Master of Information and Telecommunication Systems (MITS), Ohio University, 2015, Information and Telecommunication Systems (Communication)

This thesis addresses certain technical and financial challenges associated with the deployment and operation of relay spacecraft using the Internet Protocol as the primary routing protocol. Though IP in space has been a hot topic for nearly a decade, few studies address the capabilities of management protocols being used to operate a geostationary fleet. Likewise, few have addressed the real-world cost structure of replacing a traditional bent-pipe fleet with an IP-enabled fleet. Within our research, we investigate whether SNMP, TFTP, and SCP are capable of meeting the Tracking, Telemetry, and Command requirements set by a real-world geostationary relay service provider. We also investigate the driving forces of relay deployment and operational costs, identify Rough Order of Magnitude costs for a geostationary IP-enabled relay, and define a financial profile categorizing the costs of replacing a bent-pipe fleet with an IP-enabled fleet.

Committee: Hans Kruse (Advisor); Shawn Ostermann (Committee Member); Philip Campbell (Committee Member); Wesley Eddy (Committee Member) Subjects: Aerospace Engineering; Communication; Information Science; Information Systems; Information Technology; Technology

PHD, Kent State University, 2023, College of Arts and Sciences / Department of Computer Science

Over the last two decades, the exponential growth in data consumption, applications to facilitate them, and the evolution of application architectures have given rise to high-entropy traffic patterns through data center networks. Load balancing plays a pivotal role in managing this complex traffic pattern by link layer and application layer load balancing. The conventional load balancing meth- ods, while effective to some extent, have faced challenges in responding to the dynamic nature of the traffic pattern. To tackle this challenge, the load balancing concept has transformed, with the emergence of traffic awareness as a critical factor in its implementation. It requires the dynamic weight assignment/update for the paths while load balancing to adapt to high traffic variation. Re- cently emerging ”Protocol Independent Switch Architecture” (PISA) based programmable switches have unleashed the scope of implementing custom load balancing algorithms inside the network fab- ric. These in-network load balancers have the potential to achieve scalable, high throughput, and highly traffic-aware load balancing at the data center scale. However, PISA switches are designed with a limited per-packet computational budget to achieve extremely high throughput in the 6-100 Tbps range. Data center switches need to implement a large set of complex protocols and features. Delegating load-balancing logic to these switches consumes a costly computational budget, making implementing other primary features infeasible. As a result, existing PISA switch-based in-network load balancers are primarily designed for either link or application layer load balancing to meet this budget constraint. Moreover, they can not offer scalability for the same reason. This dissertation takes the next step to fill this critical gap and designs a weighted cost mechanism-based configurable load balancer (CLB)using PISA switches. CLB can offer scalable load balancing for both the link and ap (open full item for complete abstract)

Committee: Javed I. Khan (Advisor) Subjects: Communication; Computer Science

PhD, University of Cincinnati, 2021, Pharmacy: Pharmaceutical Sciences

Background: The efficient and safe delivery of medications represent a challenge, particularly within in-patient hospital pharmacies. Different medication distribution systems have evolved and were deployed to meet this challenge. Centralized, decentralized, and hybrid medication distribution systems comprise the main medication distribution systems. Moreover, the optimization of these systems is an ongoing process, and there is a need for innovative managing tools that align with these distribution systems. Objectives: This dissertation aimed at managing the oral medication distribution system within a Hybrid Medication Distribution System (HMDS) in a pediatric hospital using Artificial Neural Network (ANN) modeling. This aim was sought in two specific aims: to develop and validate an ANN model to determine the assignment of oral medications to either centralized or decentralized distribution system within the HMDS, and to evaluate the expandability of the developed ANN model in managing these assignments in another high-throughput nursing unit. Methods: Retrospective data analyses were performed using a one-year dispensing data from the Cincinnati Children's Hospital Medical Center between January 1st – December 31st of 2018. A subset of the oral medication dispense transactions was obtained, and two nursing units were selected to carry out the analyses for the two aims. The ANN model was developed and validated, and the model's quality metrics were obtained. The expandability of the developed ANN model, as well as the retraining of the model, were evaluated. Results: There was a total of 82,961 oral medication dispense transactions in aim 1 dispensing unit. The centralized distribution accounted for 54.18% of the oral medication dispense transactions, and 45.82% pertained to the decentralized distribution. The ANN model was developed, and cross-validated using 75% training (n= 62,002) and 25% testing (n= 20,667) data. The ANN training model had a 98% (open full item for complete abstract)

