A Chain-Based Routing Protocol to Maximize the Lifetime of Wireless Sensor Networks

Abstract

Energy conservation is a key issue in the design of systems based on wireless sensor networks. Clustering routing protocols have been developed in order to reduce the network traffic toward the sink and therefore prolong the network lifetime. An alternative of clustering is to build chains instead of clusters. In this context, we propose a routing protocol for Wireless Sensor Networks (WSN). It is based on constructing multiple chains in the direction of the sink. The first node of each chain sends data to the closest node in the same chain. This latter collects, aggregates and transmits data to the next closest node. This process repeats until reaching the last node, which aggregates and transmits data directly to the sink. An improvement of this approach is proposed. It works as follows: In addition to forming multiple chains as previously, it constructs a main chain, which includes leader node of each chain. Since, initially all main chain nodes have the same amount of power, the nearest node to the sink aggregates data from others then transmits it to the sink. In the next transmission, main chain node having the higher residual energy performs this task. Compared with the first approach, simulation results show that improvement approach consumes less energy and effectively extends the network lifetime.

Share and Cite:

M. Hadjila, H. Guyennet and M. Feham, "A Chain-Based Routing Protocol to Maximize the Lifetime of Wireless Sensor Networks," Wireless Sensor Network, Vol. 5 No. 5, 2013, pp. 116-120. doi: 10.4236/wsn.2013.55014.

1. Introduction

Today, progress in the field of microelectronics and wireless communication technologies is used to create small systems communicating with sensors at a reasonable cost [1]. These communicating micro-components are called sensors. These technological advances make possible the deployment of wireless sensor networks. A Wireless Sensor Network [2] is a set of communicating nodes, each consisting of four entities: a radio module for exchanging messages via the wireless medium, one or more sensors/actuators with a specific task, such as motion detection or the activation of a contact, a microcontroller responsible for needed processing, and an energy source which supplies the whole. The wireless sensor networks are increasingly deployed randomly or in deterministic way in various areas covering military applications such as target tracking, monitoring of wild animals in the forest, habitat monitoring, industrial applications, earth movement detection, healthcare applications, surveillance and so on [2]. This technology must offer autonomous solutions, that is to say, capable of saving energy and self-configuring. This makes it more attractive because these concepts do not apply to wired networks or even most solutions.

Figure 1 shows a typical architecture of a network of wireless sensors [3]. The data collected by sensors are fed directly or via other sensors to a collection point called base station or sink. This network communicates to a network of another type that leads to unit control system. The intermediate network used to deport the checkpoint from the place of deployment of the sensor

