research-article

Dependability analysis of wireless sensor networks with active-sleep cycles and redundant nodes

Authors:

Dario Bruneo,

Antonio Puliafito,

Marco ScarpaAuthors Info & Claims

DYADEM-FTS '10: Proceedings of the First Workshop on DYnamic Aspects in DEpendability Models for Fault-Tolerant Systems

Pages 25 - 30

https://doi.org/10.1145/1772630.1772637

Published: 27 April 2010 Publication History

Get Access

Abstract

Wireless Sensor Networks (WSN) are constituted of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, battery-operated sensors undergo cycles of sleeping - active periods that reduce their ability to send/receive data. Starting from the Markov reward model theory, in this paper we present a dependability model to analyze the reliability of a sensor node. We also introduce a new dependability parameter, referred to as producibility, able to capture the capability of a sensor to accomplish its mission. Two different model solution techniques are proposed, one based on the evaluation of the accumulated reward distribution and the other based on an equivalent model based on non-Markovian Stochastic Petri nets. The obtained results are used to investigate the dependability of a whole WSN taking into account the presence of redundant nodes. Preliminary results are provided in order to highlight the advantages of the proposed technique.

References

[1]

K. Akkaya and M. Younis. A survey on routing protocols for wireless sensor networks. Elsevier Ad Hoc Networks, 3:325--349, 2005.

Crossref

Google Scholar

[2]

G. Anastasi, M. Conti, M. D. Francesco, and A. Passarella. How to prolong the lifetime of wireless sensor networks. Chapter 6 in Mobile Ad Hoc and Pervasive Communications, 2006.

Google Scholar

[3]

D. Bruneo, M. Scarpa, A. Bobbio, D. Cerotti, and M. Gribaudo. Analytical modeling of swarm intelligence in wireless sensor networks through Markovian Agents. In VALUETOOLS09. ICST/ACM, October 2009.

Digital Library

Google Scholar

[4]

G. Ciardo, R. German, and C. Lindemann. A characterization of the stochastic process underlying a stochastic petri net. IEEE Transactions on Software Engineering, 20(7):506--515, 1994.

Digital Library

Google Scholar

[5]

L. Cloth, M. Jongerden, and B. Haverkort. Computing battery lifetime distributions. In 37th International Conference on Dependable Systems and Networks. (DSN'07), pages 780--789, 2007.

Digital Library

Google Scholar

[6]

L. Donatiello and V. Grassi. On Evaluating the Cumulative Performance Distribution of Fault-Tolerant Systems. IEEE Transactions on Computer, 40(11):1301--1307, 1991.

Digital Library

Google Scholar

[7]

C. Jaggle, J. Neidig, T. Grosch, and F. Dressler. Introduction to Model-based ReliabilityEvaluation of Wireless Sensor Networks. In 2nd IFAC Workshop on Dependable Control of Discrete Systems, pages 149--154, June 2009.

Google Scholar

[8]

S. Mukhopadhyay, C. Schurgers, D. Panigrahi, and S. Dey. Model-Based Techniques for Data Reliability in Wireless Sensor Networks. IEEE Transactions on Mobile Computing, 8(4):528--543, 2009.

Digital Library

Google Scholar

[9]

T. S. Rappaport and T. Rappaport. Wireless Communications: Principles and Practice (2nd Edition). Prentice Hall PTR, December 2001.

Digital Library

Google Scholar

[10]

R. Sahner, K. S. Trivedi, and A. Puliafito. Performance and reliability analysis of computer systems: an example based approach using the SHARPE software package. Kluwer Academic Publishers, Boston, 1995.

Digital Library

Google Scholar

[11]

M. Scarpa, A. Puliafito, and S. Distefano. A parallel approach for the solution of non Markovian Petri nets. In 10th European PVM/MPI Users' Group Conference (EuroPVM/MPI03), pages 196--203, Venice, Italy, Sep. 2003. LNCS 2840.

Crossref

Google Scholar

[12]

K. S. Trivedi, A. Bobbio, G. Ciardo, R. German, A. Puliafito, and M. Telek. Non-markovian petri nets. SIGMETRICS Perform. Eval. Rev., 23(1):263--264, 1995.

Digital Library

Google Scholar

[13]

F. Zhao and L. Guibas. Wireless sensor networks - An information processing approach. Morgan Kaufmann, 2004.

Digital Library

Google Scholar

Cited By

View all

Soleimani Borujerdi ASanahmadi AAbdollahi Azgomi M(2024)Unified modeling and evaluation of availability and power consumption in the internet of thingsPeer-to-Peer Networking and Applications10.1007/s12083-024-01865-x18:2Online publication date: 30-Dec-2024
https://doi.org/10.1007/s12083-024-01865-x
Ahmed WHasan OPervez UQadir J(2017)Reliability modeling and analysis of communication networksJournal of Network and Computer Applications10.1016/j.jnca.2016.11.00878:C(191-215)Online publication date: 15-Jan-2017
https://dl.acm.org/doi/10.1016/j.jnca.2016.11.008
Dar KTaherkordi AEliassen F(2016)Enhancing Dependability of Cloud-Based IoT Services through Virtualization2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)10.1109/IoTDI.2015.38(106-116)Online publication date: Apr-2016
https://doi.org/10.1109/IoTDI.2015.38
Show More Cited By

