With the increase in fuel prices, the efficient movement of aircraft around an airport can impact the profitability of a flight and an airline. The assignment of a flight to a specific gate not only impacts passenger satisfaction, but also impacts the efficient movement of aircraft from the departure gate to the runway. There have been bodies of research investigating aircraft taxi problems and gate assignment problems. However, each of these research bodies has not included the effects of the other research areas into their respective areas. This research presents a proposed framework that integrates the passenger or freight movement within a terminal with the taxiing of the aircraft to support an integrated approach to solving the gate assignment problem. A solution technique that incorporates a job shop scheduling solution method is presented and demonstrates that a large problem can be solved efficiently and in a short time using both deterministic and stochastic data.

Assuming that vehicle connectivity technology matures and connected vehicles hit the market, many of the running vehicles will be equipped with highly sophisticated sensors and communication hardware. Along with the goal of eliminating human distracted driving and increasing vehicle automation, it is necessary to develop novel intersection control strategies. Accordingly, the research presented in this dissertation develops an innovative system that controls the movement of vehicles using cooperative cruise control system (CACC) capabilities entitled: iCACC (intersection management using CACC). In the iCACC system, the main assumption is that the intersection controller receives vehicle requests from vehicles and advises each vehicle on the optimum course of action by ensuring no crashes occur while at the same time minimizing the intersection delay. In addition, an innovative framework has been developed (APP framework) using the iCACC platform to prioritize the movements of vehicles based on the number of passengers in the vehicle. Using CACC and vehicle-to-infrastructure connectivity, the system was also applied to a single-lane roundabout. In general terms, this application is considered quite similar to the concept of metering single-lane entrance ramps. The proposed iCACC system was tested and compared to three other intersection control strategies, namely: traffic signal control, an all-way stop control (AWSC), and a roundabout, considering different traffic demand levels ranging from low to high levels of congestion (volume-to-capacity ration from 0.2 to 0.9). The simulated results showed savings in delay and fuel consumption in the order of 90 to 45 %, respectively compared to AWSC and traffic signal control. Delays for the roundabout and the iCACC controller were comparable. The simulation results showed that fuel consumption for the iCACC controller was, on average, 33%, 45% and 11% lower than the fuel consumption for the traffic signal, AWSC and roundabout control strategies, respectively. In summary, the developed iCACC system is an innovative system because of its ability to optimize/model different levels of vehicle automation market penetrations, weather conditions, vehicle classes/models, shared movements, roundabouts, and passenger priority. In addition, the iCACC is capable of capturing the heterogeneity of roadway users (cyclists, pedestrians, etc.) using a video detection technique developed in this dissertation effort. It is anticipated that the research findings will contribute to the application of automated systems, connected vehicle technology, and the future of driverless vehicle management. Finally, the public acceptability of the new advanced in-vehicle technologies is a challenging task and this research will provide valuable feedback for researchers, automobile manufacturers, and decision makers in making the case to introduce such systems. / Ph. D.

Distributed event processing systems suffer from poor scalability and inefficient resource usage caused by load distributions typical in real-world applications. The results of these shortcomings are availability issues, poor system performance, and high operating costs. This thesis proposes three remedies to solve these limitations in content-based publish/subscribe, which is a practical realization of an event processing system. First, we present a load balancing algorithm that relocates subscribers to distribute load and avoid overloads. Second, we propose publisher relocation algorithms that reduces both the load imposed onto brokers and delivery delay experienced by subscribers. Third, we present ``green" resource allocation algorithms that allocate as few brokers as possible while maximizing their resource usage efficiency by reconfiguring the publishers, subscribers, and the broker topology. We implemented and evaluated all of our approaches on an open source content-based publish/subscribe system called PADRES and evaluated them on SciNet, PlanetLab, a cluster testbed, and in simulations to prove the effectiveness of our solutions. Our evaluation findings are summarized as follows. One, the proposed load balancing algorithm is effective in distributing and balancing load originating from a single server to all available servers in the network. Two, our publisher relocation algorithm reduces the average input load of the system by up to 68%, average broker message rate by up to 85%, and average delivery delay by up to 68%. Three, our resource allocation algorithm reduces the average broker message rate even further by up to 92% and the number of allocated brokers by up to 91%.

Distributed event processing systems suffer from poor scalability and inefficient resource usage caused by load distributions typical in real-world applications. The results of these shortcomings are availability issues, poor system performance, and high operating costs. This thesis proposes three remedies to solve these limitations in content-based publish/subscribe, which is a practical realization of an event processing system. First, we present a load balancing algorithm that relocates subscribers to distribute load and avoid overloads. Second, we propose publisher relocation algorithms that reduces both the load imposed onto brokers and delivery delay experienced by subscribers. Third, we present ``green" resource allocation algorithms that allocate as few brokers as possible while maximizing their resource usage efficiency by reconfiguring the publishers, subscribers, and the broker topology. We implemented and evaluated all of our approaches on an open source content-based publish/subscribe system called PADRES and evaluated them on SciNet, PlanetLab, a cluster testbed, and in simulations to prove the effectiveness of our solutions. Our evaluation findings are summarized as follows. One, the proposed load balancing algorithm is effective in distributing and balancing load originating from a single server to all available servers in the network. Two, our publisher relocation algorithm reduces the average input load of the system by up to 68%, average broker message rate by up to 85%, and average delivery delay by up to 68%. Three, our resource allocation algorithm reduces the average broker message rate even further by up to 92% and the number of allocated brokers by up to 91%.

We consider a wireless sensor network, in which end users are interested in maximizing the useful information supplied by the network till network partition due to inevitable node deaths. Neither throughput maximization nor network lifetime maximization achieves the objective: A network with high throughput provides information at a high rate, but can exhaust the nodes of their energies quickly; similarly, a network can achieve a long lifetime by remaining idle for most of the time. We propose and seek to maximize a new metric: “Aggregate bit transported before network partition” (a product of throughput and lifetime), which precisely captures the usefulness of sensor networks. We model the links in the wireless sensor network as wired links with reduced equivalent capacities, formulate and solve the problem of maximizing bits transported before network partition on arbitrary networks. To assess the benefits that network coding can yield for the same objective, we study a scenario where the coding-capable nodes are placed on a regular grid. We propose an optimal algorithm to choose the minimum number of coding points in the grid to ensure energy efficiency. Our results show that, even with simple XOR coding, the bits transported can increase up to 83 % of that without coding. Further, we study the problem of in-network data aggregation in a wireless sensor network to achieve minimum delay. The nodes in the network compute and forward data as per a query graph, which allows operations belonging to a general class of functions. We aim to extract the best sub-network that achieves the minimum delay. We design an algorithm to schedule the sub-network such that the computed data reaches sink at the earliest. We consider directed acyclic query graphs as opposed to the existing work which considers tree query graphs only.