Master of Science / Department of Electrical and Computer Engineering / Don M. Gruenbacher / The method for communicating within an interconnection network, or fabric of connections between nodes, can be as diverse as are the applications which utilize them. Because of dynamic traffic loads on these interconnection networks, fully-adaptive routing algorithms have been shown to exploit locality while balancing loads and softening the effects of hot-spots. One issue which has been overlooked is the impact of data traveling along the periphery of a selected minimal routable quadrant (MRQ) within these fully-adaptive algorithms. As data aligns with the destination in the x, y, and z dimensions for instance, the data then traverses the periphery of an MRQ. For each dimension that this occurs, the data is given one less choice for routing around hotspots which could appear later along the path. By weighting the decision of selecting a next-hop by avoiding the periphery of the selected MRQ, the data then has more options for avoiding hotspots. One hybridized routing algorithm which borrows heavily from CQR (an efficient and stable fully-adaptive algorithm), is introduced within this work. Enhanced CQR with Periphery Avoidance, attempts to weight the routing decision for a next hop using both output queues and the proximity to the periphery of the MRQ. This fully-adaptive algorithm is tested using simulations and a laboratory research cluster using a USB interconnect in the hypercube topology. It is also compared against other static, oblivious, and adaptive algorithms. Thor's Tack Hammer, the Kansas State University research cluster, is also benchmarked and discussed as an inexpensive and dependable parallel system.

Opportunistic Routing (OR) is an effective and enhanced routing scheme for wireless multihop environment. OR is an approach that selects a certain number of best forwarders (candidates) at each hop by taking the advantage of the broadcast nature of the wireless medium to reach the destination. When a set of candidates receive the packet, they coordinate with each other to figure out which one has to forward the packet toward the destination. Most of the research in this area has been done in mesh networks where nodes do not have mobility. In this survey, we propose a new OR protocol for mobile ad hoc scenarios called as Enhanced Mobility-based Opportunistic Routing (EMOR) protocol. To deal with the node mobility, we have proposed a new metric which considers the following: geographical position of the candidates; the link delivery probability to reach them; the number of neighboring nodes of candidates; and the predicted position of nodes using the motion vector of the nodes. We have compared EMOR with five other well-known routing protocols in terms of delivery ratio, end-to-end delay, and expected number of transmissions from source to the destination. Our simulation results show that proposed protocol improves delivery ratio and number of expected transmission in terms of different type of mobility models.

The increased demand on wireless applications, coupled with the current inefficiency in spectrum usage, mandate a new communication paradigm shift from fixed spectrum assignment to dynamic spectrum sharing which can be achieved using the cognitive radio technology. Cognitive radio allows unlicensed secondary nodes to form communication links over licensed spectrum bands on an opportunistic basis which increases the spectrum management efficiency. Cognitive radio networks (CRN), however, impose unique challenges due to the fluctuation in the available spectrum as well as the diverse quality of service requirements. One of the main challenges is the establishment and maintenance of routes in multi-hop CRNs. In this thesis, we critically investigate the problem of routing in multi-hop CRNs. The main objective of this research is to maximize network connectivity while limiting routing delay. We developed a general connectivity metric for single-band and multi-band CRNs based on the properties of the Laplacian matrix eigenvalues spectrum. We show through analytical and simulation results that the developed metric is more robust and has lower computational complexity than the previously proposed metrics. Furthermore, we propose a new position-based routing algorithm for large scale CRNs which significantly reduces the routing computational complexity with negligible performance degradation compared to the traditional full node search algorithm. In addition, the connectivity metric developed in this thesis is used to develop a connectivity-aware distributed routing protocol for CRNs. Finally, we use a commodity cognitive radio testbed to demonstrate the concept of CR Wi-Fi networks.