Committee: Alex Lin Ph.D. (Committee Chair); Jianfei (Jeff) Guo Ph.D. (Committee Member); Ana Hincapie Ph.D. (Committee Member); Marepalli Rao Ph.D. (Committee Member); Bingfang Yan D.V.M. Ph.D. (Committee Member) Subjects: Pharmaceuticals

Doctor of Philosophy, University of Toledo, 2021, Manufacturing and Technology Management

Since the outbreak of the COVID-19 pandemic in December 2019, the world has gradually appeared markedly different compared with the pre-crisis era. There is no doubt that the COVID-19 pandemic has triggered dynamic changes, but the long-lasting turbulence across the business world was not merely caused by this global crisis. In the first two months of the outbreak, regional shutdowns led to a dramatic supply shock, followed by a demand shortage due to the increasing need for pharmaceuticals and critical medical products (Sherman, 2020; Shih, 2020). In addition, panic buying behaviors of essential living supplies, together with the demand shortage, increase the difficulty of handling supply chain disruptions. These sudden changes caused by COVID-19 are extremely challenging for companies to react appropriately, especially in such a short period of time. However, at the time of writing, it has been more than ten months since the first confirmed case, and the business world is still affected by supply chain disruptions. So, risk management needs breadth and depth investigation to identify potential risk sources beyond the initial disruptions, to assess the risk impacts of subsequent vulnerabilities, to mitigate and predict unnecessary risks, and to improve resilience capabilities from a dynamic view (DuHadway et al., 2019; Ivanov et al., 2017; Ivanov & Dolgui, 2020). This dissertation aims to identify the accelerated risk forces that occur during and after a significant disruption event (i.e., disruption event itself is not the main focus of this investigation), examine how those risks drive the advancement of firm resilience capabilities through strategic and operational practices, and then evaluate the associated performance outcomes. This study first explored the trending topics and business issues from major business newspapers and media sites to obtain research relevant. It results in 1,660 news articles from 11 different sources (e.g., Financial Times, Wall S (open full item for complete abstract)

Committee: Paul Hong (Committee Chair) Subjects: Management; Operations Research

MS, University of Cincinnati, 2020, Education, Criminal Justice, and Human Services: Information Technology

The adoption of Global Software Development (GSD) continues to gain momentum. Globally distributed development is used as a substitute to single-site development mostly for the economic and strategic benefits it offers. (GSD) consists of numerous unique challenges. Requirements change management is one of such challenges. The existing models for managing requirements change in globally distributed software development have some performance issues. This proposal intends to use the mixed research technique to assess the available requirements change management processes, investigate the underlying causes of requirements change in GSD and explore problems faced in managing the changes. The researcher hopes to propose a new model that will use cloud computing which can be implemented for requirements change management in GSD. The proposed model will be simulated and eventually tried to see how it will perform when used in a real-life GSD project.

