Open Access Open Access  Restricted Access Subscription Access

Energy Efficient Routing Clustering Algorithms For Wireless Sensor Networks


Affiliations
1 Sambhram Institute of Technology, Bangalore, VTU Belagavi Karnataka, India
 

Wireless Sensor Networks have come to the forefront of the scientific community recently and it consists of small nodes with sensing, Communications and computing capabilities. The Wireless Sensor Network Systems can be applied to monitor different environments. In WSN, sensor nodes play the most prominent role. These sensor nodes batteries are replacing or recharging is impossible, it is essential to find energy efficient routing algorithm. In this paper, we survey the features / characteristics and different well-know energy efficient cluster routing algorithms for WSNs have been classified and presented based on their characteristics.

Keywords

Wireless Sensor Networks (WSN), Clustering, Energy Efficiency, Distributed Cluster Routing Algorithms, Centralized Cluster Routing Algorithms, Uni-Form Distribution.
User
Notifications
Font Size

  • I. F. Akyildiz, S. Weilian, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” IEEE Communications Magazine, vol. 40, no. 8, pp. 102–114, 2002.
  • W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” in 33rd Annual Hawaii International Conference on System Sciences, 2000.
  • M. M. Zanjireh, A. Shahrabi, and H. Larijani, “ANCH: A New Clus-tering Algorithm for Wireless Sensor Networks,” in 27th International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp. 450–455, IEEE, 2013.
  • M. Mathew and N. Weng, “Quality of Information and Energy Efficiency Optimization for Sensor Networks via Adaptive Sensing and Transmit-ting,” IEEE Sensors Journal, vol. 14, pp. 341–348, February 2014.
  • G. Anastasi, A. Falchi, A. Passarella, M. Conti, and E. Gregori, “Performance Measurements of Motes Sensor Networks,” in 7th ACM International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), (Venice, Italy), pp. 174–181, ACM, 2004
  • Karl, H., & Willig, A. (2005). Protocols and architectures for wireless sensor networks. Hoboken, NJ: Wiley.
  • Chan, H., & Perrig, A. (2004). ACE: An emergent algorithm for highly uniform cluster formation. In Wireless Sensor Networks. Lecture Notes in Computer Science, Vol. 2920, pp. 154–171.
  • Low, C. P., Fang, C., Ng, J. M., & Ang, Y. H. (2008). Efficient load-balanced clustering algorithms for wireless sensor networks. Computer Communications, 31(4), 750–759.
  • Manjeshwar, A., & Agrawal, D. P. (2002). APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In Proceedings International Parallel and Distributed Processing Symposium, IPDPS 2002 (pp. 195–202).
  • Gu, Y., Wu, Q., & Rao, N. S. V. (2010). Optimizing cluster heads for energy efficiency in large-scale heterogeneous wireless sensor networks. International Journal of Distributed Sensor Networks. doi:10.1155/2010/961591.
  • Rajkumar, Dr H G Chandrakanth, Dr D G Anand, and Dr T John Peter.” Research Challenges and Characteristic Features in Wireless Sensor Networks”, in Int. J. Advanced Networking and Applications, Volume: 09 Issue: 01 Pages: 3321-3328 (2017) ISSN: 0975-0290.
  • Tarannum, S., Srividya, S., Asha, D. S., Padmini, R., Nalini, L., Venugopal, K. R., et al. (2008). Dynamic hierarchical communication paradigm for Wireless Sensor Networks: A centralized, energy efficient approach. In 11th IEEE Singapore International Conference on Communication Systems, Singapore (pp. 959–963).
  • Ci, S., Guizani, M., & Sharif, H. (2007). Adaptive clustering in wireless sensor networks by mining sensor energy data. Computer Communications, 30(14–15), 2968–2975.
  • Huang, Y. F., Luo, W. H., Sum, J., Chang, L. H., Chang, C. W., & Chen, R. C. (2007). Lifetime Performance of an energy efficient clustering algorithm for cluster-based wireless sensor networks. In Frontiers of High Performance Computing and Networking ISPA 2007 Workshops. Lecture Notes in Computer Science, Vol. 4743, pp. 455–464.
