Abstract
A long operational lifetime is one of ultimate goals of wireless sensor networks (WSNs) due to the limited energy resources of sensors. As sensors are often randomly deployed in vast and inaccessible areas, it is impractical to recharge or replace their energy resources such as batteries. Thus, energy efficiency is likely to be a highly important issue for the WSNs. A key approach to enhancing energy efficiency is sensor scheduling. Sensor scheduling means that in each operational round certain sensors are selected to be active, whilst others are pushed into sleep mode. However, the required quality of sensing coverage and network connectivity must be guaranteed. The former is that the entire monitored area must be fully covered at a given level called a desired coverage degree (k). Meanwhile, the latter is that every active sensor must be connected with others. Both properties together are known as the connected coverage assurance. This thesis proposes a series of sensor scheduling methods, namely 6-Triangle (6-Tri), 4-Square (4-Sqr), 3-Symmetrical area (3-Sym) and Optimum-Symmetrical area (O-Sym). The 6-Tri method uses a hexagon tessellation as a virtual partition in order to group sensors into hexagonal cells. This method activates 6 sensors from each cell. Otherwise, the 4-Sqr method uses a virtual square partition instead in order to divide the sensors into square cells. A cell consists of 4 sub-squares, within each of which a sensor is activated. Similar to the 6-Tri method, the 3-Sym method has a hexagon tessellation as its virtual partition. As only three sensors whose position is symmetrical with each other are selected in each cell, the 3-Sym method can significantly reduce the number of active sensors, compared to both the 6-Tri and 4-Sqr methods. The O-Sym method enhances the 3-Sym method by optimising coverage efficiency. It firstly investigates coverage redundancy, which is produced by the 3-Sym method, and then tries to minimise the redundancy to the desired coverage degree. This method achieves both energy efficiency and coverage efficiency, which are the main objectives of this thesis.