Sensor networks deployment using flip-based sensors

Abstract

In this paper, we study the issue of mobility based sensor networks deployment. The distinguishing feature of our work is that the sensors in our model have limited mobilities. More specifically, the mobility in the sensors we consider is restricted to a flip, where the distance of the flip is bounded. Given an initial deployment of sensors in a field, our problem is to determine a movement plan for the sensors in order to maximize the sensor network coverage, and minimize the number of flips. We propose a minimum-cost maximum-flow based solution to this problem. We prove that our solution optimizes both the coverage and the number of flips. We also study the sensitivity of coverage and the number of flips to flip distance under different initial deployment distributions of sensors. We observe that increased flip distance achieves better coverage, and reduces the number of flips required per unit increase in coverage. However, such improvements are constrained by initial deployment distributions of sensors, due to the limitations on sensor mobility.

Focused-coverage by mobile sensor networks

“…Chellappan et al [3] presented a centralized algorithm for mobility-limited sensors. They divide the target field into weighted regions and model the sensor self-deployment problem as a minimum-cost maximum-flow problem.…”

Dynamic Cooperative Coevolutionary Sensor Deployment Via Localized Fitness Evaluation

“…We have implemented the DCC concept to solve the autonomous sensor deployment problem 1 . DCC consists of 3 major stages: planning, computing, and moving.…”

“…Chellappan et al [1] proposed a flip-based algorithm to optimize both the coverage and the total number of flips. More recently, it has been demonstrated that computational intelligence techniques, such as fuzzy logic [8] and swarm intelligence [12] can be effective in sensor deployment.…”

An Integrated Self-deployment and Coverage Maintenance Scheme for Mobile Sensor Networks

“…One is the most commonly used binary sensor model [1,2,[4][5][6][7][8][9][10]. In this model, a sensor detects with probability 1 (resp., 0) the target events happening inside (resp., outside) its sensing range, a disc centered at itself.…”

“…There are two main streams of algorithms, i.e., sensor self-deployment [1][2][3][4][5][6][7] and sensor relocation [8][9][10], for coverage improvement in MSNs. Other streams include, for example, robot-assisted approaches [11,12].…”