  • M. M. Zanjireh, H. Larijani, and W. O. Popoola, “Energy Based Analytical Modelling of ANCH Clustering Algorithm for Wireless Sensor Networks,” International Journal On Advances in Networks and Services, vol. 7, no. 3&4, pp. 173–182, 2014.
  • O. Younis and S. Fahmy, “HEED: A Hybrid, Energy-Efficient, Dis-tributed Clustering Approach for Ad Hoc Sensor Networks,” IEEE Transactions on Mobile Computing, vol. 3, no. 4, pp. 366–379, 2004.
  • M. Ilyas and I. Mahgoub, Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems. CRC press, 2004.
  • L. Benyuan, O. Dousse, P. Nain, and D. Towsley, “Dynamic Cover-age of Mobile Sensor Networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 24, pp. 301–311, February 2013.
  • O. Younis, M. Krunz, and S. Ramasubramanian, “Location-unaware coverage in wireless sensor networks,” Ad Hoc Networks, vol. 6, no. 7, pp. 1078– 1097, 2008.
  • Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366–379.
  • Manjeshwar, A., & Agrawal, D. P. (2001). TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. In Proceedings of the 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, San Francisco, CA (pp. 2009-2015).
  • Ye, M., Li, C., Chen, G., & Wu, J. (2005). EECS: An energy efficient clustering scheme in wireless sensor networks. In 24th IEEE International Performance, Computing, and Communications Conference, IPCCC 2005 (pp. 535–540).
  • Kamimura, J., Wakamiya, N., & Murata, M. (2006). A distributed clustering method for energy-efficient data gathering in sensor networks. International Journal of Wireless and Mobile Computing, 1(2), 113–120.
  • Zhang, M., Gong, C., & Lu, Y. (2008). An novel dynamic clustering algorithm based on geographical location for wireless sensor networks. In 2008 International Symposium on Information Science and Engineering (ISISE), Piscataway, NJ, USA (pp. 565– 568).
  • Salehpour, A. A., Afzali-Kusha, A., & Mohammadi, S. (2008). Efficient clustering of wireless sensor networks based on memetic algorithm. In IIT 2008 International Conference on Innovations in Information Technology, Piscataway, NJ, USA (pp. 450–454).
  • W.Heinzelman,A.Chandrakasan, H. Balakrishnan. "Energy-Efficient communication protocol for wireless microsensor network", Proc. of the Hawaii International Conference on System Sciences, IEEE Computer Society, Washington. DC USA,Jan 2000, pp.3005-3014.
  • G. Ran, H. Zhang, and S. Gong, “Improving on LEACH Protocol of Wireless Sensor Networks Using Fuzzy Logic,” Journal of Information & Computational Science, vol. 7, no. 3, pp. 767–775, 2010.
  • S. Lindsey, C. S. Raghavendra, "PEGASIS: Power-Efficient gathering in sensor information systems". In: Proc. of the IEEE Aerospace Conference, Big, Sky, Montana, July 2002, vol.3, pp.1125-1130.
  • A. Manjeshwar and D. P. Agarwal, "TEEN: a routing protocol for enhanced efficiency in wireless sensor networks", In proceedings of the 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, IEEE Computer Society, San Francisco, April 2001, pp.2009-2015.
  • Ding P., Holliday J. and Celik A., “Distributed energy efficient hierarchical clustering for wireless sensor networks”, in Proc. of the 8th IEEE International Conference on Distributed Computing in Sensor Systems, Jun.2005.
  • A. Manjeshwar and D. P. Agrawal, “TEEN: A Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks,” in 15th International Symposium on Parallel and Distributed Processing, (Francisco, USA), pp. 2009–2015, April 2001.
  • S. Lindsey, C. Raghavendra, and K. M. Sivalingam, “Data Gathering Algorithms in Sensor Networks Using Energy Metrics,” IEEE Transac-tions on Parallel and Distributed Systems, vol. 13, no. 9, pp. 924–935, 2002.
  • J. Zhao and A. T. Erdogan, “A Novel Self-Organizing Hybrid network Protocol for Wireless Sensor Networks,” in 1st NASA/ESA Conference on Adaptive Hardware and Systems (AHS), (Istanbul, Turkey), pp. 412– 419, June 2006.
