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Wireless sensor networks (WSN’s) have been receiving a lot of interest in the last two decades due to the variety of applications that can benefit from them. As the interest in WSN’s grows, addressing the physical constraints of these networks has become extremely important to ensure their reliability and efficiency. It was noted in the US Military challenge in 2016 that the wireless networks were already overcrowded and by 2030 the demands on wireless networks will be 250 times greater. Taking this into account, reducing the amount of messages exchanged (communication) between the sensors in the network while maintaining an adequate level of performance has become a critical task, and this will be the focus of this dissertation. A trivial solution which can reduce the amount of communication over a wireless network is by using a periodic communication model and specifying a long enough communication period. In spite of this, this solution may not ensure the level of performance desired. For a WSN to do its job the controller must have sufficient information to be updated. This requires finding a communication strategy for the sensors to exchange messages and find the conditions for the controllers to be updated. This dissertation addresses this problem for different deployment approaches. In this dissertation, we explore various existing and new methods to reduce the amount of communication with sufficient autonomy that allows the sensors to determine when information is needed and what kind of information is needed to perform a given task. The first chapter of this dissertation focuses on the virtual force deployment approach, the second chapter revisits the problem of the Voronoi diagram deployment approach to provide a more practical solution, and the third chapter adapts the tools and concepts from chapter 2 to any type of Voronoi diagram.