Deploying Wireless Sensor Networks under Limited Mobility Constraints

Abstract

In this paper, we study the issue of sensor network deployment using limited mobility sensors. By limited mobility, we mean that the maximum distance that sensors are capable of moving to is limited. Given an initial deployment of limited mobility sensors in a field clustered into multiple regions, our deployment problem is to determine a movement plan for the sensors to minimize the variance in number of sensors among the regions and simultaneously minimize the sensor movements. Our methodology to solve this problem is to transfer the nonlinear variance/movement minimization problem into a linear optimization problem through appropriate weight assignments to regions. In this methodology, the regions are assigned weights corresponding to the number of sensors needed. During sensor movements across regions, larger weight regions are given higher priority compared to smaller weight regions, while simultaneously ensuring a minimum number of sensor movements. Following the above methodology, we propose a set of algorithms to our deployment problem. Our first algorithm is the Optimal Maximum Flow-based (OMF) centralized algorithm. Here, the optimal movement plan for sensors is obtained based on determining the minimum cost maximum weighted flow to the regions in the network. We then propose the Simple Peak-Pit-based distributed (SPP) algorithm that uses local requests and responses for sensor movements. Using extensive simulations, we demonstrate the effectiveness of our algorithms from the perspective of variance minimization, number of sensor movements, and messaging overhead under different initial deployment scenarios.

Nodes self-deployment for coverage maximization in mobile robot networks using an evolving neural network

“…Concerning the Grid quorum based movement [4], typically the sensors field is partitioned into many cells and the number of sensors in a cell is the load of the cell. Coverage and connectivity depend on the size of the cell.…”

“…Nodes deployment is a critical issue for coverage, because it affects costs and detection capability of a WSRN. In literature, existing nodes deployment algorithms can be classified into the following categories: 1) Stationary sensors [2], [3] 2) Mobile Sensors [4] [5] and 3) Mobile Robot [6] [7]. Usually stationary sensors are random deployed in the area of interest.…”

“…Furthermore, a random deployment of static nodes could be inefficient since some areas could be densely deployed in respect of others and some coverage holes or network partitions can occur. In some work [4] [5], a large number of stationary nodes and a few mobile sensors are considered. Unfortunately, when the initial deployment of static nodes is random, this kind of approach is not useful to overcome the hole problems.…”

Points of Interest Coverage with Connectivity Constraints Using Wireless Mobile Sensors

“…Moreover, we consider the deployment of mobile sensors but more interested readers can refer to [6,13] for static random deployment strategies, to [10,3] for off-line computation of sensor placement and to [18] or [15] for complete surveys. There are mainly three ways to optimize the deployment or the placement of mobile sensors: the coverage pattern [16], grid quorum [7] and virtual force based movements [5]. This paper belongs to the virtual force based movement category, where sensors are repelled or attracted each other by using virtual forces like electromagnetic particles.…”

Collaborative Target Detection in Wireless Sensor Networks with Reactive Mobility

“…Several projects proposed to eliminate coverage holes in a sensing field by relocating mobile sensors [8], [9], [10]. Although such an approach improves the sensing coverage of the initial network deployment, it does not dynamically improve the network's performance after targets of interest appear.…”