Dependability analysis of wireless sensor networks with active-sleep cycles and redundant nodes
1. General and reference
  1. Cross-computing tools and techniques
2. Networks
  1. Network types

Recommendations

The reliability analysis of wireless sensor networks based on the energy restrictions

The Wireless Sensor Networks WSNs are composed of sensor nodes and sink nodes, and the network of sensor nodes is energy constrained, so the reliability of the WSNs is closely related to the energy of the nodes. According to the characteristics of the ...
Markov decision process-based analysis of rechargeable nodes in wireless sensor networks
SpringSim '10: Proceedings of the 2010 Spring Simulation Multiconference

Wireless Sensor Networks (WSNs) are popular nowadays for applications ranging from environmental monitoring to object tracking and surveillance. But the sensors which are deployed are energy constrained. The nodes in WSNs deplete of their very limited ...
Reliability of Sensor Nodes in Wireless Sensor Networks of Cyber Physical Systems

Sensors are a crucial component of any intelligent control system. Wireless sensor networks are one of the most rapidly developing information technologies and promise to have a variety of applications in Next Generation Networks, Internet of Things and ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

DYADEM-FTS '10: Proceedings of the First Workshop on DYnamic Aspects in DEpendability Models for Fault-Tolerant Systems

April 2010

45 pages

ISBN:9781605589169

DOI:10.1145/1772630

Conference Chair:
Arndt Bode
Technische Universitát Múnchen

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

IEEE Computer Society TC on Dependable Computing and Fault Tolerance
IFIP Working Group 10.4 Dependable Computing and Fault Tolerance
EWICS TC7 on Safety, Reliability and Security

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 April 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Ministero dell'Istruzione, dell'Università e della Ricerca

Conference

EDCC '10

Sponsor:

EDCC '10: European Dependable Computing Conference

April 27, 2010

Valencia, Spain

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

11
Total Citations
View Citations
293
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Soleimani Borujerdi ASanahmadi AAbdollahi Azgomi M(2024)Unified modeling and evaluation of availability and power consumption in the internet of thingsPeer-to-Peer Networking and Applications10.1007/s12083-024-01865-x18:2Online publication date: 30-Dec-2024
https://doi.org/10.1007/s12083-024-01865-x
Ahmed WHasan OPervez UQadir J(2017)Reliability modeling and analysis of communication networksJournal of Network and Computer Applications10.1016/j.jnca.2016.11.00878:C(191-215)Online publication date: 15-Jan-2017
https://dl.acm.org/doi/10.1016/j.jnca.2016.11.008
Dar KTaherkordi AEliassen F(2016)Enhancing Dependability of Cloud-Based IoT Services through Virtualization2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)10.1109/IoTDI.2015.38(106-116)Online publication date: Apr-2016
https://doi.org/10.1109/IoTDI.2015.38
Fazio MPuliafito AVillari M(2014)IoT4SInternational Journal of Web and Grid Services10.1504/IJWGS.2014.06025510:2/3(114-138)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1504/IJWGS.2014.060255
Fazio MMerlino GBruneo DPuliafito A(2013)An Architecture for Runtime Customization of Smart Devices2013 IEEE 12th International Symposium on Network Computing and Applications10.1109/NCA.2013.39(157-164)Online publication date: Aug-2013
https://doi.org/10.1109/NCA.2013.39
Attiah AAkbas MChatterjee MTurgut D(2013)EE-MAC: Energy efficient sensor MAC layer protocol38th Annual IEEE Conference on Local Computer Networks - Workshops10.1109/LCNW.2013.6758507(116-119)Online publication date: Oct-2013
https://doi.org/10.1109/LCNW.2013.6758507
Distefano SMerlino GPuliafito A(2013)Towards the Cloud of Things Sensing and Actuation as a Service, a Key Enabler for a New Cloud ParadigmProceedings of the 2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing10.1109/3PGCIC.2013.16(60-67)Online publication date: 28-Oct-2013
https://dl.acm.org/doi/10.1109/3PGCIC.2013.16
Distefano S(2013)Evaluating reliability of WSN with sleep/wake-up interfering nodesInternational Journal of Systems Science10.1080/00207721.2012.67029344:10(1793-1806)Online publication date: 1-Oct-2013
https://dl.acm.org/doi/10.1080/00207721.2012.670293
Silva IGuedes LPortugal PVasques F(2012)Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial ApplicationsSensors10.3390/s12010080612:1(806-838)Online publication date: 12-Jan-2012
https://doi.org/10.3390/s120100806
Bruneo DCucinotta AMinnolo APuliafito AScarpa M(2012)Energy Management in Industrial PlantsComputers10.3390/computers10100241:1(24-40)Online publication date: 13-Sep-2012
https://doi.org/10.3390/computers1010024
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Recommendations

The reliability analysis of wireless sensor networks based on the energy restrictions

Markov decision process-based analysis of rechargeable nodes in wireless sensor networks

Reliability of Sensor Nodes in Wireless Sensor Networks of Cyber Physical Systems

Comments

Information

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Funding Sources

Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations