a family of path-ensembled based proximity measures for information-centric groups. We develop Clustered Spectral Graph Embedding (SCGE) that captures the essential structure of large graphs in a highly efficient and scalable manner. Our techniques help to explain the proximity (closeness) of users in information-centric groups, and can be applied to a variety of analysis tasks of complex network structures. (2) Based on SCGE, we develop new supervision based link prediction techniques called Clustered Spectral Learning and Clustered Polynomial Learning that enable us to predict the evolution of massive and complex network structures in an accurate and efficient way. By exploiting supervised information from past snapshots of network structures, our methods yield up to 20% improvement in link prediction accuracy when compared to existing state-of-the-art methods. (3) Finally, we develop a novel multicast infrastructure called Multicast with Adaptive Dual-state (MAD). MAD supports large number of group and group membership, and efficient content dissemination in a presence of dynamic group activity. We demonstrate the effectiveness of our approach in extensive simulation, analysis, and emulation through the real system implementation.Item Human rights discourses on a global network: rhetorical acts and network actors from humanitarian NGOs, conflict sites, and the fiction market(2009-05) Khor, Lena Lay Suan; Arens, Katherine, 1953-; Roberts-Miller, Patricia, 1959-As the language and ideology of human rights globalizes, some scholars have revisited pressing questions about the universality and cultural relativity of human rights as theory, discourse, and practice in philosophy, law, and culture. While some view the globalization of human rights negatively as Western cultural imperialism, others see it positively as a means to empower the oppressed. These arguments often reach an impasse because they presume human rights as a fixed entity. This project reconsiders this assumption in the debate about the globalization of human rights by attending to the discursive (and thus changeable and changing) nature of this language and ideology, and the networked system through which it globalizes. By modeling a global discourse network, it examines how a globalizing discourse of human rights might be affected by and be affecting its subjects, especially their individual identity and agency. Thereafter, it tests this model on three actors speaking from different subject positions and through different textual genres – a humanitarian NGO and a speech; a genocide survivor and an autobiography; and a global author and a novel. These case studies suggest that groups and individuals speaking from traditionally less-than-powerful subject positions (like the NGO and crisis survivor) in a typical human rights framework can benefit from the discourse and its network. They gain global presence and influence through the network’s amplifying effects on identity, influence, and conventions, which offer its users the chance of appearing as agents. But there are also instances (as with the author and novel) where the universalist rhetoric of the discourse and the global reach of its network (their power) cannot overcome the force of other more divisive discourses and networks oriented around markers of difference like nationality, ethnicity, class, or religion. This project thus outlines some possibilities and limits of speaking globally through a purportedly universalist discourse in a network situation, and identifies consistent problems of representing human rights crisis and causes as globalized speech acts and from postnational speaking positions, in a still nation-centered world.Item An information theoretic approach to structured high-dimensional problems(2013-12) Das, Abhik Kumar; Vishwanath, SriramA majority of the data transmitted and processed today has an inherent structured high-dimensional nature, either because of the process of encoding using high-dimensional codebooks for providing a systematic structure, or dependency of the data on a large number of agents or variables. As a result, many problem setups associated with transmission and processing of data have a structured high-dimensional aspect to them. This dissertation takes a look at two such problems, namely, communication over networks using network coding, and learning the structure of graphical representations like Markov networks using observed data, from an information-theoretic perspective. Such an approach yields intuition about good coding architectures as well as the limitations imposed by the high-dimensional framework. Th e dissertation studies the problem of network coding for networks having multiple transmission sessions, i.e., multiple users communicating with each other at the same time. The connection between such networks and the information-theoretic interference channel is examined, and the concept of interference alignment, derived from interference channel literature, is coupled with linear network coding to develop novel coding schemes off ering good guarantees on achievable throughput. In particular, two setups are analyzed – the first where each user requires data from only one user (multiple unicasts), and the second where each user requires data from potentially multiple users (multiple multicasts). It is demonstrated that one can achieve a rate equalling a signi ficant fraction of the maximal rate for each transmission session, provided certain constraints on the network topology are satisfi ed. Th e dissertation also analyzes the problem of learning the structure of Markov networks from observed samples – the learning problem is interpreted as a channel coding problem and its achievability and converse aspects are examined. A rate-distortion theoretic approach is taken for the converse aspect, and information-theoretic lower bounds on the number of samples, required for any algorithm to learn the Markov graph up to a pre-speci fied edit distance, are derived for ensembles of discrete and Gaussian Markov