A method of sub-optimal sensor placement: sensing coverage and data precision
International Journal of Systems, Control and Communications
Coverage restoration of wireless sensor networks through the usage of decision trees
AsiaCSN '07 Proceedings of the Fourth IASTED Asian Conference on Communication Systems and Networks
Adaptive k-coverage contour evaluation and deployment in wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
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Wireless sensor networks are emerging as a new computational platform consisting of small, low-power and inexpensive nodes that integrate a modest amount of sensing, computation and wireless communication capabilities. These have found popular applications in a broad set of areas including environmental monitoring, habitat monitoring and disaster recovery. Typically sensor nodes are deployed over a geographical area for the purpose of detecting, tracking and monitoring events of interest. Reports produced upon the observation of specific events are then processed locally at the sensor nodes and transmitted over multiple hops to a centralized sink in order to reach an operations center or to be analyzed further. Since sensor nodes are deployed in a large land region, the objective is to achieve complete coverage of the region, that is, every location in the region lies in the observation field of at least one sensor node. However the initial placement of sensors may not achieve this goal for various reasons: the number of original sensors may have been too low, the original placement may have been random (for example, sensors deployed from the air) leaving parts of the region uncovered, or, some of the sensors have malfunctioned, leaving coverage holes. In this paper we study the coverage restoration problem in sensor networks. The fundamental question is “Given a two-dimensional area, a piece of land for example, and an initial set of sensors, how can we determine the number of sensor nodes required to completely cover the region”. Essentially, the coverage restoration problem re.ects how well an area is monitored by sensors. In abstract terms, our approach determines uncovered area in the sensor network .eld and proposes the deployment of nodes to completely cover the area. Our mechanism consists of two steps: (a) estimating the regions uncovered by sensors and (b) identifying the minimum number and location of sensors required to cover this region. The key idea of our technique is to make an e.cient and yet very accurate representation of the uncovered area that uses techniques from discrepancy theory. By representing the uncovered area as a set of points,we can use e.cient and simple algorithms for .nding small sets of sensors to cover the uncovered areas. We partition the sensor network into cells, and run these algorithms locally. We formulate this problem as a disk covering problem where the goal is to cover a set of points on the plane by a set of disks. This problem is known to be NP-complete. However, there exist various approximate solutions that run in polynomial time and have a bounded error ratio.We use one of such proposed algorithm for our experimental purpose. The technique we propose is distributed, and minimizes thecommunication costs.We present a comprehensive set of experiments that demonstrate that our technique is highly e.ective in achieving a good coverage of a given sensor network area.