Committee: M. Murat Ozer Ph.D. (Committee Chair); Bilal Gonen Ph.D. (Committee Member) Subjects: Information Technology

Master of Science, University of Toledo, 2009, Civil Engineering

Prediction of future pavement conditions is one of the important functions of pavement management systems. They are helpful in determining the rate of roadway network deterioration both at the network-level and project-level management, which forms a major part of engineering decision making and reporting. Network-level management focuses on determination and allocation of funds to maintain the pavement network above a specified operational standard and does not give importance to how the individual pavement sections deteriorate. Therefore, a survival time analysis is determined to predict the remaining service life. At the project-level, engineers make decisions on which pavement to repair, when and how to repair. Therefore, it requires more condition accuracy than network-level. The two adjustment methods proposed by Shahin (1994) and Cook and Kazakov (1987) are often used to obtain more condition prediction at the project-level. Both the Shahin and the Cook and Kazakov models take into account a family average curve in predicting deterioration of individual pavement sections. This prediction is done through the latest available condition-age point of an individual pavement section and does not consider all available data points. This study considers the most commonly used pavement condition prediction models viz. linear regression, polynomial constrained least squares, S-shape and power curve. The prediction accuracy of these four models is compared. Further the prediction accuracy of each of the four models is compared with their respective the Shahin's and the Cook's models to determine whether is it possible to further improve the prediction accuracy error for each of the four models.

Committee: Eddie Y. Chou PhD (Committee Chair); George J. Murnen PhD (Committee Member); Andrew G. Heydinger PhD (Committee Member) Subjects: Civil Engineering; Engineering; Transportation

Master of Science (MS), Ohio University, 2019, Electrical Engineering & Computer Science (Engineering and Technology)

Network-on-chip (NoC) continues to be the preferred communication fabric in multicore and manycore architectures as the NoC seamlessly blends the resource efficiency of the bus with the parallelization of the crossbar. However, without adaptable power management the NoC suffers from excessive static power consumption at higher core counts. Static power consumption will increase proportionally as the size of the NoC increases to accommodate higher core counts in the future. NoC also suffers from excessive dynamic energy as traffic loads fluctuate throughout the execution of an application. Power-gating (PG) and Dynamic Voltage and Frequency Scaling (DVFS) are two highly effective techniques proposed in literature to reduce static power and dynamic energy in the NoC respectively. DVFS is a popular technique that allows dynamic energy to be saved but may potentially lead to a loss in throughput. Power-gating allows static power to be saved but can introduce new problems incurred by isolating network routers. Further complications include the introduction of long wake-up delays and break-even times. However, both DVFS and power-gating are critical for realizing energy proportional computing as core counts race into the hundreds for multi-cores. In this thesis, we propose two distinct but related techniques that enable energy proportional computing for NoC. We first propose LEAD - Learning-enabled Energy Aware Dynamic voltage/frequency scaling for NoC architectures. LEAD applies machine learning (ML) techniques to enable improvements in both energy and performance with reduced overhead cost. This allows LEAD to enact a proactive energy management strategy that relies on an offline trained regression model while also providing a wide variety of voltage/frequency (VF) pairs. In this work, we will refer to various VF pairs as modes. LEAD groups each router and the router's outgoing links locally into the same V/F domain allowing energy management at a finer granularity wit (open full item for complete abstract)

Committee: Avinash Karanth (Advisor); Razvan Bunescu (Committee Member); Savas Kaya (Committee Member) Subjects: Computer Engineering; Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2018, Agricultural and Extension Education

The purpose of this study was to explore the informal network of social support within the Ohio State University Extension system, specifically exploring the perceived behaviors, characteristics, and influence of central actors as sources of social support. A mixed-methods approach was employed in two phases: (1) using network analysis to identify the central actors from a census of OSU Extension personnel; and (2) a follow-up survey of identified central actors and their specific relational ties. Findings from this study showed a sparse network with informal social support actor-tie connections generally existing in close physical proximity supporting the preference of in-person interactions. Central actors were described as being older, more experienced, and possessing attributes and characteristics of: accessibility, positivity, listening, open-mindedness, encouragement and coaching, being a role model, an altruistic service orientation, building relationships, being a connector, relevant experience and knowledge, and inclined to provide instrumental assistance. An interesting finding included an element of motivation among central actors reflecting that of self-actualization and spirituality. Central actors were perceived to hold influence on behaviors of ties. Actions reported as contributing to the central actors' influence included: providing aid to navigate organizational practices, empowerment through positivity, encouraging a work-life balance, and enhancing competencies of ties. Interestingly, central actors are passive leaders, as they saw evidence of changes in tie behaviors yet did not perceive themselves as influential. Implications of this study are to encourage others to think about organizational change differently and be encouraged to engage in social support behaviors, and for leaders to create an environment where supportive behaviors are encouraged, developed, and rewarded for the sake of building capacity for change.

