# Estimation and Healing of Coverage Hole in Hybrid Sensor Networks: A Simulation Approach
## 2 Related Work  
In the WSNs, coverage is a fundamental but complicated problem all the time. For deterministic sensor deployment, coverage holes may not exist owns to the reasonable sensor layout, nevertheless the random distribution sensor always encounters many unexpected problems, for instance the redundant nodes and coverage holes. A lot of comprehensive studies about the redundancy and coverage have been done. In paper [8], the authors discussed the effect of adjustable radius for the network lifetime. They proposed an algorithm based on learning-automata and equipped with a pruning rule, the algorithm is aimed to select a sensor which can adjust radius to satisfy a certain target coverage. The main idea of radius adaptive mechanism is to reduce the overlaps among sensing ranges while guarantee the QoS of coverage. However, radius adaptive mechanism is mainly used to solve the certain objective coverage problems, as how to apply it to more extensive coverage is a knotty question. [PERSON] et al. at [9] estimated the number of coverage holes by detecting critical points on the boundary, calculated locations of new nodes by two kinds of models which are adjacent critical points and multi-adjacent critical points, as well as got the conclusion that patched sensor nodes should be deployed on the bisectors of boundary lines. The hybrid network which contained both static and mobile sensors was studied in paper [10; 11; 12; 13; 14; 15; 16]. [PERSON] et al. [10] employed the geometrical approaches, and the mainly steps including divided monitoring area into many cells by Voronoi diagram [11], estimated the coverage holes by static sensors and commanded mobile sensors to move to the target location to heal the holes. But they did not propose the detail scheme about how to work out the coverage holes. In the process of biding the mobile sensors, two mobile guidelines those were Distance-based and Price-based were came up by them. The Distance-based scheme mainly took the moving distance into consideration, the assistant sensor moves or not depends on the distance between server and target location. The Price-based approach was based on the cost, due to move different mobile sensors have different cost, the cheapest mobile sensor would have priority to heal the coverage hole. Besides, they also provided a Multiple Healing Detection algorithm to deal with the multiple healing problem. In paper [12], the authors developed two sets of distributed protocols [13] for controlling the movement path of sensors and provided three kind of target locations calculated algorithms. [PERSON] et al. [5] proposed the DT-Score algorithm which was a two phases method to maximize the coverage of an area with obstacles. At the first phase, they used contour-based deployment to estimate the coverage holes, what important is that the deployment has an excellent performance of coverage holes detecting about the obstacles and area boundary. It is important to deploy an excellent performance of coverage holes detecting about the obstacles and area boundary. In the second phase, the deployment method applied the DT to the uncovered area, after calculating the candidate positions of assistant sensors, they scored the candidate position and chosen the high scores positions to locate assistant sensor. [PERSON] et al. (2014) provided the COVEN algorithm to enhance coverage, they exploited the Voronoi diagram to achieve accurate calculation about the coverage holes. The method divided the detecting field into many cells and then divided every cell into several triangles, next discussed the relationship between sensor radius and Voronoi edge \(l_{ij}\), then worked out the uncovered area in every cell, finally dispatched the assisted sensors to heal the coverage holes.