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] C. Li, H. Zhang, B. Hao and J. Li, “A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks,” Sensors, Vol. 11, No. 4, 2011, pp. 3498-3526. doi:10.3390/s110403498
[2] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “Wireless Sensor Networks: A Survey,” Computer Networks (Elsevier), Vol. 38, No. 4, 2002, pp. 393-422. doi:10.1016/S1389-1286(01)00302-4
[3] G. Anastasi, M. Conti, M. Di Francesco and A. Passarella, “Energy Conservation in Wireless Sensor Networks: A Survey,” Elsevier, Ad Hoc Networks, Vol. 7, No. 3, 2009, pp. 537-568. doi:10.1016/j.adhoc.2008.06.003
[4] J. Hill and D. Culler, “A Wireless Embedded Sensor Architecture for System Level Optimization,” International Research IRB-TR-02-00N, 2002.
[5] G. Anastasi, M. Conti, M. Di Francesco and A. Passarella, “How to Prolong the Lifetime of Wireless Sensor Networks,” In: M. Denko and L. Yang, Eds., Mobile Ad Hoc and Pervasive Communications, American Scientific Publishers, CRC Press, Boca Raton, 2011. http://info.iet.unipi.it/~anastasi/papers/Yang.pdf
[6] S. Bandyopadhyay and E. Coyle, “An Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks,” 22nd Annual Joint Conference of the IEEE Computer and Communications (INFOCOM 2003), San Francisco, 30 March-3 April 2003, pp. 1713-1723.
[7] S. Banerjee and S. Khuller, “A Clustering Scheme for Hierarchical Control in Multi-Hop Wireless Networks,” 20th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2001), Anchorage, 22-26 April 2001, pp. 1028-1037.
[8] A. Boukerche, R. W. Pazzi and R. B. Araujo, “Fault-Tolerant Wireless Sensor Network Routing Protocols for the Supervision of Context-Aware Physical Environments,” Journal of Parallel and Distributed Computing, Vol. 66, No. 4, 2006, pp. 586-599. doi:10.1016/j.jpdc.2005.12.007
[9] A. Boukerche and A. Martirosyan, “An Energy-Aware and Fault Tolerant Inter-Cluster Communication Based Protocol for Wireless Sensor Networks,” Global Telecommunications Conference (GLOBECOM’07), Washington, 26-30 November 2007, pp. 1164-1168.
[10] W. Heinzelman, A. Chandrakasan and H. Balakrishnan, “Energy-Efficient Communication Protocols for Wireless Sensor Networks,” Proceedings of the 33rd Annual Hawaii International Conference on System Sciences (HICSS), Hawaii, 4-7 January 2000, pp. 3005-3014. doi:10.1109/HICSS.2000.926982
[11] A. Manjeshwar and D. P. Agrawal, “TEEN: A Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks,” 15th Conference on Parallel and Distributed Processing Symposium, San Francisco, 23-27 April 2000, pp. 2009-2015.
[12] A. Manjeshwar and D. P. Agrawal, “APTEEN: A Hybrid Protocol for Efficient Routing and Comprehensive Information Retrieval in Wireless Sensor Networks,” 2nd International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, Ft. Lauderdale, 15-19 April 2002, pp. 195-202.
[13] A. M, A. Boukerche and R. W. Nelem Pazzi, “A Taxonomy of Cluster-Based Routing Protocols for Wireless Sensor Networks,” IEEE International Symposium on Parallel Architectures, Algorithms, and Networks, Sydney, 7-9 May 2008, pp. 247-253.
[14] S. Lindsey and C. S. Raghavendra, “PEGASIS: Power Efficient Gathering in Sensor Information Systems,” Proceedings of the IEEE Aerospace Conference, Vol. 3, Big Sky, 2002, pp. 1125-1130.
[15] H. O. Tan and I. Korpeoglu, “Power Efficient Data Gathering and Aggregation in Wireless Sensor Networks,” ACM SIGMOD, Vol. 32, No. 4, 2003, pp. 66-71. doi:10.1145/959060.959072
[16] Y. Yu and Y. Song, “An Energy-Efficient Chain-Based Routing Protocol in Wireless Sensor Network,” International Conference on Computer Application and System Modeling (ICCASM), Taiyuan, 22-24 October 2010, pp. 486-489.
[17] W. Guo, W. Zhang and Gang Lu, “PEGASIS Protocol in Wireless Sensor Network Based on an Improved Ant Colony Algorithm,” 2nd International Workshop on Education Technology and Computer Science, Wuhan, 6-7 March 2010, pp. 64-67.
[18] Y. L. Chen, J. S. Lin, Y. F. Huang, F. K. Cheung and J. Y. Lin, “Energy Efficiency of a Chain-Based Scheme with Intra-Grid in Wireless Sensor Networks,” International Symposium on Computer, Communication, Control and Automation, Tainan, 5-7 May 2010, pp. 484-487.
[19] W. Linping and C. Zhen, “Improved Algorithm of PEGASIS Protocol Introducing Double Cluster Heads in Wireless Sensor Network,” International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE), Changchun, 24-26 August 2010, pp. 148-151. doi:10.1109/CMCE.2010.5609618

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.