Committee: Graham Cochran (Advisor); Jeff King (Advisor); Mary Rodriguez (Committee Member) Subjects: Educational Leadership; Organizational Behavior

Master of Science in Engineering, University of Akron, 2017, Electrical Engineering

In recent years, the Microgrid (MG), a widely acceptable small-scale power infrastructure, is being well developed due to its two characteristics. The rst is its ability to integrate distributed energy resources (DER), especially renewable energy sources (RES). The second is its resilience and reliability especially during emergent situations such as blackouts. Two important aspects for Microgrid Networks (MGN) are efficient coordination with other supportive MGs, which is achieved via energy trading, and security. This thesis proposes several mechanisms for energy trading in the MGN. Firstly, we propose a self-healing resilient Microgrid social network, in which the Deep Belief Network (DBN) algorithm is developed to predict the social relations between different energy users and producers and a coalition game model is designed to reduce the power loss in energy transmission. Secondly, we propose an energy trading mechanism using the game theoretic method by considering the non-stability of renewable energy sources (RES) and social network, by which the individual's decision-making is influenced. Finally, this thesis proposes a Bayesian game-based energy trading mechanism, in which the market participants can share partial information with others to preserve their privacy. The work in this thesis paves the way for further investigation and realization of resilient reliable Microgrids (MGs) to improve reliability and quality of the power supply.

Committee: Jin Wei (Advisor); Hamid Bahrami (Committee Member); Shiva Sastry (Committee Member) Subjects: Electrical Engineering; Energy

Doctor of Business Administration, Cleveland State University, 2017, Monte Ahuja College of Business

Organizations often begin knowledge management (KM) efforts by building knowledge repositories to store organizational knowledge to ensure that it may be later retrieved to reuse, share with, and transfer to knowledge workers. The use of such storage/retrieval systems (S/RS) are particularly relevant in preserving and restoring internal organizational knowledge; such implementations support reduced costs associated with knowledge reacquisition, recreation, and reinvention, thus increasing the efficiency of knowledge transfer. Additionally, there is an increased interest in newer uses of S/RS to support large-scale knowledge-bases and knowledge sharing communities. Therefore, it is important for organizations to understand the factors that influence success in S/RS, as generally, KM systems (KMS) initiatives have failed to realize promised results. This study focuses on knowledge flow from the knowledge repository to the knowledge consumer to facilitate and enable knowledge transfer (FEKT). Because of the strong relationship between S/RS processes and technologies and IS/IT, DeLone and McLean's (2003) IS success model serves as the foundation for the S/RS success model, which is modified here to include the complexities inherent in an S/RS. This empirical study presents a model of S/RS success in FEKT and identifies, prioritizes, and weights both the constructs that define S/RS success and the critical success factors (CSF) that influence these success constructs. In addition to informing KM practitioners, this research also addresses a research gap in the KM literature in respect to storage/retrieval systems in facilitating knowledge transfer. Moreover, while prior KMS research has generally assumed an independence in factors and constructs when empirically testing KMS success, this study embraces the notion that real-world factors and constructs are interrelated, intertwined, and interdependent; thus, the analytic network process (ANP) is used as an analytic method (open full item for complete abstract)

Committee: Radha Appan Ph.D. (Committee Chair); Oya Tukel Ph.D. (Committee Member); Timothy Arndt Ph.D. (Committee Member); Birsen Karpak Ph.D. (Committee Member) Subjects: Information Systems

