With the growing density and shrinking feature size of modern semiconductors, it is increasingly difficult to manufacture defect free semiconductors that maintain acceptable levels of reliability for long periods of time. These systems are increasingly susceptible to wear-out by failing to meet their operational specifications for an extended period of time. The reconfigurability of FPGAs can be used to repair post-manufacturing faults by configuring the FPGA to avoid a damaged resource. This thesis presents a method for preemptively preparing to repair FPGA devices with wear-out faults by precomputing a set of repair circuits that, collectively, can repair a fault found in any logic block of the FPGA. This approach relies on logic placement and routing to create “repair” circuits that avoid specific logic blocks. These repairs can be used when a specific resource has failed. New placement and routing algorithms are proposed for generating such repair circuits. The number of repairs needed to create a complete repair set depends heavily on the utilization of the FPGA resources. The algorithms are tested against several benchmarks and with multiple area constraints for each benchmark. Using this work, on average 20 repair configurations were needed to repair 99% of permanent faults.

<p>How the world eats is changing dramatically. Nowadays, food delivery, where freshly prepared food is delivered from restaurants to customers' residences or workplaces, has become a huge and rapidly growing market. Yet, the escalating expense of food delivery personnel and the guarantee of fast and punctual delivery are big challenges faced by food delivery platforms. To address this issue, our research proposes drone resupply delivery in food delivery, where drones and human couriers collaborate to facilitate the delivery process. Specifically, drones are responsible for resupplying orders from restaurants to couriers, who then complete the final leg of the delivery to customers. The drone resupply delivery model is particularly well-suited for the food delivery industry, as it overcomes the limitations of drone accessibility to customer locations and adheres to the existing ground-based operational system as much as possible. We have developed a mathematical model and a large neighborhood search heuristic to support this approach. Our numerical experiment, based on real-world order data, has demonstrated that the delivery delay and overall efficiency of food delivery are significantly improved through the utilization of drone resupply, compared to traditional ground-only delivery. Moreover, this improvement is achieved with only a small number of drones integrated into the system. </p>

<p>How the world eats is changing dramatically. Nowadays, food delivery, where freshly  prepared food is delivered from restaurants to customers' residences or workplaces, has become a  huge and rapidly growing market. Yet, the escalating expense of food delivery personnel and the  guarantee of fast and punctual delivery are big challenges faced by food delivery platforms. To  address this issue, our research proposes drone resupply delivery in food delivery, where drones  and human couriers collaborate to facilitate the delivery process. Specifically, drones are  responsible for resupplying orders from restaurants to couriers, who then complete the final leg of  the delivery to customers. The drone resupply delivery model is particularly well-suited for the  food delivery industry, as it overcomes the limitations of drone accessibility to customer locations  and adheres to the existing ground-based operational system as much as possible. We have  developed a mathematical model and a large neighborhood search heuristic to support this  approach. Our numerical experiment, based on real-world order data, has demonstrated that the  delivery delay and overall efficiency of food delivery are significantly improved through the  utilization of drone resupply, compared to traditional ground-only delivery. Moreover, this  improvement is achieved with only a small number of drones integrated into the system.</p>

The Internet of Things is expanding, and with the increasing numbers of connected devices,exploitation of those devices also becomes more common. Since IoT devices and IoT networksare used in many crucial areas in modern societies, ranging from everything between securityand militrary applications to healthcare monitoring and production efficiency, the need to securethese devices is of great importance for researchers and businesses. This project explores howan intrusion detection system called DETONAR can be used on border router logs, instead of itsoriginal use of sniffer devices. Using DETONAR in this way allows us to detect many differentattacks, without contributing to the additional cost of deploying sniffer devices and the additionalrisk of the sniffer devices themselves becoming the target of attack

