Efficient Schemes To Improve The Life Time Of Wireless Sensor Networks

S. Anandamurugan*
Assistant Professor (SLG), Information Technology, Kongu Engineering College, Erode, India.
Periodicity:April - June'2015
DOI : https://doi.org/10.26634/jwcn.4.1.3457

Abstract

In recent years, a new wave of network labeled Wireless Sensor Networks (WSNs) has attracted a lot of attention from researchers in both academic and industrial communities. WSNs consist of tiny, energy efficient sensor nodes communicating via wireless channels, performing distributed sensing and collaborative tasks for a variety of monitoring applications. They include physical phenomena like temperature, humidity, vibrations, seismic events and pollution detection, to feature extractions. An energy source supplies the energy needed by the device to achieve the programmed assignment. This energy source often consists of a battery with a limited energy plan. It could be unfeasible or difficult to recharge the battery, because nodes may be deployed in a hostile or unpractical environment. The sensor network should have a life span long enough to fulfill the application requirements. Therefore, the crucial issue is to prolong the network lifetime. In some cases, it is possible to scavenge energy from the external environment (e. g. by using solar cells as the energy source). However, external energy supply sources regularly exhibit a non-continuous performance so that an energy buffer (a battery) is needed, as well. In any case, energy is a very significant resource and must be used very sparingly. Therefore, the main issues in wireless sensor networks is how to prolong the network lifetime of WSNs with a certain energy source and how to maintain coverage and connectivity. Optimizing the energy consumption in wireless sensor networks has recently become an important concern. Hence, energy management is a key issue in Wireless Sensor Networks.

Keywords

Wireless Sensor Networks, Energy, Battery, Duty cycle, Sink, Mobility, Data.

How to Cite this Article?

Anandamurugan, S. (2015). Efficient Schemes To Improve The Life Time Of Wireless Sensor Networks. i-manager's Journal on Wireless Communication Networks, 4(1), 1-10. https://doi.org/10.26634/jwcn.4.1.3457

References

[1]. Ahn, J. and Krishnamachari, B. (2007). “Modeling Search Costs in Wireless Sensor Networks”, Technical Report CENG-2007, Computer Science Department, University of Southern California.
[2]. Akyildiz, I.F. and Kasimoglu, I.H. (2004). “Wireless Sensor and Actor Networks: Research Challenges”, Ad Hoc Networks Journal, Vol. 2, No. 4, pp. 351-367.
[3]. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y. and Cayirci, E. (2002). “Wireless sensor Networks: a survey”, Computer Networks, pp. 393-422.
[4]. Akyildiz,I.F.,Su,W., Sankarasubramaniam, Y. and Cayirci,E. (2002). “A Survey on Sensor Networks,” IEEE Communication Magazine, Vol. 38, No. 8, pp. 102-114.
[5]. Aldosari, S.A. and Moura, J.M.F. (2004). “Detection in Decentralized Sensor Networks,” Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, pp. 277-280.
[6]. Alippi, C., Anastasi, G., Galperti,C., Mancini, F.and Roveri, M. (2007). “Adaptive Sampling for Energy Conservation in Wireless Sensor Networks for Snow Monitoring Applications”, Proceedings of IEEE International Workshop on Mobile Ad-hoc and Sensor Systems for Global and Homeland Security, Pisa (Italy).
[7]. Alshaibi, A., Vial, P. and Ros, M., “Hybrid powersaving technique for wireless sensor networks“, IEEE International Conference on wireless Information Technology and Systems (ICWITS), pp.1 - 4.
[8]. Amis, A., Prakash, R., Huynh, D. and Vuong, T. (2000). “Max-Min Cluster Formation in Wireless Ad Hoc Networks,” Proceedings of IEEE INFOCOM.
[9]. Anastasi, G., Conti, M., Di Francesco, M. and Passarella, A. (2009). “Energy Conservation in Wireless Sensor Networks: a Survey,” Ad Hoc Networks, Vol. 7, No. 3, pp. 537-568.
[10]. Anderson, R. and Kuhn, M. (1996). “Tamper Resistance—A Cautionary Note,” Proceedings of the Second Usenix Workshop Electronic Commerce, pp. 1-11.
[11]. Arroyo-Valles, R. Marques, A.G.; Cid-Sueiro, J. , (2011). “Optimal Selective Forwarding for Energy Saving in Wireless Sensor Networks”, IEEE Transactions on Wireless Communications, Vol. 10 , No. 1, pp. 164 –175.
[12]. Banerjee and C. Saxena, S. (2013). “Energy conservation in wireless sensor network using block cellular automata” International Conference on Computer Communication and Informatics (ICCCI), pp. 1 – 6,
[13]. Batalin, M.A. and Sukhatme, G.S. (2003). “Efficient exploration without localization,” in Proceedings of IEEE International Conference on Robot Automation. (ICRA), Vol. 2, pp. 2714–2719.
[14]. Braun, T. and Uttel, M. (2003). “A Novel Position Based and Beacon-Less Routing Algorithm for Mobile Ad-Hoc Networks," Proceedings of Third IEEE Workshop Applications and Services in Wireless Networks, pp. 197-210.
[15]. Cai, J., Ee, D., Pham, B., Roe, P. and Zhang, J. (2007). “Sensor Network for the Monitoring of Ecosystem: Bird Species Recognition”, Proceedings of Third International Conference on Intelligent Sensors, Sensor Networks and Information, pp. 293-298.
[16]. Chakrabarti, A., Sabharwal, A. and Aazhang, B. (2003). “Using predictable observer mobility for power efficient design of sensor networks,” in Proceedings of IPSN, pp. 129–145.
[17]. Chamberland, J.F. and Veeravalli, V.V. (2004). “Asymptotic Results for Decentralized Detection in Power Constrained Wireless Sensor Networks,” IEEE Journal on Selected Areas Communication, Vol. 2, No. 6, pp. 1007- 1015.
[18]. Chen, C.E., Ali, A.M. and Wang, H. (2006). “Design and Testing of Robust Acoustic Arrays for Localization and Enhancement of Several Bird Sources”, Proceedings of Fifth International Conference on Information in Sensor Networks, pp. 268-275.
[19]. Chih-Kuang Lin, Kokkinos, T., (2013). “Cross-Layer Solutions for Extended-Range Wireless Sensor Networks” IEEE Sensors Journal, Vol. 13, No. 3, pp. 1044 – 1054.
[20]. Ching-Yung Chang, Chao-Tsum Chang, Yu-Chieh Chen and Hsu-Ruey Chang, (2009). “Obstacle- Resistant Deployment Algorithms for Wireless Sensor Networks,” IEEE Transactions on Vehicular Technology, Vol. 58, No. 6.
[21]. Ching-Yung Chang, Hsu-Ruey Chang, Chen-Chi Hsieh and Chao-Tsun Chang, (2007). “OFRD: Obstacle- Free Robot Deployment Algorithms for Wireless Sensor Networks, ” Proceedings of WCNC, pp. 4374-4379.
[22]. Chou, J., Petrovic, D. and Ramchandran, K. (2003). “A Distributed and Adaptive Signal Processing Approach to Reducing Energy Consumption in Sensor Networks,” Proceedings of IEEE INFOCOM.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.