Doctor of Philosophy, The Ohio State University, 2017, Labor and Human Resources

This dissertation examines the effect of social networks on the occurrence of abusive supervision. Previous study of the predictors of abusive supervision has focused on factors including the leader, follower, and organization, ignoring any relational antecedents that may facilitate or constrain leader abuse. An emerging body of theory and empirical research suggests that leadership is a relational phenomenon. As a result, social networks play an important part in this phenomenon. Thus, I invoke social network frameworks to explain how leader and follower position in intra-team networks—which I define as the structure of social relationships among team members and their leader—influence the frequency of leader abuse. Specifically, considering both benefits and costs of social structure, I hypothesize that leader centrality can both increase and decrease leader abuse. It increases it through ego-depletion and decreases it through leaders' belief that they are trusted. In addition, I theorize that a team member's centrality is negatively associated with leader abuse through perceived utility of the team member and yet, positively associated with leader abuse through identity threat. Finally, linking leader and team member centrality, I hypothesize that leader centrality interacts with member centrality such that leader centrality weakens the link between team member centrality and perceived utility and the link between team member centrality and identity threat. Results with 289 leaders across various organizations provided general support for the iii indirect effect of members' advice network centrality on individual-level abusive supervision (but not for members' friendship network centrality) and partial support for the effect of leaders' advice network centrality on leaders' psychological states, feeling trusted. This dissertation extends abusive supervision and leadership literature by considering abusive supervision as a socially embedded phenomenon and by sho (open full item for complete abstract)

Committee: Bennett Tepper (Advisor); Howard Klein (Committee Member); Robert Lount (Committee Member); James Oldroyd (Committee Member) Subjects: Management

Doctor of Philosophy (PhD), Ohio University, 2016, Mechanical and Systems Engineering (Engineering and Technology)

Global supply chain decisions, such as facility location, manufacturing system design, resource allocation, and distribution center location are long-term strategic decisions in nature and involve many uncertainties. Traditionally, a hierarchical approach is used design supply chain networks and manufacturing systems. First, the location of the facilities are determined, and then the manufacturing systems are designed at the selected locations. In this dissertation, a multi-stage supply chain network model is developed where locations of the plants and inner manufacturing system design are determined simultaneously for labor-intensive manufacturing companies. This dissertation aims to develop a decision making framework to integrate manufacturing systems and supply chain network design decisions considering optimal operator assignment and layered cellular manufacturing in mind. The industry studied is fashion jewelry manufacturing where labor cost is one of the major cost factors. Hence, optimizing the number of workers required for each operation, cell, and plant is critical for the cost efficiency of the entire supply chain. The optimal number of operators are determined for each manufacturing process, and then the optimal cell sizes are found for each manpower level using a heuristic procedure. The optimal number of manufacturing cells required to cover the uncertain demand is determined with mathematical modeling, and the designed layered cellular manufacturing systems for manufacturing stages are evaluated using Arena simulation models. The results of these models and methods are used as inputs while finding the optimal locations of the plants and allocating the optimal number of cells, workers, and machines for each selected plant. Different supply chain design alternatives considering various factors such as the shortest lead times, minimum capacity allocations, and multiple shifts are also studied.

Committee: Gursel A. Suer Ph.D. (Advisor) Subjects: Industrial Engineering; Operations Research

Doctor of Philosophy, Case Western Reserve University, 2015, EECS - Electrical Engineering

