Energy limitation is one of the most critical challenges in the area of sensor networks. Sleep scheduling mechanisms can reduce the energy consumption. Coverage mechanisms attempt to cover the area with the minimum possible number of sensors. There are many area coverage approaches which also consider the connectivity problem. However, in the area of point coverage, there are limited mechanisms that maintain connectivity. In this paper, we propose a point coverage mechanism and two connectivity mechanisms. We compare these mechanisms to one of the best methods that consider both point coverage and connectivity. In the point coverage mechanism, we present a method for computing the waiting time, which reduces the number of the required sensors. For preserving the connectivity, virtual robust spanning tree (VRST) and modified virtual robust spanning tree (MVRST) are proposed. These mechanisms are based on making a virtual spanning tree and converting this tree to a physical tree. In order to spread out sensed data to the sink from different paths and decrease the loss probability, instead of using a minimum spanning tree (MST) to connect nodes to the sink, we use a combination of distance of nodes and number of hops to select edges and construct the tree. The simulation results show that the proposed coverage method reduces energy consumption by up to 7% compared to the Cardei method. The VRST and MVRST use more energy than the Cardei method, but the average data loss decreases by up to 40%. Moreover, VRST and MVRST have less depth and data latency.
['Pouya Ostovari', 'Mehdi Dehghan', 'Jie Wu']
Connected Point Coverage in Wireless Sensor Networks Using Robust Spanning Trees