Nothing Special   »   [go: up one dir, main page]

skip to main content
article

A stable energy efficient clustering protocol for wireless sensor networks

Published: 01 August 2017 Publication History

Abstract

Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.

References

[1]
Afsar, M. M., & Tayarani-N, M. (2014). Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications,46, 198---226.
[2]
Pantazis, N. A., Nikolidakis, S. A., & Vergados, D. D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications, Surveys & Tutorials,15(2), 551---591.
[3]
Memon, I., Jamro, D. A., Mangi, F. A., Basit, M. A., & Memon, M. H. (2013). Source localization wireless sensor network using time difference of arrivals (TDOA). International Journal of Scientific & Engineering Research,4(7), 1046.
[4]
Memon, I., Hussain, I., Akhtar, R., & Chen, G. (2015). Enhanced privacy and authentication: An efficient and secure anonymous communication for location based service using asymmetric cryptography scheme. Wireless Personal Communications,84, 1487---1508.
[5]
Memon, I. (2015). A secure and efficient communication scheme with authenticated key establishment protocol for road networks. Wireless Personal Communications,85, 1167---1191.
[6]
Heinzelman, W. B., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Annual Hawaii international conference on system siences (HICSS-33) (p. 223), IEEE.
[7]
Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. In Proceedings of the international workshop on SANPA.http://open.bu.edu/xmlui/bitstream/handle/2144/1548/2004-022-sep.pdf?sequence=1.
[8]
Kumar, D., Aseri, T. C., & Patel, R. B. (2009). EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications,32, 662---667.
[9]
Tyagi, S., & Kumar, N. (2013). A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks. Journal of Network and Computer Applications,36(2), 623---645.
[10]
Kumar, D. (2014). Performance analysis of energy efficient clustering protocols for maximising lifetime of wireless sensor networks. IET Wireless Sensor Systems,4(1), 9---16.
[11]
Kang, S. H., & Nguyen, T. (2012). Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Communications Letters,16(9), 1396---1399.
[12]
Tarhani, M., Kavian, Y. S., & Siavoshi, S. (2014). SEECH: Scalable energy efficient clustering hierarchy protocol in wireless sensor networks. IEEE Sensors Journal,14(11), 3944---3954.
[13]
Mahajan, S., Malhotra, J., & Sharma, S. (2014). An energy balanced QoS based cluster head selection strategy for WSN. Egyptian Informatics Journal,15, 189---199.
[14]
Aderohunmu, F. A., Deng, J. D., & Purvis, M. K. (2011). A deterministic energy-efficient clustering protocol for wireless sensor networks. In Proceedings of the 7th international conference on intelligent sensors, sensor networks and information processing (ISSNIP `11) (pp. 341---346), IEEE.
[15]
Manjeshwar, A., & Agrawal, D. P. (2001). TEEN: A routing protocol for enhanced efficiency in wireless sensor networks. In Proceedings of international parallel and distributed processing symposium (IPDPS'01) workshops (pp. 2009---2015), San Francisco, CA, USA.
[16]
Kashaf, A., Javaid, N., Khan, Z.A., & Khan, I.A. (December, 2012). TSEP: Threshold-sensitive stable election protocol for WSNs. In Proceedings of 10th international conference on frontiers of information technology (pp. 164---168), IEEE, Islamabad.
[17]
Mittal, N., & Singh, U. (2015). Distance-based residual energy-efficient stable election protocol for WSNs. Arabian Journal for Science and Engineering,40, 1637---1646.
[18]
Amini, N., Vahdatpour, A., Xu, W., Gerla, M., & Sarrafzadeh, M. (2012). Cluster size optimization in sensor networks with decentralized cluster-based protocols. Computer Communications,35, 207---220.
[19]
Rappaport, T. (1996). Wireless communications: Principles & practice. Englewood Cliffs, NJ: Prentice-Hall.
[20]
Karl, H., & Willig, A. (2005). Protocols and architectures for wireless sensor networks. Hoboken: Wiley.

