Open Access Open Access  Restricted Access Subscription or Fee Access

A Review on Energy Optimization in WSN

Puneet Garg

Abstract


Wireless sensor networks (WSN) has expanded immensely in late time because of development in micro-electro-mechanical systems (MEMS) innovation. WSN has the possibility to interface the physical world with the virtual world by shaping a network of sensor nodes. Here, sensor nodes are typically battery-worked devices, and thus energy sparing of sensor nodes is a noteworthy configuration issue. Energy control is the most vital issue for wireless sensor systems, and the outline of a proficient energy procedure for drawing out the entire systems lifetime. Bacterial foraging optimization algorithm (BFOA) has pulled in a considerable measure of consideration as a high performance optimizer due to its quicker meeting and worldwide inquiry approach. Since its origin in 2001, numerous variations of BFOA have come up prompting significantly quicker union with higher precision. The center of this paper is to introduce the energy control system in energy proficient routing protocols for wireless sensor systems utilizing BFO.

Keywords: bacteria foraging algorithm, BFOA, PSO

Full Text:

PDF

References


Akyildiz I.F., Su W., Sankarasubramaniam Y., et al. A survey on sensor networks," Communications Magazine, IEEE. 2002; 40: 102–14p.

Akyildiz I.F., Su W., Sankarasubramaniam Y., et al. Wireless sensor networks: a survey, Comput Net. 2002; 38: 393–422p.

Yick J., Mukherjee B., Ghosal D. Wireless sensor network survey, Comput Networks. 2008; 52: 2292–330p.

Martinez K., Hart J.K., Ong R. Environmental Sensor Networks, computer magazine, IEEE. 2004; 37(8): 50–6p.

Culler D., Estrin D., Srivastava M., Overview of Sensor Networks, computer magazine, IEEE. 2004; 37(8): 41–9p.

Hill J.L. System architecture for wireless sensor networks, Ph.D. Dissertation. University of California, Berkeley, 2003.

Mohanty S., Patra S.K. A novel Bio-inspired Clustering algorithm for Wireless Sensor Networks, accepted in 3rd International Conference on Intelligent and Advanced Systems, Kuala Lumpur, Malaysia (ICIAS2010).

Manwall R., Mathuriya A., Garg S., et al. Performance evaluation of energy saving in WSN by using simulator ns2, Int J Data Network Security. 2012; 1(1).

Sinha A. Dynamic power management in wireless sensor networks, IEEE Des Test Comput. 2001; 18: 62–74p.

Rajeshwari A., Vimala Devi V., Lakshmi A.S., et al. Civilizing Energy Efficiency in wireless Sensor Network using Bacterial Foraging Algorithm, IOSR J Comput Eng. (IOSRJCE) 2012.

Banerjee I., Rahaman H., Sikdar B., UDDN: Unidirectional Data Dissemination via Negotiation, IEEE International Conference on Information Networking, 23–25 January, Pusan, Korea, 2008.

Niewiadomska-Szynkiewicz E., Kwaśniewski P., Windyga I. Comparative study of wireless sensor networks energy-efficient topologies and power save protocols, J Telecomm Inform Technol. 2009.

Passino K.M. “Biomimicry of bacterial for aging for distributed and optimization control”, IEEE Control Syst Mag. 2002.

Liu Y., Ji H., Yue G. An Energy-Efficient PEGASIS-Based Enhanced Algorithm in Wireless Sensor Networks, China Commun. 2006.

C., Sen S.J. Energy Efficient Communication Protocols for Wireless Sensor Networks, Natl Inst Technol. 2006.

Rajeshwari A., Vimala Devi V., Lakshmi A.S., et al. Civilizing Energy Efficiency in Wireless Sensor Network Using Bacteria Foraging Algorithm, IOSR J Comput Eng (IOSRJCE). 2012; 7(5): 61–65p, www.iosrjournals.org.

Sharma V., Pattnaik S.S., Garg T. A Review of Bacterial Foraging Optimization and Its Applications, National Conference on Future Aspect s of Artificial intelligence in Industrial Automation NCFAAIIA, 2012.

Anastasi G., Conti M., Di Francesco M., et al. Energy Conservation in wireless sensor networks: a survey. Sci Direct. 2009; 535–43p.


Refbacks

  • There are currently no refbacks.