Route Optimization using Swarm Intelligence Techniques in WSN

Authors

  • Chander Diwaker Department of Computer Science Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, India
  • Anu Mehla Department of Computer Science Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, India

DOI:

https://doi.org/10.37591/rtpl.v3i2.794

Abstract

The research in wireless sensor network (WSN) progressively increases due to its extensive array of applications. Lifetime of sensor node in WSN is dependent on limited battery powered devices. Thus, designing of an adequate WSN to increase the network lifetime becomes one of the salient performance metrics. There are several energy efficient routing protocols described in the literature for the achievement of optimal routing. To produce the optimal result, swarm intelligence (SI) based techniques are very effective to maximize the network lifetime. This paper is focused on review under swarm intelligence based route optimization technique to increase network lifetime by using ACO and PSO.

Keywords: WSN, swarm intelligence, ant colony optimization, particle swarm optimization

Cite this Article
Chander Diwaker, Anu Mehla. Route Optimization using Swarm Intelligence Techniques in WSN. Recent Trends in Programming Languages. 2016; 3(2): 13–18p.

Author Biography

  • Chander Diwaker, Department of Computer Science Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, India
    Asst. Professor, CSE Department

References

Wenjing Guo, Wei Zhang. A Survey on Intelligence Routing Protocols in Wireless Sensor Networks. J Netw Comput Appl. 2014; 38: 185–201p.

Jalel Ben-Othman, Bashir Yahya. Energy Efficient and QoS Based Routing Protocol for Wireless Sensor Networks. J Parallel Distrib Comput. 2010; 70(8): 849–857p.

Loveneet Kaur, Dinesh Kumar. Optimization Techniques for Routing in Wireless Sensor Network. International Journal of Computer Science and Information Technologies (IJCSIT). 2014; 5(3): 4719–4721p.

Selvi V, Umarani R. Comparative Analysis of Ant Colony and Particle Swarm Optimization Techniques. International Journal of Computer Applications (IJCA) (0975-8887). 2010; 5(4): 1–6p.

Reetika Nagar, Sachin Kumar, Gaurav Pratap Singh. Using Swarm Approaches for Student Selection Process. International Journal of Research in Engineering and Technology (IJRET). 2014; 3(12): 7–13p.

Xuxun Liu, Desi He. Ant Colony Optimization with Greedy Migration Mechanism for Node Deployment in Wireless Sensor Networks. J Netw Comput Appl. 2014; 39: 310–318p.

Pratyay Kuila, Jana Prasanta K. Energy Efficient Clustering and Routing Algorithms for Wireless Sensor Networks: Particle Swarm Optimization Approach. Eng Appl Artif Intell. 2014; 33: 127–140p.

Selcuk Okdem, Dervis Karaboga. Routing in Wireless Sensor Networks Using Ant Colony Optimization. In the Proceedings of the First IEEE NASA/ESA Conference on Adaptive Hardware and Systems. 2006; 2614–17p.

Zulfiqar Ali, Waseem Shahzad. Critical Analysis of Swarm Intelligence basedRouting Protocols in Ad-hoc and Sensor Wireless Networks. Journal of National University of Computer & Emerging Science. 2011; 287–292p.

Mohammad El-Basioni Basma M, Abd El-kader Sherine M, Eissa Hussein S, et al. An Optimized Energy-Aware Routing Protocol for Wireless Sensor Network.

Egyptian Informatics Journal. 2011; 12: 61–72p.

Ahmed Abdulla EAA, Hiroki Nishiyama, Nei Kato. Extending the Lifetime of Wireless Sensor Networks: A Hybrid Routing Algorithm. Journal of Computer Communication (JCC). 2012; 35: 1056–1063p.

Yong Lv. Routing in Wireless Sensor Networks Using Swarm Intelligence. In the Proceedings of the 10th World Congress on Intelligent Control and Automation. 2012; 680–684p.

Adamu Murtala Zungeru, Li-Minn Ang, Kah Phooi Seng. Classical and Swarm Intelligence Based Routing Protocols for Wireless Sensor Networks: A Survey and Comparison. J Netw Comput Appl. 2012; 35: 1508–1536p.

Jacques Bahi, Mohammed Haddad, Mourad Hakem, et al. Efficient Distributed Lifetime Optimization Algorithm for Sensor Networks. J Ad-hoc Netw. 2014; 16: 1–12p.

Md. Azharuddin, Pratyay Kuila, Jana Prasanta K. Energy Efficient Fault Tolerant Clustering and Routing Algorithms for Wireless Sensor Networks. Journal of Computers and Electrical Engineering. 2014; 67: 997–1002p.

Tarachand Amgoth, Jana Prasanta K. Energy-Aware Routing Algorithm for Wireless Sensor Networks. Journal of Computer and Electrical Engineering. 2015; 41(C): 357–367p.

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Published

2016-09-07

Issue

Vol. 3 No. 2 (2016)

Section

Research Articles

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