Cooperative routing for collision minimization in wireless sensor networks

Cooperative communication has gained much interest due to its ability to exploit the broadcasting nature of the wireless medium to mitigate multipath fading. There has been considerable amount of research on how cooperative transmission can improve the performance of the network by focusing on the physical layer issues. During the past few years, the researchers have started to take into consideration cooperative transmission in routing and there has been a growing interest in designing and evaluating cooperative routing protocols. Most of the existing cooperative routing algorithms are designed to reduce the energy consumption; however, packet collision minimization using cooperative routing has not been addressed yet. This dissertation presents an optimization framework to minimize collision probability using cooperative routing in wireless sensor networks. More specifically, we develop a mathematical model and formulate the problem as a large-scale Mixed Integer Non-Linear Programming problem. We also propose a solution based on the branch and bound algorithm augmented with reducing the search space (branch and bound space reduction). The proposed strategy builds up the optimal routes from each source to the sink node by providing the best set of hops in each route, the best set of relays, and the optimal power allocation for the cooperative transmission links. To reduce the computational complexity, we propose two near optimal cooperative routing algorithms. In the first near optimal algorithm, we solve the problem by decoupling the optimal power allocation scheme from optimal route selection. Therefore, the problem is formulated by an Integer Non-Linear Programming, which is solved using a branch and bound space reduced method. In the second near optimal algorithm, the cooperative routing problem is solved by decoupling the transmission power and the relay node se- lection from the route selection. After solving the routing problems, the power allocation is applied in the selected route. Simulation results show the algorithms can significantly reduce the collision probability compared with existing cooperative routing schemes.

A framework for better understanding drinking-water quality in Happy Valley-Goose Bay, Labrador: Implications for optimization and protection of municipally supplied water

This research project was driven by the recurring complaints and concerns voiced in the media by residents living in the Valley area of the community of Happy Valley-Goose Bay, Labrador. Drinking water in this town is supplied by two water treatment plants (a municipality treatment plant and a DND treatment plant), which use raw water from two different sources (groundwater from multiple wells versus surface water from Spring Gulch brook) and use two different processes of drinking-water treatment. In fact, the drinking water supplied in the Valley area has a unique distribution arrangement. To meet demand, the Valley area is served by a blend of treated waters from a storage reservoir (Sandhill reservoir), which is fed by both water treatment plants. Most of the time, treated water from the municipal treatment plant dominates in the mixture. As water travels through the distribution system and household plumbing, specific reactions can occur either in the water itself and/or at the solid–liquid interface at the pipe walls; this is strongly influenced by the physical and chemical characteristics of the water. These reactions can introduce undesirable chemical compounds and/or favor the growth of bacteria in the drinking water, causing the deterioration of the quality of water reaching the consumer taps. In the distribution system in general, these chemical constituents and bacteria may pose potential threats to health or the water’s aesthetic qualities (smell, taste or appearance). Drinking water should be not only safe, but also palatable.