  • G. Smaragdakis, I. Matta, and A. Bestavros, “SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks,” tech. rep., Boston University Computer Science Department, 2004.
  • Z. A. Eu, H. P. Tan, and W. K. G. Seah, “Routing and Relay Node Placement in Wireless Sensor Networks Powered by Ambient Energy Harvesting,” in Wireless Communications and Networking Conference (WCNC), (Budapest, Hungary), pp. 1–6, IEEE, April 2009.
  • N. Choon-Sung, J. Hee-Jin, and S. Dong-Ryeol, “The Adaptive Cluster Head Selection in Wireless Sensor Networks,” in IEEE International Workshop on Semantic Computing and Applications (IWSCA), pp. 147– 149, 2008.
  • D. Karaboga, S. Okdem, and C. Ozturk, “Cluster based wireless sensor network routing using artificial bee colony algorithm,” Wireless Net-works, vol. 18, no. 7, pp. 847–860, 2012.
  • G. Zheng, S. Liu, and X. Qi, “Clustering routing algorithm of wireless sensor networks based on Bayesian game,” Journal of Systems Engi-neering and Electronics, vol. 23, pp. 154–159, February 2012.
  • M. M. Zanjireh, H. Larijani, W. O. Popoola, and A. Shahrabi, “An-alytical Modelling of ANCH Clustering Algorithm for WSNs,” in 13 International Conference on Networks (ICN), (Nice, France), pp. 68– 73, IARIA, February 2014.
  • W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An Application-Specific Protocol Architecture for Wireless Microsensor Networks,” IEEE Transactions on Wireless Communications, vol. 1, no. 4, pp. 660–670, 2002.
  • S. Fedor and M. Collier, “On the Problem of Energy Efficiency of Multi-Hop vs One-Hop Routing in Wireless Sensor Networks,” in 21st International Conference on Advanced Information Networking and Applications Workshops (WAINA), (Washington, USA), pp. 380–385, IEEE Computer Society, 2007.
  • S. D. Muruganathan, D. C. F. Ma, R. I. Bhasin, and A. Fapojuwo, “A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks,” IEEE Communications Magazine, vol. 43, no. 3, pp. 8–13, 2005.
  • S. Yi, J. Heo, Y. Cho, and J. Hong, “PEACH: Power-Efficient and Adaptive Clustering Hierarchy protocol for Wireless Sensor Networks,” Computer Communications, vol. 30, no. 14, pp. 2842–2852, 2007.
  • A. Chakraborty, K. Chakraborty, S. K. Mitra, and M. K. Naskar, “An Op-timized Lifetime Enhancement Scheme for Data Gathering in Wireless Sensor Networks,” in 5th IEEE Conference on Wireless Communication and Sensor Networks (WCSN), (Allahabad, India), pp. 1–6, December 2009.
  • I. Gupta, D. Riordan, and S. Sampalli, “Cluster-head Election using Fuzzy Logic for Wireless Sensor Networks,” in 3rd Annual Research Conference on Communication Networks and Services, pp. 255–260, 2005.
  • G. Ran, H.Zhang, and S. Gong, “Improving on LEACH Protocol of Wireless Sensor Networks Using Fuzzy Logic,” Journal of Information & Computational Science, vol. 7, no.3, pp. 767-775, 2010.

Abstract Views: 228

PDF Views: 0




  • Energy Efficient Routing Clustering Algorithms For Wireless Sensor Networks

Abstract Views: 228  |  PDF Views: 0

Authors

Rajkumar
Sambhram Institute of Technology, Bangalore, VTU Belagavi Karnataka, India
H. G. Chandrakanth
Sambhram Institute of Technology, Bangalore, VTU Belagavi Karnataka, India

Abstract


Wireless Sensor Networks have come to the forefront of the scientific community recently and it consists of small nodes with sensing, Communications and computing capabilities. The Wireless Sensor Network Systems can be applied to monitor different environments. In WSN, sensor nodes play the most prominent role. These sensor nodes batteries are replacing or recharging is impossible, it is essential to find energy efficient routing algorithm. In this paper, we survey the features / characteristics and different well-know energy efficient cluster routing algorithms for WSNs have been classified and presented based on their characteristics.

Keywords


Wireless Sensor Networks (WSN), Clustering, Energy Efficiency, Distributed Cluster Routing Algorithms, Centralized Cluster Routing Algorithms, Uni-Form Distribution.

References