A novel review on various energy efficient routing algorithms in wireless sensor networks

  • Authors

    • Abhilasha Jain Associate Professor
    • Ashok Kumar Goel Professor
    2018-04-12
    https://doi.org/10.14419/ijet.v7i2.10709

  • In the past few decades, Wireless sensor networks have exhibited a significant amount of growth and have been used in various applications like traffic control, environment monitoring etc. It comprises an accumulation of sensor nodes that sense the data from their surroundings and relay it to the base station. The network suffers from the limited energy constraints since the sensor nodes are mobile nodes and they run out of battery after a considerable amount of time. To overcome this, a certain level of heterogeneity is introduced among the nodes in terms of energy consumption to sustain the overall network lifetime. Various protocols are developed to prolong the network longevity. Among those, PEGASIS (Power-Efficient Gathering in Sensor Information Systems) and LEACH (Low- Energy Adaptive Clustering Hierarchy) are the significant ones, which ensures power-efficient gathering of the data in the sensor networks. This paper attempts to discuss the different aspects of PEGASIS and LEACH and their advantages and disadvantages in detail.

  • References

    1. [1] Chandrakasan, A., Amirtharajah, R., Cho, S., Goodman, J., Konduri, G., Kulik, J. & Wang, A. (1999). Design considerations for distributed micro sensor systems. In Custom Integrated Circuits, 1999. Proceedings of the IEEE 1999 (pp. 279-286). IEEE. https://doi.org/10.1109/CICC.1999.777291.

      [2] Clare, L. P., Pottie, G. J., & Agre, J. R. (1999, July). Self-organizing distributed sensor networks. In Unattended Ground Sensor Technologies and Applications (Vol. 3713, pp. 229-238). International Society for Optics and Photonics. https://doi.org/10.1117/12.357138.

      [3] Dong, M. J., Yung, K. G., & Kaiser, W. J. (1997, August). Low power signal processing architectures for network micro sensors. In Proceedings of the 1997 international symposium on Low power electronics and design (pp. 173-177). ACM. https://doi.org/10.1145/263272.263320.

      [4] Srbinovski, B., Magno, M., O'Flynn, B., Pakrashi, V., & Popovici, E. (2015, April). Energy aware adaptive sampling algorithm for energy harvesting wireless sensor networks. In Sensors Applications Symposium (SAS), 2015 IEEE (pp. 1-6). IEEE.

      [5] Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: a survey. IEEE wireless communications, 11(6), 6-28 https://doi.org/10.1109/MWC.2004.1368893.

      [6] Sohraby, K., Minoli, D., & Znati, T. (2007). Wireless sensor networks: technology, protocols, and applications. John Wiley & Sons. https://doi.org/10.1002/047011276X.

      [7] Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January). Energy-efficient communication protocol for wireless micro sensor networks. In System sciences, 2000. Proceedings of the 33rd annual Hawaii international conference on (pp. 10-pp). IEEE.

      [8] Lindsey, S., & Raghavendra, C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. In Aerospace conference proceedings, 2002. IEEE (Vol. 3, pp. 3-3). IEEE. https://doi.org/10.1109/AERO.2002.1035242.

      [9] Chourse, L. K., Chaurse, D., & Chourse, P. (2012). A Review on Energy Efficient of Clustering-based Routing Protocol in Wireless Sensor Network. International Journal of Computer Applications, 50(16).

      [10] Xu, Z., Yin, Y., Wang, J., & Kim, J. U. (2014). A game-theoretic approach for efficient clustering in wireless sensor networks. International Journal of Hybrid Information Technology, 7(1), 67-80. https://doi.org/10.14257/ijhit.2014.7.1.06.

      [11] Yang, J., & Zhang, D. Y. (2009). A data transmission mechanism for wireless sensor networks using unequal clustering. Journal of Xi’an Jiaotong University, 43(4), 14-17.

      [12] Vidhyapriya, R., & Vanathi, P. T. (2007). Energy efficient adaptive multipath routing for wireless sensor networks. IAENG International Journal of Computer Science, 34(1).

      [13] Guo, W., Zhang, W., & Lu, G. (2010, March). PEGASIS protocol in wireless sensor network based on an improved ant colony algorithm. In Education Technology and Computer Science (ETCS), 2010 Second International Workshop on (Vol. 3, pp. 64-67). IEEE.

      [14] Linping, W., Wu, B., Zhen, C., & Zufeng, W. (2010, August). Improved algorithm of PEGASIS protocol introducing double cluster heads in wireless sensor network. In Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on (Vol. 1, pp. 148-151). IEEE. https://doi.org/10.1109/CMCE.2010.5609618.

      [15] Sen, F., Bing, Q., & Liangrui, T. (2011, July). An improved energy-efficient pegasis-based protocol in wireless sensor networks. In Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference On (Vol. 4, pp. 2230-2233). IEEE.

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  • How to Cite

    Jain, A., & Kumar Goel, A. (2018). A novel review on various energy efficient routing algorithms in wireless sensor networks. International Journal of Engineering & Technology, 7(2), 533-535. https://doi.org/10.14419/ijet.v7i2.10709