Recent measurements on radio spectrum usage have revealed the abundance of underutilized bands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access. Cognitive radio based secondary networks that utilize such unused spectrum holes in the licensed band, have been proposed as a possible solution to the spectrum crisis. The idea is to detect times when a particular licensed band is unused and use it for transmission without causing interference to the licensed user. We argue that prior knowledge about occupancy of such bands and the corresponding achievable performance metrics can potentially help secondary networks to devise effective strategies to improve utilization. In this work, we use Shepard's method of interpolation to create a spectrum map that provides a spatial distribution of spectrum usage over a region of interest. It is achieved by intelligently fusing the spectrum usage reports shared by the secondary nodes at various locations. The obtained spectrum map is a continuous and differentiable 2-dimension distribution function in space. With the spectrum usage distribution known, we show how different radio spectrum and network performance metrics like channel capacity, secondary network throughput, spectral efficiency, and bit error rate can be estimated. We show the applicability of the spectrum map in solving the intra-cell channel allocation problem in centralized cognitive radio networks, such as IEEE 802.22. We propose a channel allocation scheme where the base station allocates interference free channels to the consumer premise equipments (CPE) using the spectrum map that it creates by fusing the spectrum usage information shared by some CPEs. The most suitable CPEs for information sharing are chosen on a dynamic basis using an iterative clustering algorithm. Next, we present a contention based media access control (MAC) protocol for distributed cognitive radio network. The unlicensed secondary users contend among themselves over a common control channel. Winners of the contention get to access the available channels ensuring high utilization and minimum collision with primary incumbent. Last, we propose a multi-channel, multi-hop routing protocol with secondary transmission power control. The spectrum map, created and maintained by a set of sensors, acts as the basis of finding the best route for every source destination pair. The proposed routing protocol ensures primary receiver protection and maximizes achievable link capacity. Through simulation experiments we show the correctness of the prediction model and how it can be used by secondary networks for strategic positioning of secondary transmitter-receiver pairs and selecting the best candidate channels. The simulation model mimics realistic distribution of TV stations for urban and non-urban areas. Results validate the nature and accuracy of estimation, prediction of performance metrics, and efficiency of the allocation process in an IEEE 802.22 network. Results for the proposed MAC protocol show high channel utilization with primary quality of service degradation within a tolerable limit. Performance evaluation of the proposed routing scheme reveals that it ensures primary receiver protection through secondary power control and maximizes route capacity.

Flooding can severely disrupt transportation systems. When safety measures are limited to road closures, vehicles affected by the flooding have an origin, destination, or path segment that is closed or soon-to-be flooded during the trip's duration. This thesis introduces a framework to provide routing assistance and trip cancellation recommendations to affected vehicles. The framework relies on the connected vehicle environment for real-time link performance measures and flood data and evaluates the trip of the vehicle to determine whether it is affected by the flood or not. If the vehicle is affected and can still leave its origin, the framework generates the corresponding routing assistance in the form of hyperpath(s) or set of alternative paths. On the other hand, a vehicle with a closed origin receives a warning to wait at origin, while a vehicle with an affected destination is assigned to a new safe one. This framework is tested on two transportation networks. The evaluation of the framework's scalability to different network sizes and the sensitivity of the results to various flood characteristics, policy-related variables and other dependencies are performed using simulated vehicle data and hypothetical flood scenarios. The computation times depends on the network size and flood depth but have generally an average of 1.47 seconds for the largest tested network and deepest tested flood. The framework has the potential to alleviate the impacts and inconveniences associated with flooding. / Master of Science

In intelligent transportation systems, the cooperation between vehicles and the road side units is essential to bring these systems to fruition. Vehicular ad hoc networks (VANETs) are a promising technology to enable the communications among vehicles on one hand and between vehicles and road side units on the other hand. However, it is a challenging task to develop a reliable routing algorithm for VANETs due to the high mobility and the frequent changes of the network topology. Communication links are highly vulnerable to disconnection in VANETs; hence, the routing reliability of these ever-changing networks needs to be paid special attention. In this paper, we propose a new vehicular reliability model to facilitate the reliable routing in VANETs. The link reliability is defined as the probability that a direct communication link between two vehicles will stay continuously available over a specified time period. Furthermore, the link reliability value is accurately calculated using the location, direction and velocity information of vehicles along the road. We extend the well-known ad hoc on-demand distance vector (AODV) routing protocol to propose our reliable routing protocol AODV-R. Simulation results demonstrate that AODV-R outperforms significantly the AODV routing protocol in terms of better delivery ratio and less link failures while maintaining a reasonable routing control overhead.

