Next Article in Journal
Creating Affording Situations: Coaching through Animate Objects
Next Article in Special Issue
Comparing the Performance of Indoor Localization Systems through the EvAAL Framework
Previous Article in Journal
A Reliable and Real-Time Tracking Method with Color Distribution
Previous Article in Special Issue
Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter
Article Menu

Export Article

Open AccessArticle
Sensors 2017, 17(10), 2304; doi:10.3390/s17102304

On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space

1
Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA
2
College of Engineering, Xi’an International University, Xi’an 710077, Shaanxi, China
This paper is an extended version of our paper published in Lin, Y.;Wu, Q. Approximate Algorithms for Sensor Deployment with k-coverage in Constrained 3D Space. In Proceedings of the 16th International Conference on Parallel and Distributed Systems, Shanghai, China, 8–10 December 2010.
*
Author to whom correspondence should be addressed.
Received: 10 September 2017 / Revised: 3 October 2017 / Accepted: 6 October 2017 / Published: 10 October 2017
View Full-Text   |   Download PDF [493 KB, uploaded 12 October 2017]   |  

Abstract

Sensor networks have been used in a rapidly increasing number of applications in many fields. This work generalizes a sensor deployment problem to place a minimum set of wireless sensors at candidate locations in constrained 3D space to k-cover a given set of target objects. By exhausting the combinations of discreteness/continuousness constraints on either sensor locations or target objects, we formulate four classes of sensor deployment problems in 3D space: deploy sensors at Discrete/Continuous Locations (D/CL) to cover Discrete/Continuous Targets (D/CT). We begin with the design of an approximate algorithm for DLDT and then reduce DLCT, CLDT, and CLCT to DLDT by discretizing continuous sensor locations or target objects into a set of divisions without sacrificing sensing precision. Furthermore, we consider a connected version of each problem where the deployed sensors must form a connected network, and design an approximation algorithm to minimize the number of deployed sensors with connectivity guarantee. For performance comparison, we design and implement an optimal solution and a genetic algorithm (GA)-based approach. Extensive simulation results show that the proposed deployment algorithms consistently outperform the GA-based heuristic and achieve a close-to-optimal performance in small-scale problem instances and a significantly superior overall performance than the theoretical upper bound. View Full-Text
Keywords: sensor deployment; network connectivity; k-coverage; approximation algorithm sensor deployment; network connectivity; k-coverage; approximation algorithm
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wu, C.Q.; Wang, L. On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space. Sensors 2017, 17, 2304.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top