networks based on degree-bounded graphs. The problem of accurately learning the structure of discrete Markov networks, based on power-law graphs generated from the con figuration model, is also studied. The eff ect of power-law exponent value on the hardness of the learning problem is deduced from the converse aspect – it is shown that discrete Markov networks on power-law graphs with smaller exponent values require more number of samples to ensure accurate recovery of their underlying graphs for any learning algorithm. For the achievability aspect, an effi cient learning algorithm is designed for accurately reconstructing the structure of Ising model based on power-law graphs from the con figuration model; it is demonstrated that optimal number of samples su ffices for recovering the exact graph under certain constraints on the Ising model potential values.Item The integration of emergency economies in developing countries : the case of Los Platanitos, Santo Domingo Norte, Dominican Republic(2010-05) Strange, Shawn Michael; Sletto, Bjørn; Wilson, Robert H.Slum development in the Global South continues at a rapid pace, leading to a search for solutions to the severe environmental, social, and economical challenges facing these settlements. Informal economic activities are central to these communities’ survival and structure. Ownership policies have been initiated that contribute to security for residents, and there is evidence that this can lead to increased social and economic productivity. However, studies have also shown that broad ranging titling reforms may destroy existing networks, practices, and livelihoods of residents. This raises a fundamental question on how land titling and formalization of business ownership can be accomplished, while still maintaining local social networks and livelihoods. This thesis calls attention to the need to develop policy approaches that are context specific while also taking into account the complex economic networks that develop in informal settlements.Item Network routing problems in stochastic-state networks(2011-05) Fajardo, David Ignacio; Waller, S. Travis; Hasenbein, John; Machemehl, Randy; Zhang, Zhanmin; Unnikrishnan, AvinashNetwork Routing problems focus on exploiting the network-based struc- ture of a mathematical optimization problem to establish e cient solutions that are tailored to the problem at hand. The topic of this dissertation relates to a speci c class of network routing problems, those in which the properties of the nodes and/or links in the network can be represented as instances of a particular network-state realization, where the set possible network-state can be represented by a discrete probability distribution. The main contribution of this research is to formalize the de nition of such families of network-states, a construct we de ne as Stochastic-State Networks (SSN), and show that certain properties of such networks can allow for the systematic development of exact and heuristic solution procedures for a speciric class of network routing problems. The class of network problems considered are those in which dynamic routing decisions are seeked, and where information about the network can only be gathered through direct observation of the instantiation of the stochastic elements of the network. Two speci c instances of routing problems are considered: a dynamic instance of a Traveling Salesman Problem, and a routing problem in the presence of stochastic link failures. Exact methods and heuristics are developed by exploiting the underlaying stochastic-state network formulation and numerical results are presented.Item Performance of Quantized Congestion Notification in TCP Incast in Data Centers(2011-08-08) Devkota, Prajjwal PrasadThis thesis analyzes the performance of Quantized Congestion Notification (QCN) during data access from clustered servers in data centers. The reasons why QCN does not perform adequately in these situations are examined and several modifications are proposed to the protocol to improve its performance in these scenarios. The causes of QCN performance degradation are traced to flow rate variability, and it is shown that adaptive sampling at the switch and adaptive self-increase of flow rates at the QCN rate limiter significantly enhance QCN performance in a TCP Incast setup. The performance of QCN is compared against TCP modifications in a heterogeneous environment, and it is shown that modifications to QCN yield better performance. Finally, the performance of QCN with the proposed modifications is compared with that of unmodified QCN in other workloads to show that the modifications do not negatively affect QCN performance in general.Item Prediction of end-to-end single flow characteristics in best-effort networks(Texas A&M University, 2005-08-29) Shukla, Yashkumar DipakkumarThe nature of user traffic in coming years will become increasingly multimediaoriented which has much more stringent Quality of Service (QoS) requirements. The current generation of the public Internet does not provide any strict QoS guarantees. Providing Quality of Service (QoS) for multimedia application has been a difficult and challenging problem. Developing predictive models for best-effort networks, like the Internet, would be beneficial for addressing a number of technical issues, such as network bandwidth provisioning, congestion avoidance/control to name a few. The immediate motivation for creating predictive models is to improve the QoS perceived by end-users in real-time applications, such as audio and video. This research aims at developing models for single-step-ahead and multi-stepahead prediction of end-to-end single flow characteristics in best-effort networks. The performance of path-independent predictors has also been studied in this research. Empirical predictors are developed using simulated traffic data obtained from ns-2 as well as for actual traffic data collected from PlanetLab. The linear system identification models Auto-Regressive (AR), Auto-Regressive Moving Average (ARMA) and the