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.

Patch selection behaviour in the presence of environmental constraints

Habitat selection behaviour is the primary way in which organisms are able to regulate encounters with their biotic and abiotic environment. An individual chooses an area that best meets their current needs, particularly regarding safety and the presence of high-quality food. Several physical aspects of the environment can make it difficult for individuals to assess the relative habitat quality of the areas available, thus leading to suboptimal habitat selection. In this thesis, I investigated the way in which two aquatic habitat constraints - obstacles to movement between patches and turbidity - affected the ability of fish to make optimal patch choices, using threespine stickleback Gasterosteus aculeatus as a model species. Laboratory experiments showed that when movement between patches was hindered by increasingly challenging obstacles, groups of stickleback did not move as freely between the patches, and thus had greater deviations from the predictions of the Ideal Free Distribution (IFD). I also demonstrated that, unlike other species, stickleback do not use turbid environments to avoid predator detection. A trend was seen towards avoidance of a turbid food patch regardless of risk level, although this was not statistically significant. As expected, the stickleback avoided feeding in the presence of a predator regardless of water clarity. Overall, I found that both turbidity and movement constraints can have significant impacts on patch use and distribution in the threespine stickleback. Both turbidity and ease of transit will impact the distribution of ecologically important species like the threespine stickleback, and therefore should be taken into account when studying habitat selection in the wild.