Skip to main content

Advertisement

SpringerLink
Log in

A Differential Indexing Approach for Wireless Sensor Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In wireless sensor networks (WSNs), the sensor nodes (SNs) have batteries with limited energy. Therefore, the energy consumption must be reduced in order to make the batteries live longer. In this paper, a differential indexing approach is proposed to reduce the consumed energy and as a result the batteries of SNs will last longer. This approach first assigns an index for each possible value for a sensed reading. Then, it starts giving a number for each sensed reading. For each newly sensed reading, this number is increased by one. When the SN wants to send a sensed reading, it sends its location in the lookup table represented by the least number of bits (which will have shorter length than the length of corresponding index for the sensed reading in the indexing table), if it exists in the lookup table. Otherwise, it sends the corresponding index for this sensed reading in the indexing table. The evaluation shows that the differential indexing approach has better performance than the non-indexing and index-based approaches in terms of total energy consumption and total elapsed time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Bsoul, M., Kilani, Y., Hammad, M., Abdallah, E. E., & Alsarhan, A. (2015). An index-based approach for wireless sensor networks. Wireless Personal Communications, 82(4), 2185–2197.

    Article  Google Scholar 

  2. Gong, P., Chen, T., & Xu, Q. (2015). ETARP: An energy efficient trust-aware routing protocol for wireless sensor networks. Journal of Sensors, 2015, 1–10.

    Article  Google Scholar 

  3. Heinzelman, W., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Hawaii International Conference on System Sciences, Maui, Hawaii (pp. 3005–3014).

  4. Bsoul, M., Al-Khasawneh, A., Abdallah, A. E., Abdallah, E. E., & Obeidat, I. (2013). An energy-efficient threshold-based clustering protocol for wireless sensor networks. Wireless Personal Communications, 70(1), 99–112.

    Article  Google Scholar 

  5. Azharuddin, M., & Jana, P. (2015). A distributed algorithm for energy efficient and fault tolerant routing in wireless sensor networks. Wireless Networks, 21(1), 251–267.

    Article  Google Scholar 

  6. Zhang, H., Li, L., Yan, X., & Li, X. (2011). A load-balancing clustering algorithm of wsn for data gathering. In Proceedings of the 2011 2nd international conference on artificial intelligence, management science and electronic commerce, Deng Feng, China (pp. 915–918).

  7. Nikolidakis, S., Kandris, D., Vergados, D., & Douligeris, C. (2013). Energy efficient routing in wireless sensor networks through balanced clustering. Algorithms, 6(1), 29–42.

    Article  MathSciNet  Google Scholar 

  8. Yessad, S., Bouallouche-Medjkoune, L., & Assani, D. (2015). A cross-layer routing protocol for balancing energy consumption in wireless sensor networks. Wireless Personal Communications, 81(3), 1303–1320.

    Article  Google Scholar 

  9. Oliveira, H., Boukerche, A., Guidoni, D., Nakamura, E., Mini, R., & Loureiro, A. (2015). An enhanced location-free greedy forward algorithm with hole bypass capability in wireless sensor networks. Journal of Parallel and Distributed Computing, 77, 1–10.

    Article  Google Scholar 

  10. Chatterjee, M., Das, S., & Turgut, D. (2002). WCA: a weighted clustering algorithm for mobile ad hoc networks. Cluster Computing, 5(2), 193–204.

    Article  Google Scholar 

  11. Low, C., Fang, C., Ng, J., & Ang, Y. (2008). Efficient load-balanced clustering algorithms for wireless sensor networks. Computer Communications, 31(4), 750–759.

    Article  Google Scholar 

  12. Wei, D., & Chan, H. (2007). Clustering algorithm to balance and to reduce power consumptions for homogeneous sensor networks. In International conference on wireless communications, networking and mobile computing (pp. 2723–2726).

  13. Ducrocq, T., Hauspie, M., & Mitton, N. (2013). Balancing energy consumption in clustered wireless sensor networks. ISRN Sensor Networks, 2013(314732), 1–14.

    Article  Google Scholar 

  14. Chakraborty, A., Chakraborty, K., Mitra, S., & Naskar, M. (2009). An energy efficient scheme for data gathering in wireless sensor networks using particle swarm optimization. Journal of Applied Computer Science, 3(6), 9–13.

    Google Scholar 

  15. Lin, C., Huang, C., & Fang, R. (2008). A power-efficient data gathering scheme on grid sensor networks. In Proceedings of the 8th WSEAS international conference on multimedia systems and signal processing, Hangzhou, China (pp. 142–147).

  16. Chuang, P., Li, B., & Chao, T. (2007). Hypercube-based data gathering in wireless sensor networks. Journal of Information Science and Engineering, 23(4), 1155–1170.

    Google Scholar 

  17. Gao, C., Zhao, G., Pan, S., & Zhou, J. (2009). Distributed multi-weight data-gathering and aggregation protocol in fleet wireless sensor networks: Optimal and heuristic algorithms. International Journal of Distributed Sensor Networks, 2(4), 1–8.

    Google Scholar 

  18. Seetharam, A., Acharya, A., Bhattacharyya, A., & Naskar, M. (2009). Energy efficient data gathering schemes in wireless sensor networks using ant colony optimization. Journal of Applied Computer Science and Mathematics, 3(5), 19–28.

    Google Scholar 

  19. Zhu, Y., Wu, W., Pan, J., & Tang, Y. (2010). An energy-efficient data gathering algorithm to prolong lifetime of wireless sensor networks. Computer Communications, 33(5), 639–647.

    Article  Google Scholar 

  20. Duarte-Melo, E., & Liu, M. (2002). Analysis of energy consumption and lifetime of heterogeneous wireless sensor networks. In IEEE Global Telecommunications Conference, Taipei, Taiwan (pp. 21–25).

  21. Lee, N., Levis, P., & Hill, J. (2002). Mica high speed radio stack. http://www.tinyos.net/tinyos-1.x/doc/stack.pdf.

  22. Wen, Y. (2004). Smart dust sensor mote characterization, validation, fusion and actuation: Research report, 2004 (Online). Available: http://books.google.jo/books?id=6oJlHwAACAAJ.

  23. Shi, L., Han, J., Shi, Y., & Wei, Z. (2010). Cross-layer optimization for wireless sensor network with multi-packet reception. In ICST conference on communications and networking, Beijing, China.

  24. Chao, L., & Aiqun, H. (2007). Reducing the message overhead of AODV by using link availability prediction. In Proceedings of the 3rd International conference on Mobile Ad-Hoc and sensor networks, MSN 2007, Beijing, China. December 12–14, 2007 (pp. 113–122).

  25. Nazi, A., Raj, M., Francesco, M., Ghosh, P., & Das, S. (2014). Deployment of robust wireless sensor networks using gene regulatory networks: An isomorphism-based approach. Pervasive and Mobile Computing, 13, 246–257.

    Article  Google Scholar 

  26. Ning, X., & Cassandras, C. G. (2006). Dynamic sleep time control in event-driven wireless sensor networks. In Proceedings of the 45th IEEE Conference on Decision and Control, California, USA (pp. 2722–2727).

Download references

Author information

Authors and Affiliations

  1. Hashemite University, P.O. Box 150459, Zarqa, 13115, Jordan

    Mohammad Bsoul

Authors
  1. Mohammad Bsoul
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Bsoul.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bsoul, M. A Differential Indexing Approach for Wireless Sensor Networks. Wireless Pers Commun 97, 2649–2663 (2017). https://doi.org/10.1007/s11277-017-4628-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4628-y

Keywords

Search

Navigation