Abstract-Providing field coverage is a key issue in many and thus making the area even sparser. In an extreme case, sensor network applications. For a field with unevenly distributed an area will be uncovered by any sensor, leaving a hole in static sensors, a quality coverage with acceptable network lifetime the field. Unfortunately, such unfavorable sensor distributions is often difficult to achieve. We propose a hybrid network that . . ' consists of both static and mobile sensors, and we suggest are nevtable n many applcations where a well-controlled or that it can be a cost-effective solution for field coverage. The manual deployment is not practical. main challenges of designing such a hybrid network are, first, Recent advances of embedded hardware and robot have determining necessary coverage contributions from each type of made mobile sensors possible. The mobile sensors have the sensors; and second, scheduling the sensors to achieve the desired same sensing capability as static sensors, but are able to move coverage contributions, which includes activation scheduling for in a field, and their batteries are generally rechargeable. In static sensors and movement scheduling for mobile sensors. In this paper, we offer an analytical study on the above other words, their lifetime is not bounded by the limited problems, and the results also lead to a practical system design. battery. While fully mobile sensor networks remain expensive Specifically, we present an optimal algorithm for calculating and are complicated by information exchange, we envision that the contributions from different types of sensors, which fully a hybrid network with both static and mobile nodes can be a exploits the potentials of the mobile sensors and maximizes the network lifetime. We then present a random walk model for the costf i r c ragewth unevenly distributed senmobile sensors. The model is distributed with very low control sors. A related design was presented in [19], which suggested overhead. Its parameters can be fine-tuned to match the moving a one-time reposition of the mobile sensors after the initial capability of different mobile sensors and the demands from a deployment. This solution, however, proves inadequate for broad spectrum of applications. A node collaboration scheme is balancing the sensor coverage and load in many applications. then introduced to further enhance the system performance. Consider Fig. 1 , where there are a number of static sensors and We demonstrate through analysis and simulation that, in our hybrid design, a small set of mobile sensors can effectively address three mobile sensors to cover a field. Each sensor can cover the uneven distribution of the static sensors and significantly its associated grid. If there are no mobile sensors, grid 6 will improve the coverage quality. never be covered. If only one-time repositioning for the mobile sensors is employed, the coverage can be enhanced, but there will still remain grids with permanently fewer sensors. In this paper we propose a hybrid sensor network which Wireless sensor networks have recently been suggested fully exploits the movement capability of the mobile sensors. for many protection and surveillance applications. One key In our solution, the mobile sensors are always in motion to objective of these applications is to detect abnormal events in assist the static sensors; the occurrence probability of the a sensing field, which depends on the coverage quality of the mobile sensors in each grid, or their contribution for covering sensor network. The k-coverage is a common criterion, where the grid, is adaptively determined according to the network any point in the sensor field should be covered by k sensors configuration. From a statistical point of view, the overall [18]. For many applications, it turns out that a deterministic coverage is enhanced, and energy consumption of the static k-coverage is too expensive and not necessary. Therefore, sensors is more balanced. probabilistic coverage [7][22] is introduced and every point The main challenges in designing such a hybrid network is covered with certain probability ratio. This ratio tunes the are, first, to clarify the necessary coverage contributions from coverage quality and allows the sensors to switch between the static and mobile sensors; and second, to find a mobility sleeping and working states. model for the mobile sensors to achieve their desired coverage In these studies, only static sensors are used. The quality of contribution. In this paper, we for the first time offer an coverage is noticeably affected by the initial deployment of the analytical study on the above problems, and the results also sensors. For uneven sensor distributions, the sensors in a sparse lead to a practical system design. Specifically, we present an area may have to stay active longer to ensure the coverage optimal algorithm for calculating the contributions, which fully quality. The batteries of these sensors will be depleted earlier explores the potentials of the mobile sensors and maximizes 1-4244-1 185-8/07/$25.00
Wang et al. REF proposed a hybrid network of static sensors and mobile sensors with a random walk model and showed that a small set of mobile sensors can effectively address the uneven distribution of the static sensors so as to improve the field coverage quality.
Probabilistic Field Coverage using a Hybrid Network of Static and Mobile Sensors
2007 Fifteenth IEEE International Workshop on Quality of Service
2007 Fifteenth IEEE International Workshop on Quality of Service
Engineering Computer Science