Smart distribution system automation is the key to realizing a highly reconfigurable, reliable, flexible and active distribution system. Automated network reconfiguration including restoration is the most studied area in distribution automation, and it contributes to power loss minimization, voltage improvement and also can enable the distribution network to respond to contingencies and changes happened in the grid. Distributed energy resources at the customer premises, energy storage systems and plug-in electric vehicles are indispensable parts of future smart distribution systems. Their participations have brought more dynamics and uncertainties into the grid, and hence new technologies at both planning and operation levels must be developed to manage the energy dispatched from distributed energy resources and energy storage units, the charging and discharging behaviors of electric vehicles so that the entire power distribution system could operate stably and efficiently. Meantime, due to the intermittent, imperfectly predicted renewable energy and more complicated, uncertain load patterns, two challenges have arisen on network reconfiguration study, including more frequent reconfiguration actions and more complicated optimization problems for determining the optimal network topology. Thus, new approaches for reconfiguring distribution networks must be developed to overcome these challenges. In order to address the above challenges which distribution systems are facing to and develop new technologies for realizing smart distribution automation, a comprehensive study on network reconfiguration and energy management of distributed generation systems was studied. The contributions of this dissertation include: (1) proposed a novel problem formulation for network reconfiguration problem based on “switch states”; (2) developed three new methods to solve the optimization problem including heuristic algorithm, hybrid algorithm and revised genetic algorithm; (3) propos (open full item for complete abstract)

Committee: Kenneth Loparo (Advisor); Vira Chankong (Committee Member); Hong Mingguo (Committee Member); Prica Marija (Committee Member) Subjects: Electrical Engineering; Energy

Master of Arts (M.A.), University of Dayton, 2013, Psychology, Clinical

The widespread use of social network websites has made risky online behaviors salient to friends, family, officials, and potential employers. The present study was undertaken to investigate the potential of self-disclosure patterns, psychopathological personality characteristics, gender, and risky behaviors in the ethical, social, and health and safety domains to predict risky online behaviors. The Online Risky Behavior Questionnaire was developed to assess the amount of risky behavior online by 102 male and 73 female participants. Results of this study indicate that men are more likely than women to endorse engaging in risky behaviors online. For both men and women, taking ethical and health/safety risks, self-disclosing with more depth, and engaging in less impression management predicted risky online behaviors. However, for men, another predictor was antisocial personality characteristics. Women in the study were more likely to engage in impression management than were men. Women who were more likely to intend to self-disclose were also more likely to engage in risky social behaviors. New venues for social interactions offer the opportunities for new patterns of self-disclosure and risk-taking behaviors, and it is important for the psychological sciences to keep pace with the technological developments that inform our understanding of social behaviors. It is, therefore, suggested that future studies investigate the links between self-disclosure, socially-desirable reporting, gender differences, and risky online behaviors.

Committee: Susan Davis Ph.D. (Advisor); Lee Dixon Ph.D. (Committee Member); Melissa Layman-Guadalupe Ph.D. (Committee Member) Subjects: Personality; Psychology; Social Psychology; Social Research; Technology

Master of Science in Engineering, Youngstown State University, 2010, Department of Electrical and Computer Engineering

A wireless sensor mesh network for health monitoring of structures is presented. It is a low cost, easy to deploy, fast and reliable wireless sensor network. Wireless nodes are all identical to each other with on board sensors for measuring acceleration and temperature. The acceleration data from the nodes used to detect the strain of the structure was calibrated using a Vishay P3 strain gauge instrument. These sensor nodes can collect data as well as relay the data of the neighboring nodes. Data from all the nodes reaches the base station through multiple hop relays. The nodes were tested for their performance by using different frequency channels and radio output power levels. This network implements an energy efficient routing protocol which can also handle a node failure in route without losing data. Different power conservation techniques were discussed which can keep the network unattended for a week after being deployed on the structure.

