2 resultados para Moibanus, Ambrosius, 1494-1554.
em CORA - Cork Open Research Archive - University College Cork - Ireland
Resumo:
A wireless sensor network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. In addition, minimising the number of relay nodes might lead to long routing paths to the sink, which may cause problems of data latency. This data latency is extremely important in wireless sensor network applications such as battlefield surveillance, intrusion detection, disaster rescue, highway traffic coordination, etc. where they must not violate the real-time constraints. Therefore, we also consider the problem of deploying multiple sinks in order to improve the network performance. Previous research has only parts of this problem in isolation, and has not properly considered the problems of moving through a constrained environment or discovering changes to that environment during the repair or network quality after the restoration. In this thesis, we firstly consider a base problem in which we assume the exploration tasks have already been completed, and so our aim is to optimise our use of resources in the static fully observed problem. In the real world, we would not know the radio and physical environments after damage, and this creates a dynamic problem where damage must be discovered. Therefore, we extend to the dynamic problem in which the network repair problem considers both exploration and restoration. We then add a hop-count constraint for network quality in which the desired locations can talk to a sink within a hop count limit after the network is restored. For each new problem of the network repair, we have proposed different solutions (heuristics and/or complete algorithms) which prioritise different objectives. We evaluate our solutions based on simulation, assessing the quality of solutions (node cost, movement cost, computation time, and total restoration time) by varying the problem types and the capability of the agent that makes the repair. We show that the relative importance of the objectives influences the choice of algorithm, and different speeds of movement for the repairing agent have a significant impact on performance, and must be taken into account when selecting the algorithm. In particular, the node-based approaches are the best in the node cost, and the path-based approaches are the best in the mobility cost. For the total restoration time, the node-based approaches are the best with a fast moving agent while the path-based approaches are the best with a slow moving agent. For a medium speed moving agent, the total restoration time of the node-based approaches and that of the path-based approaches are almost balanced.
Resumo:
The obesity pandemic has become perhaps the most prevalent health issue of our time, with more than 10% of the world’s population now being obese. Obesity can be defined as abnormal or excess fat accumulation that may impair health and results from an imbalance between energy intake and energy expenditure. A decrease in physical activity due to an increase in sedentary forms of work, changing modes of transport and increasing urbanization is likely a major contributory factor. Diet is another major factor with the increased availability and intake of calorie dense, high fat foods being of global concern. Notably, with respect to this thesis, over the last decade advances in the field of next generation sequencing (NGS) have facilitated investigations to determine the relationship between the gut microbiota and obesity. This thesis examines the impact of a variety of factors on the obesity associated gut microbiota. Overall the results presented in this thesis highlight that microbial diversity is influenced by diet, exercise, antibiotics and disease state, however it is only through further understanding of the structure and function that we can identify targets that can impact on health.