Cited By

View all
  • (2024)Threshold-driven K-means sector clustering algorithm for wireless sensor networksEURASIP Journal on Wireless Communications and Networking10.1186/s13638-024-02403-22024:1Online publication date: 4-Sep-2024
  • (2024)Data fusion algorithm of wireless sensor network based on clustering and fuzzy logicTelecommunications Systems10.1007/s11235-024-01141-686:4(617-626)Online publication date: 1-Aug-2024
  • (2022)EE-WCA: Energy Efficient Weighted Clustering Algorithm to Regulate Application’s Quality of Service RequirementsWireless Personal Communications: An International Journal10.1007/s11277-022-09531-2124:4(3647-3660)Online publication date: 1-Jun-2022
  • Show More Cited By
  1. A stable energy efficient clustering protocol for wireless sensor networks

      Recommendations

      Comments

      Please enable JavaScript to view thecomments powered by Disqus.

      Information & Contributors

      Information

      Published In

      cover image Wireless Networks
      Wireless Networks  Volume 23, Issue 6
      August 2017
      328 pages

      Publisher

      Springer-Verlag

      Berlin, Heidelberg

      Publication History

      Published: 01 August 2017

      Author Tags

      1. Clustering
      2. DRESEP
      3. Network lifetime
      4. Residual energy
      5. SEECP
      6. WSNs

      Qualifiers

      • Article

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)0
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 27 Nov 2024

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)Threshold-driven K-means sector clustering algorithm for wireless sensor networksEURASIP Journal on Wireless Communications and Networking10.1186/s13638-024-02403-22024:1Online publication date: 4-Sep-2024
      • (2024)Data fusion algorithm of wireless sensor network based on clustering and fuzzy logicTelecommunications Systems10.1007/s11235-024-01141-686:4(617-626)Online publication date: 1-Aug-2024
      • (2022)EE-WCA: Energy Efficient Weighted Clustering Algorithm to Regulate Application’s Quality of Service RequirementsWireless Personal Communications: An International Journal10.1007/s11277-022-09531-2124:4(3647-3660)Online publication date: 1-Jun-2022
      • (2022)An Intrusion Detection and Prevention Protocol for Internet of Things Based Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-022-09521-4124:4(3461-3483)Online publication date: 1-Jun-2022
      • (2022)EDCCS: effective deterministic clustering scheme based compressive sensing to enhance IoT based WSNsWireless Networks10.1007/s11276-022-02973-328:6(2375-2391)Online publication date: 1-Aug-2022
      • (2021)Trust-aware energy-efficient stable clustering approach using fuzzy type-2 Cuckoo search optimization algorithm for wireless sensor networksWireless Networks10.1007/s11276-020-02438-527:1(151-174)Online publication date: 1-Jan-2021
      • (2021)EOCGS: energy efficient optimum number of cluster head and grid head selection in wireless sensor networksTelecommunications Systems10.1007/s11235-021-00782-178:1(1-13)Online publication date: 1-Sep-2021
      • (2021)EDVWDD: Event-Driven Virtual Wheel-based Data Dissemination for Mobile Sink-Enabled Wireless Sensor NetworksThe Journal of Supercomputing10.1007/s11227-021-03714-777:10(11432-11457)Online publication date: 1-Oct-2021
      • (2021)Energy-efficient cluster head selection through relay approach for WSNThe Journal of Supercomputing10.1007/s11227-020-03593-477:7(7649-7675)Online publication date: 1-Jul-2021
      • (2020)An Efficient QoS Based Data Packet Transmission in Wireless Sensor Networks Using OREAWireless Personal Communications: An International Journal10.1007/s11277-020-07295-1113:4(1839-1850)Online publication date: 1-Aug-2020
      • Show More Cited By

      View Options

      View options

      Login options

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media