We investigate sensor control and scheduling strategies to most effectively use the limited resources of an ad hoc network or closed-loop sensor network. In this context, we examine the following three problems. Where to focus sensing? Certain types of sensors, such as cameras or radars, are unable to simultaneously collect high fidelity data from all environmental locations, and thus require some sort of sensing strategy. Considering a meteorological radar network, we show that the main benefits of optimizing sensing over expected future states of the environment are when there are multiple small phenomena in the environment. Considering multiple users, we show that the problem of call admission control (i.e., deciding which sensing requests to satisfy) in the context of a virtualized private sensor network can be solved in polynomial time when sensor requests are divisible or fixed in time. When sensor requests are indivisible but may be shifted in time, we show that the call admission control problem is NP-complete. How to make sensing robust to delayed and dropped packets? In a closed-loop sensor network, data collected by the sensors determines each sensor's future data collection strategy. Network delays, however, constrain the quantity of data received by the time a control decision must be made, and consequently affect the quality of the computed sensor control. We investigate the value of separate handling of sensor control and data traffc, during times of congestion, in a closed-loop sensor network. Grounding our analysis in a meteorological radar network, we show that prioritizing sensor control traffc decreases the round-trip control-loop delay, and thus increases the quantity and quality of the collected data and improves application performance. How to make routing robust to network changes? In wireless sensor and mobile ad-hoc networks, variable link characteristics and node mobility give rise to changing network conditions. We propose a routing algorithm that selects a type of routing subgraph (a braid) that is robust to changes in the network topology. We analytically characterize the reliability of a class of braids and their optimality properties, and give counter-examples to other conjectured optimality properties in a well-structured (grid) network. Comparing with dynamic source routing, we show that braid routing can significantly decrease control overhead while only minimally degrading the number of packets delivered, with gains dependent on node density.

Trafiksimulering är vanligt förekommande i stadsbyggarspel, som t.ex. SimCity (2013), och innebär att bilar färdas mot ett bestämt mål, istället för endast visuellt presenterat utifrån statistik, som i tidigare stadsbyggarspel. Problemet med denna simulering är att antalet bilar ökar i takt med att staden växer, vilket innebär att simuleringen måste vara optimalt effektiv för att kunna köras i realtid. För att bilarna ska hitta till målet genomförs vanligtvis en genomsökning av vägnätet med en algoritm som heter A*, som lägger upp en väg till målet.Detta kan vara tidskrävande att simulera i realtid med många bilar. Detta arbete tar fram en ny metod som liknar hur data navigeras på Internet, kallat routing. Denna metod benämns Internet Routing. Metoden testades mot A* algoritmen och sedan jämfördes deras simuleringseffektivitet (FPS). Resultaten visade att det blev nästan samma FPS för båda. Slutsatsen är att den är likvärdig men mer komplex att implementera.

Ad hoc routing inherently serves two separate and conflicting divisions of interest: the needs of the user or individual and the needs of the network or community. These interests should be secured differently. The proposed research is a dual-agent approach for securing ad hoc routing protocols. This approach assumes a physical division of tasks into user agent tasks and tasks performed by a trustworthy network agent. The research, motivated by the need to reduce the tasks of the network agent, investigates strategies for an optimal division of labor while promoting the faithful execution of the routing protocol. This investigation employs the dual-agent approach for securing a variant of distance vector routing.