Committee: Frank Li PhD (Advisor); Philip Munro PhD (Committee Member); Faramarz Mossayebi PhD (Committee Member) Subjects: Civil Engineering; Computer Science; Electrical Engineering; Engineering

MS, University of Cincinnati, 2009, Engineering : Computer Science

The wireless and mobile networks (WMNs) have grown in an explosion fashion in recent years. The future wireless and mobile network system will allow different types of networks coexisting in some partial of service area and cooperate with each other, and thus an integrated heterogeneous networks system will be formed. On the other hand, the future terminals will be equipped with multiple radio interfaces that can access different types of networks. With the terminals receiving multiple services and performing vertical handoffs between different types of networks, it has imposed great challenges for the integration of heterogeneous wireless networks. One of them is how to effectively manage the resources of different types of networks for a better entire system performance. Another is how to make an efficient network selection to access among different types of networks. Most of the literatures on the first issue discussed the resource management with single type of traffic or network, while few works have considered the multiple traffic in an integrated heterogeneous network environment. On the second issue, most of the works are policy based selection strategies. The policy based selection strategy is to design different selection policy functions, which combine network conditions, and user's preference, etc. in order to make a network selection decision. However, the user's traffic types, i.e. the real-time (voice, video) and non-real-time (data) service, have not been identified in the policies. Based on these, in this thesis, we proposed a resource management and a network selection strategy respectively. Firstly a novel preemption-based resource management scheme supporting multiple traffic in heterogeneous network system is proposed. The proposed scheme takes advantage of the service features of different types of traffic and mobile user's cell dwelling time, as well as moving nature of users. The real-time traffic is allowed to preempt non-real-time traffic a (open full item for complete abstract)

Committee: Raj Bhatnagar PhD (Committee Chair); Anca Ralescu PhD (Committee Member); Carla Purdy PhD (Committee Member); Qing An Zeng PhD (Committee Member) Subjects: Computer Science

PhD, University of Cincinnati, 2008, Engineering : Electrical Engineering

Wireless and mobile networks (WMNs) are witnessing a great success inrecent years. Although there are different types of WMNs (e.g., cellular networks, WLANs, etc.) that can provide different types of services (e.g., different bandwidth and coverage), any single type of existing WMN is not able to provide all types of services such as high bandwidth with wide cov- erage. In order to provide more comprehensive services, a concept of integrated heterogeneous wireless and mobile network (IHWMN) is introduced by combing different types of WMNs. Additionally, with the advance of software defined radio (SDR) technologies, it is possible to integrate multiple WMN interfaces into a single mobile terminal and let the terminal be able to access multiple WMNs. It is obvious that the introduction of IHWMN as well as multi-interface terminal brings more flexible and plentiful access options for mobile users. However, it faces great challenges, such as the architecture of network integration, network selection strategies, handoff scheme, resource allocation, etc. Although IHWMN is a very promising candidate for the future WMNs, a lot of problems have to be solved before launching to the commercial market. In this research thesis, we briefly review the existing work for IHWMN. Then, traffic and system models are proposed for IHWMNs. Based on the proposed models, we tackle the network selection problem in IHWMNs, which is required to determine which network should be accessed. A cost-function-based network selection (CFNS) strategy is proposed based on system's perspective, which also takes into account of the user's needs. Theoretical model is used to evaluate the system performance of the proposed CFNS strategy and simulations are also conducted to verify our analysis. Then, we propose preemption-based resource management schemes to support real-time and non-real-time traffic in IHWMNs. The proposed resource management schemes take advantage of heterogeneities of multiple traffi (open full item for complete abstract)

Committee: Qing-An Zeng (Committee Chair); Kenneth Berman (Committee Member); Raj K. Bhatnagar (Committee Member); Wen-Ben Jone (Committee Member); Heng Wei (Committee Member) Subjects: Computer Science

PhD, University of Cincinnati, 2008, Engineering : Computer Science and Engineering

