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Utilizing Priority-Based Queen Bee Algorithm for Power Conservation in Wireless Sensor Networks

Alireza Jahani*, Sogol Rabei Savoji**, Mahdiye Bagheri***, Hooman Soori Roodavari****

* Assistant Professor and Head, Department of Information Technology, Mehralborz Institute of Higher Education, Tehran, Iran.

** Teacher and Research Assistant, Department of Information Technology.

***-**** Graduate, Department of Information Technology Engineering, Mehralborz Institute of Higher Education, Tehran, Iran.

Periodicity:October - December'2018
DOI : https://doi.org/10.26634/jwcn.7.3.15517

Abstract

Wireless Sensor Networks form small nodes that calculate and communicate with each other. In such networks, fault tolerance and security must be improved. In addition, maintaining node energy is one of the most important problems in node operation. Since wireless sensor networks have energy constraints, power conservation in these networks is very important and faces challenges. The aim of this study is to study the challenges and factors affecting node failure as well as the techniques and challenges related to power conservation. Since this study describes and introduces the performance of wireless sensor networks by including features, dimensions and relevant constraints, an appropriate algorithm for power conservation in wireless sensor networks is attempted. Therefore, power conservation techniques were studied in this paper to increase the fault tolerance of these network types and the performance of each method is separately described in different energy degradation conditions by providing a comparative table. The solution presented is a combination of priority-based methods and the Queen Bee algorithm and is introduced and analyzed to create energy-efficient clusters in wireless sensor networks. Therefore, the "Queen Bee Algorithm based on priority "(PQBA) is presented to improve power conservation and achieve the desired energy consumption. The simulation results in the CupCarbon simulator showed that more active points in the wireless sensor network lead to more clusters that reduce energy consumption by increasing the number of clusters and thus increase network lifetime.

Keywords

Wireless Sensor Network, Node Failure Tolerance, Power Conservation Conservation, Priority-based Methods, Queen Bee Algorithm

How to Cite this Article?

Jahani,A., Savoji,S.R., Bagheri,M., Roodavari,H.S. (2018). Utilizing Priority-Based Queen Bee Algorithm for Power Conservation in Wireless Sensor Networks. i-manager's Journal on Wireless Communication Networks, 7(3),19-31. https://doi.org/10.26634/jwcn.7.3.15517

References

[1]. Abbasi, A. A., Younis, M. F., & Baroudi, U. A. (2013). Recovering from a node failure in wireless sensor-actor networks with minimal topology changes. IEEE Transactions on Vehicular Technology, 62(1), 256-271.

[2]. Agah, A., & Das, S. K. (2007). Preventing DoS attacks in Wireless Sensor Networks: A repeated game theory approach. IJ Network Security, 5(2), 145-153.

[3]. Alam, M. M., Arbia, D. B., & Hamida, E. B. (2016). Wearable Wireless Sensor Networks for emergency response in Public Safety Networks. In Wireless Public Safety Networks, Vol. 2, (pp. 63-94). Elsevier.

[4]. Alfadhly, A., Baroudi, U., & Younis, M. (2012). An effective approach for tolerating simultaneous failures in wireless sensor and actor networks. In Proceedings of the First ACM International Workshop on Mission-oriented Wireless Sensor Networking (pp. 21-26). ACM.

[5]. Amirthavalli, K., & Sivakumar, P. (2014). Power conservation and security in Wireless Sensor Networks-A survey. In Electronics and Communication Systems (ICECS), 2014 International Conference on (pp. 1-7). IEEE.

[6]. Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Power conservation in Wireless Sensor Networks: A survey. Ad Hoc Networks, 7(3), 537- 568.

[7]. Asadi, M., Zimmerman, C., & Agah, A. (2013). A game-theoretic approach to security and power conservation in Wireless Sensor Networks. IJ Network Security, 15(1), 50-58.

[8]. Bidgoli, G., & Salman Abadi, Y. (2013). Fault tolerance evaluation in Wireless Sensor Networks. Soft Computing Journal, 1(2), 2-13.

[9]. Di Francesco, M., Das, S. K., & Anastasi, G. (2011). Data collection in wireless sensor networks with mobile elements: A survey. ACM Transactions on Sensor Networks (TOSN), 8(1), 1-34.

[10]. Geeta, D. D., Nalini, N., & Biradar, R. C. (2013). Fault tolerance in a Wireless Sensor Network using hand-off and dynamic power adjustment approach. Journal of Network and Computer Applications, 36(4), 1174-1185.

[11]. Kim, H., & Min, S.-G. (2009). Priority-based QoS MAC protocol for Wireless Sensor Networks. In Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on (pp. 1-8). IEEE.

[12]. Li, H., & Lin, Z. (2017). Study on Location of Wireless Sensor Network Node in Forest Environment. Procedia Computer Science, 107, 697-704.

[13]. Lopez-Pavon, C., Sendra, S., & Valenzuela-Valdes, J.F. (2018). Evaluation of cupcarbon network simulator for Wireless Sensor Networks. Network Protocols and Algorithms (Vol. 10). https://doi.org/10.5296/npa.v10i2. 13201

[14]. Pooranian, Z., Barati, A., & Movaghar, A. (2011). Queen-bee algorithm for energy efficient clusters in Wireless Sensor Networks. World Academy of Science, Engineering and Technology, 73, 1080-1083.

[15]. Pottie, G. J., & Kaiser, W. J. (2000). Wireless integrated network sensors. Communications of the ACM, 43(5), 51- 58.

[16]. Saad, W., Han, Z., Debbah, M., Hjørungnes, A., & Basar, T. (2009). Coalitional game theor y for communication networks: A tutorial. arXiv preprint arXiv:0905.4057.

[17]. Shah, R. C., Roy, S., Jain, S., & Brunette, W. (2003). Data Mules: Modeling and analysis of a three-tier architecture for sparse sensor networks. Ad Hoc Networks, 1(2-3), 215-233.

[18]. Sivakumar, P., Amirthavalli, K., & Senthil, M. (2014). Power conservation and security enhancement in Wireless Sensor Networks: A priority-based approach. International Journal of Distributed Sensor Networks, 10(5), 1-7.

[19]. Wang, G., Wang, T., Jia, W., Guo, M., & Li, J. (2009). Adaptive location updates for mobile sinks in Wireless Sensor Networks. The Journal of Supercomputing, 47(2), 127-145.

[20]. Younis, M., Senturk, I. F., Akkaya, K., Lee, S., & Senel, F. (2014). Topology management techniques for tolerating node failures in Wireless Sensor Networks: A survey. Computer Networks, 58, 254-283.

[21]. Zhao, W., Ammar, M., & Zegura, E. (2004). A message ferrying approach for data delivery in sparse mobile ad hoc networks. In Proceedings of the 5^th ACM International Symposium on Mobile Ad Hoc Networking and Computing (pp. 187-198). ACM.

[22]. Zhou, A., & Nascimento, M. A. (2014). RAID'ing Wireless Sensor Networks-Data Recovery for Node Failures. In SENSORNETS (pp. 298-308).

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Utilizing Priority-Based Queen Bee Algorithm for Power Conservation in Wireless Sensor Networks

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