Next Article in Journal
Portable Solid Phase Micro-Extraction Coupled with Ion Mobility Spectrometry System for On-Site Analysis of Chemical Warfare Agents and Simulants in Water Samples
Previous Article in Journal
Temperature-Independent Fiber Inclinometer Based on Orthogonally Polarized Modes Coupling Using a Polarization-Maintaining Fiber Bragg Grating
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(11), 20940-20962; doi:10.3390/s141120940

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

1
College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
2
Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35401, USA
3
Instituto de Investigación Para la Gestión Integrada de Zonas Costeras, Universidad Politécnica de Valencia, C/ Paranimf nº 1, Grao de Gandia, Gandia, Valencia 46730, Spain
4
Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou University, Fuzhou 350108, China
*
Author to whom correspondence should be addressed.
Received: 3 August 2014 / Revised: 1 October 2014 / Accepted: 28 October 2014 / Published: 6 November 2014
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [1409 KB, uploaded 6 November 2014]   |  

Abstract

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. View Full-Text
Keywords: wireless sensor networks; service-oriented; multi-service; node scheduling; Markov Random Field; energy efficiency wireless sensor networks; service-oriented; multi-service; node scheduling; Markov Random Field; energy efficiency
Figures

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

Cheng, H.; Su, Z.; Lloret, J.; Chen, G. Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model. Sensors 2014, 14, 20940-20962.

Show more citation formats Show less citations formats

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