Wireless Ad Hoc Networks have emerged as an advanced networking paradigm based on collaborative efforts among multiple self-organized wireless communication devices. Without the requirement of a fixed infrastructure support, wireless ad hoc networks can be quickly deployed anywhere at any time when needed. The decentralized nature, minimal configuration and quick deployment of wireless ad hoc networks make them suitable for various applications, from disaster rescue, target tracking to military conflicts. Wireless ad hoc networks can be further categorized into mobile ad hoc networks (MANETs), wireless sensor networks (WSNs), and wireless mesh networks (WMNs) depending on their applications.Security is a big challenge in wireless ad hoc networks due to the lack of any infrastructure support, dynamic network topology, shared radio medium, and resource-constrained wireless users. Most existing security mechanisms applied for the Internet or traditional wireless networks are neither applicable nor suitable for wireless ad hoc network environments. In MANETs, routing security is an extremely important issue, as the majority of the standard routing protocols assume non-hostile environments. Once deployed in a hostile environment and working in an unattended mode, existing routing protocols are vulnerable to various attacks. To address these concerns, we propose an anonymous secure routing protocol for MANETs in this dissertation, which can be incorporated with existing routing protocols and achieve enhanced routing security with minimum additional overheads. In WSNs, key distribution and management is the core issue of any security approaches. Due to extremely resource-constrained sensor nodes and lack of any infrastructure support, traditional public-key based key distribution and management mechanisms are commonly considered as too expensive to be employed in WSNs. In this dissertation, we propose two efficient pairwise key pre-distribution and management mechanisms f (open full item for complete abstract)

Committee: Dharma Agrawal (Committee Chair); Jerome Paul (Committee Member); Wen-Ben Jone (Committee Member); Chia-Yung Han (Committee Member); Ernest Hall (Committee Member) Subjects: Communication; Computer Science

MS, University of Cincinnati, 2004, Engineering : Computer Science

Routing protocols in wireless ad hoc network are highly insecure and prone to various attacks owing to its inherent characteristics of open medium, dynamically changing topologies and distributed cooperation between the member nodes. Having a secure routing protocol in wireless ad hoc networks appears to be a problem that is not trivial to solve. We propose a scheme to enhance the fault-tolerance of cluster head's functionality in CBRP. CBRP with a single cluster head is single point of failure and unsuitable especially for functionalities like key distribution. By distributing the cluster head service to a group of cluster heads called Council nodes and utilizing the (k, n) secret sharing scheme, we can increase the fault tolerance of network manifolds against security attacks. Simulation results obtained demonstrates that our proposed algorithm enables simultaneous formation the Council based clusters, thereby making the scheme time efficient and comparable to CBRP. Results also show that since large size clusters are formed in Council based clusters, it is feasible to apply (k, n) secret sharing concepts. The scheme is more suitable for low mobility networks due to the less signaling overhead involved in during cluster reformations.

Committee: Dr. Dharma Agrawal (Advisor) Subjects: Computer Science

Master of Science, The Ohio State University, 2012, Computer Science and Engineering

For purposes such as end-to-end monitoring, capacity planning, and performance bottleneck troubleshooting across multi-domain networks, there is an increasing trend to deploy interoperable measurement frameworks such as perfSONAR. These deployments expose vast data archives of current and historic measurements, which can be queried using web services. Analysis of these measurements using effective schemes to detect and diagnose anomaly events is vital since it allows for verifying whether network behavior meets expectations. In addition, it allows for proactive notification of bottlenecks that may be affecting large number of users. In this thesis, we describe our novel topology-aware scheme that can be integrated into perfSONAR deployments for detection and diagnosis of network-wide correlated anomaly events. Our scheme involves spatial and temporal analysis on combined topology and uncorrelated anomaly events information for detection of correlated anomaly events. Subsequently, a set of filters are applied on the detected events to prioritize them based on potential bottleneck severity, and to drill-down upon the events nature (e.g., event burstiness) and root-location(s) (e.g., edge or core location affinity). To validate our scheme, we use traceroute information and one-way latency measurements collected over 3 months between various DOE national lab network locations, published via perfSONAR web services. Further, using real-world case studies, we show how our scheme can provide helpful insights for detection and diagnosis of correlated network anomaly events, and can ultimately save time and cost spent on network management.

Committee: Rajiv Ramnath PhD (Advisor); Prasad Calyam PhD (Committee Member); Gagan Agrawal PhD (Committee Member) Subjects: Computer Engineering; Computer Science