Network coding is an emerging technology that intelligently exploits the store/forward nature of routers to increase the efficiency of the network. Though the concept works in theory, the segregation of coding and routing decisions makes them inapplicable in almost any practical environment. Coding-aware routing takes the network coding a step further to lessen its disadvantages by allowing interlayer communication while making routing decisions. However, most of the existing work exploits coding benefits only for fixed wireless networks, making them dependent on the types of network medium, topology and mobility and thus inapplicable for wired and mobile Ad Hoc networks. The aim of this thesis is to present a generalized algorithm that can detect any possible coding opportunity in a network of any medium, topology and mobility while making routing decisions. We have tested and evaluated our algorithm in six different network topology settings i.e. small wired, big wired, small Ad Hoc network with regular trajectories, big Ad Hoc network with regular trajectories, small Ad Hoc with random trajectories and big Ad Hoc with random trajectories. Improved performance in network throughput, mean queue size and mean end-to-end delay confirms the validity of our algorithm.

Underwater wireless sensor networks (UWSNs) are the enabling technology for a new era of underwater monitoring and actuation applications. However, there still is a long road ahead until we reach a technological maturity capable of empowering high-density large deployment of UWSNs. To the date hereof, the scientific community is yet investigating the principles that will guide the design of networking protocols for UWSNs. This is because the principles that guide the design of protocols for terrestrial wireless sensor networks cannot be applied for an UWSN since it uses the acoustic channel instead of radio-frequency-based channel. This thesis provides a general discussion for high-fidelity and energy-efficient data collection in UWSNs. In the first part of this thesis, we propose and study the symbiotic design of topology control and opportunistic routing protocols for UWSNs. We propose the CTC and DTC topology control algorithms that rely on the depth adjustment of the underwater nodes to cope with the communication void region problem. In addition, we propose an analytical framework to study and evaluate our mobility-assisted approach in comparison to the classical bypassing and power control-based approaches. Moreover, we develop the GEDAR routing protocol for mobile UWSNs. GEDAR is the first OR protocol employing our innovative depth adjustment-based topology control methodology to re-actively cope with communication void regions. In the second part of this thesis, we study opportunistic routing (OR) underneath duty-cycling in UWSNs. We propose an analytical framework to investigate the joint design of opportunistic routing and duty cycle protocols for UWSNs. While duty-cycling conserves energy, it changes the effective UWSN density. Therefore, OR is proposed to guarantee a suitable one-hop density of awake neighbors to cope with the poor and time-varying link quality of the acoustic channel. In addition, we propose an analytical framework to study the impact of heterogeneous and on-the-fly sleep interval adjustment in OR underneath duty-cycling in UWSNs. The proposed model is aimed to provide insights for the future design of protocols towards a prolonged UWSN lifetime. The developed solutions have been extensively compared to related work either analytically or through simulations. The obtained results show the potentials of them in several scenarios of UWSNs. In turn, the devised analytical frameworks have been providing significant insights that will guide future developments of routing and duty-cycling protocols for several scenarios and setting of UWSNs.

This thesis describes and analyzes the postal transportation network of Central Bohemian Region, shows an applications of operational management in transport and by Clarke - Wright algorithm with limited capacity of the vehicles and limited time of ride solves the design of new routes to reduce mileage while operating the branch network of the territory.

One of the problems sensor networks face is adversaries corrupting nodes along the path to the base station. One way to reduce the effect of these attacks is multipath routing. This introduces some intrusion-tolerance in the network by way of redundancy but at the cost of a higher power consumption by the sensor nodes. Erasure coding can be applied to this scenario in which the base station can receive a subset of the total data sent and reconstruct the entire message packet at its end. This thesis uses two commonly used encodings and compares their performance with respect to power consumed for unencoded data in multipath routing. It is found that using encoding with multipath routing reduces the power consumption and at the same time enables the user to send reasonably large data sizes. The experiments in this thesis were performed on the Tiny OS platform with the simulations done in TOSSIM and the power measurements were taken in PowerTOSSIM. They were performed on the simple radio model and the lossy radio model provided by Tiny OS. The lossy radio model was simulated with distances of 10 feet, 15 feet and 20 feet between nodes. It was found that by using erasure encoding, double or triple the data size can be sent at the same power consumption rate as unencoded data. All the experiments were performed with the radio set at a normal transmit power, and later a high transmit power.