non-linear models Feed-forward Multi-layer Perceptron (FMLP) have been used to develop predictive models. In the present research, accumulation is chosen as a signal to model the end-to-end single flow characteristics. As the raw accumulation signal is extremely noisy, the moving average of the accumulation isused for the prediction. Developed predictors have been found to perform accurate single-step-ahead predictions. However, as the multi-step-ahead prediction horizon is increased, the models do not perform as accurately as in the single-step-ahead prediction case. Acceptable multi-step-ahead predictors for up to 240 msec prediction horizon have been obtained using actual traffic data.Item Realtime Streaming with Guaranteed QOS over Wireless D2D Networks(2014-05-22) Paul, SumanThe increase in the processing power of mobile devices has led to an explosion of available services and applications. However, the cost of mobile data is a hindrance to the adoption of data intensive applications. We consider a group of co-located wireless peer devices that desire to synchronously receive a live content stream. Devices desire to minimize the usage of their B2D interfaces (3G/4G) to reduce cost, while maintaining synchronous reception and playout of content. While it might be possible for a cellular base station to broadcast or multicast live events to multiple handsets, such content would be restricted to a few selected channels, and only available to subscribers of a single provider. Utilizing both B2D and D2D (WiFi) interfaces enables users to pick any event of interest, and "stitch together" their B2D capacities regardless of provider support. Our objective is to enable users to listen or watch real time streams while incurring only a fraction of the original costs. Our system setup is as follows. The real-time stream is divided into blocks, which must be played out soon after their initial creation. If a block is not received within a specific time after its creation, it is rendered useless and dropped. The blocks in turn are divided into random linear coded chunks to facilitate sharing across the devices. We transform the problem into the two questions of (i) deciding which peer should broadcast a chunk on the D2D channel at each time, and (ii) how long B2D transmissions should take place for each block. The thesis studies the performance of a provably-minimum-cost algorithm that can ensure that QoS targets can be met for each device. We use a Lyapunov stability argument to show that a stable delivery ratio can be achieved using our mechanism. We show that the optimal D2D scheduling algorithm has a simple and intuitive form under reliable broadcast, which allows for easy implementation and development of good heuristics. We study this via simulations, and present an overview of the implementation on Android phones using the algorithm as a basis. Additionally, we design an incentive framework that promotes cooperation among devices. We show that under this incentive framework, each device benefits by truthfully reporting the number of chunks that it received via B2D and its deficit in each frame, so that a system-wide optimal allocation policy can be employed. The incentive framework developed is lightweight and compatible with minimal amounts of history retention. The Android testbed used in the experiments consisted of multiple Google Nexus 4 phones. A modified version of Android Jelly Bean (v 4.3) was built in order to conduct the experiments which removes the limitation wherein the phone switches off its 3G data connection (B2D) whenever a known WiFi network (D2D) becomes available. Since the Nexus 4 devices are incapable of operating in ad-hoc mode, we used a WiFi network (without Internet connectivity) to emulate the D2D part. Hence, devices must use their 3G interfaces to receive chunks for the server (via the Internet). We present experimental results, and show that it would be possible to follow popular streams on hand held devices incurring only a fraction of the costs while achieving a high QoS.Item Submicroscopic characterization of biopolymer networks in solution by Thermal Noise Imaging(2013-05) Bartsch, Tobias Fabian; Florin, Ernst-Ludwig; Shubeita, George T; Aldrich, Richard W; Demkov, Alex A; Fink, ManfredBiopolymer networks display a wide range of interesting mechanical properties that are essential for living organisms. For example, a highly nonlinear elastic response to strain gives biopolymer networks the ability to comply with small stresses but to resist large ones. These macroscopic mechanical properties have their origin in the properties of the individual filaments and their connectedness, like cross-linking geometry and pore size distribution. While the macroscopic properties of biopolymer networks have been extensively studied, there has been a lack of experimental techniques that can simultaneously determine mechanical and architectural properties of networks in situ with single filament resolution. This work introduces Thermal Noise Imaging (TNI) as a novel quantitative method to address these issues. TNI is a three-dimensional scanning probe technique that utilizes the confined thermal motion of an optically trapped particle as a three-dimensional, noninvasive scanner for soft, biological material. Using a photonic force microscope (PFM) custom built for this research, the position of the probe can be detected with nanometer precision and megahertz bandwidth. Two sets of single molecule experiments are described that demonstrate the microscope's exceptional precision and stability. Micrometer scale thermal noise images inside a collagen network are shown and quantitative information about cross-linking geometry is extracted from the data. Further, by imaging microtubules grafted to a support it is shown that the acquired data yield information about the transversal fluctuations of the imaged fibers and about fiber elasticity. These results pave the way for an investigation of force distributions inside biopolymer networks on the single filament level.