South African metropolitan areas are experiencing rapid growth and require an increase in network infrastructure. Increased congestion negatively impacts both public and freight transport costs. The concept of City Logistics is concerned with the mobility of cities, and entails the process of optimizing urban logistics activities by concerning the social, environmental, economic, financial, and energy impacts of urban freight movement. In a costcompetitive environment, freight transporters often use sophisticated vehicle routing and scheduling applications to improve fleet utilization and reduce the cost of meeting customer demands. In this thesis, the candidate builds on the observation that vehicle routing and scheduling algorithms are inherent problem specific, with no single algorithm providing a dominant solution to all problem environments. Commercial applications mostly deploy a single algorithm in a multitude of environments which would often be better serviced by various different algorithms. This thesis algorithmically implements the ability of human decision makers to choose an appropriate solution algorithm when solving scheduling problems. The intent of the routing agent is to classify the problem as representative of a traditional problem set, based on its characteristics, and then to solve the problem with the most appropriate solution algorithm known for the traditional problem set. A not-so-artificially-intelligent-vehicle-routing-agent™ is proposed and developed in this thesis. To be considered intelligent, an agent is firstly required to be able to recognize its environment. Fuzzy c-means clustering is employed to analyze the geographic dispersion of the customers (nodes) from an unknown routing problem to determine to which traditional problem set it relates best. Cluster validation is used to classify the routing problem into a traditional problem set. Once the routing environment is classified, the agent selects an appropriate metaheuristic to solve the complex variant of the Vehicle Routing Problem. Multiple soft time windows, a heterogeneous fleet, and multiple scheduling are addressed in the presence of time-dependent travel times. A new initial solution heuristic is proposed that exploits the inherent configuration of customer service times through a concept referred to as time window compatibility. A high-quality initial solution is subsequently improved by the Tabu Search metaheuristic through both an adaptive memory, and a self-selection structure. As an alternative to Tabu Search, a Genetic Algorithm is developed in this thesis. Two new crossover mechanisms are proposed that outperform a number of existing crossover mechanisms. The first proposed mechanism successfully uses the concept of time window compatibility, while the second builds on an idea used from a different sweeping-arc heuristic. A neural network is employed to assist the intelligent routing agent to choose, based on its knowledge base, between the two metaheuristic algorithms available to solve the unknown problem at hand. The routing agent then not only solves the complex variant of the problem, but adapts to the problem environment by evaluating its decisions, and updating, or reaffirming its knowledge base to ensure improved decisions are made in future. / Thesis (PhD (Industrial Engineering))--University of Pretoria, 2007. / Industrial and Systems Engineering / PhD / unrestricted

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

CASCADE 2001 is a multi-basin flood routing program used in areas of flat terrain. CASCADE was used for different situational elements including the Florida Keys, Broward County, and Pensacola. The goal for this screening tool was to create flood inundation watershed mapping for the Florida Division of Emergency Management (FDEM). After showing the risks of flooding that could occur in Florida, the thought of how useful CASCADE can be in other environmental conditions. The Rocky Mountains were selected to show the effect of flood inundation that can be mirrored in an opposite condition from prior experimentation. We chose to test this program in an area with mountainous terrain like the region of Grand Lake, Colorado. Rainfall, in collaboration with groundwater tables, ground soil storage and topography have the most effect on the CASCADE modeling program. Effects that were not used in the Florida models but added for Grand Lake included snowmelt. Snowmelt in the Rocky Mountains affects the flow of the Colorado River causing excess discharge that flows throughout the valleys and into Shadow Mountain Lake. WINSRM was a recommended model that could be used to simulate snowmelt during different months of Colorado’s spring season. The effects of snowmelt and rainfall flooding can be compared in relation to each other. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection