Cluster Based Optimization of Routing in Distributed Sensor Networks Using Bayesian Networks with Tabu Search

Lokesh B. Bhajantri


This paper proposes a cluster based optimizat ion of routing in Distributed Sensor Network (DSN) by employing a
Bayesian network with Tabu search approach. Bayesian Network based approach is used to select efficient cluster
heads, as well as construction of Bayesian Networks for the proposed scheme. This approach incorporates energy
level of each node, bandwidth and link efficiency. Simulations have been conducted to compare the performance of
the proposed approach and LEACH.
The optimization of routing is considered as a design issue in DSNs due to lack of energy consumption, delay
and maximum time required for data transmission between source nodes (cluster heads) to sink node. In this work,
optimization of routing takes place through cluster head nodes by using Tabu search. This meta - heuristic technique
is used to optimize the routing in the DSN environment that guides a local search procedure to explore the solution
space beyond local optimality. The objective of the proposed work is to improve the performance of network in
terms of energy consumption, throughput, packet delivery ratio, and time efficiency of optimizat ion of routing. The
results shows that the proposed approach perform better than LEACH protocol and proposed protocol utilizes
minimum energy and latency for cluster formation, thereby reducing the overhead of the protocol.

Full Text:



Iyengar S. S., Ankit T., Brooks R. R., An Overview of Distributed

Sensors Network. Available:−sensor−networks.html?id=Nff5

Shivakumar S., Iyengar S. S., Taxonomy of Distributed Sensors

Network. Available:

Heinzelman W. C., Balakrishnan. H, Energy-efficient Communication

Protocol for Wireless Micro Sensor Networks. In the Proceedings of the

rd Annual Hawaii International Conference on System Sciences, pp.

–10, 2000.

Karaki A. N., Kamal A. E., Routing Techniques in Wireless Sensor

Networks: A Survey, Journal on IEEE wireless Communications, vol.

, pp. 6–28, 2004.

Allirani A., Suganthi M., An Energy Efficient Cluster Formation

Protocol with Low Latency in Wireless Sensor Networks, International

Journal of Electrical and Computer Engineering, vol.4, no. 16, pp. 985 –

, 2009.

Handy M. J., Marc H., Dirk T., Low Energy Adaptive Clustering

Hierarchy with Deterministic Cluster-Head Selection, In proceedings of

th International workshop on mobile and wireless communications

network, pp. 368 – 372, 2002.

Yun Li. N., Weiyi Z., Weiliang Z., Xiaohu Y., Mahmoud D., Enhancing

the Performance of LEACH Protocol in Wireless Sensor Networks, In

proceedings of IEEE conference on computer communications, pp. 223

– 228, 2011.

Michel G., Jean-Yves P., Tabu Search. pp. 165–188.


Anant O., Wichai S., Boonruang M., Thanatchai K., Tabu Search

Approach to Solve Routing Issues in Communication Networks. In

Proceedings of World Academy of Science: Engineering & Technology,

vol. 53, pp. 1168–1171, 2009.

Bager Z., Mohammad Z., Vahid M. N., A Novel Cluster Based Routing

Protocol in Wireless Sensor Networks, International Journal of

Computer Science Issues, vol. 7, no 1, pp. 32 -36, 2010.

Young G. H., Heemin K., Yung C. B., Energy Efficient Fire Monitoring

Over Cluster Based Wireless Sensor Networks, International Journal of

Distributed Sensor Networks, vol. 2012, pp. 1-11, 2012.

Ali N., Faezeh S. B., Abdul H. Z., A New Clustering Protocol for

Wireless Sensor Networks using Genetic Algorithm approach, Journal of

Wireless Sensor Network, vol.3, no. 11, pp. 362-370, 2011.

Sanghak L., Junejae Y. C, Distance based Energy Efficient Clustering

for Wireless Ssensor Networks. In proceedings of 29th Annual IEEE

international Conference on Local Computer Networks, pp. 567 – 568,

Taewook K., Jangkyu Y., Hoseung L., Icksoo L., Hyunsook K.,

Byunghwa L., Byeongjik L. K., A Clustering Method for Energy

Efficient Routing in Wireless Sensor Networks, In Proceedings of the 6th

WSEAS International Conference on Electronics, Hardware, Wireless

and Optical Communications, pp. 133 – 138, 2007.

Jyh H. C., Rong H. J., An Energy-Aware, Cluster-Based Routing

Algorithm for Wireless Sensor Networks, Journal of Embedded and

Ubiquitous Computing, vol. 3824, pp. 255-266, 2005.

Arroyo V. R., Marques A. G., Vinagre-Diaz J., Cid-Sueiro J., A

Bayesian Decision Model for Intelligent Routing in Sensor Networks, In

proceedings of 3rd International Symposium on Wireless

Communication Systems, pp. 103 – 107. 2006.

Bhaskar K., Sitharama I., Distributed Bayesian Algorithms for Fault-

Tolerant Event Region Detection in Wireless Sensor Networks, IEEE

Transactions on computers, vol. 53, no. 3, pp. 241- 250, 2004.

Mohammad M., Subhash C., Rami A., Bayesian Fusion Algorithm for

Inferring Trust in Wireless Sensor Networks, Journal of Networks, vol 5,

no 7, pp. 815-822, 2010.

Abdelmorhit R., Samuel P., Tabu Search Algorithm for Cluster Building in Wireless Sensor Networks, IEEE Transactions on Mobile Computing, vol. 8, no. 4, 2009, pp. 433-444, 2009.

Masaya Y., Kazuo O., Ant Colony Optimization Routing Algorithm

with Tabu Search, In proceedings of International conference of

engineers and computer scientist, vol. 3, pp. 1-4, 2010.

Nadjib A., Nadjib A., Khaled B., Guy P., Tabu Search WSN

Deployment Method for Monitoring Geographically Irregular Distributed Events. Journal of sensors, vol.9, pp. 1625-1643, 2009.

Thamilselvan R., Balasubramanie P., Integrating Genetic Algorithm, TS approach for job shop scheduling, International Journal of Computer

Science and Information Security, vol. 2, no. 1, pp 1-6, 2009.

Eneko O., Fernando D., Comparison of a Memetic Algorithm and a

Tabu Search Algorithm for the Traveling Salesman Problem. In the

Proceedings of the Federated Conference on Computer Science and

Information Systems, pp. 131–136, 2012.

Bajeh A. O., Abolarinwa K. O., Optimization: A Comparative Study of

Genetic and Tabu Search Algorithms. International Journal of Computer

Applications, vol. 31, no. 5, pp. 43–48, 2011.

Ben G., Rugari F., Futtin F., Kuretti R., Bayesian Networks,

Encyclopedia of studies in Quality and Reliability, Wiley and Sons,

Nishant S., Upinderpal S., A Location Based Approach to Prevent

Wormhole Attack in Wireless Sensor Networks. International Journal of

Advanced Research in Computer Science and Software Engineering,

vol.4, no.1, pp. 840-845, 2014.

Herbert T., Donald L., Schilling principles of communication, systems.

McGraw-Hill, 1986.

Miao G., Himayat N., Li G. Y., Energy efficient link adaptation in

frequency-selective channels. IEEE Transaction on Communication,

vol.58, no.2, 2010.

Lokesh B. B., Nalini N. S. R., Nagaraj H. V., Chaitra N. Srinivas,

Performance Analysis of Heuristic Techniques for Optimization of

Routing in Distributed Sensor Networks. In the proceedings of

International Conference on Emerging Research in Computing,

Information, Communication and Applications, pp. 547-556, 2013.

Heinzelman W., Chandrakasan A., Balakrishnan H., Energy efficient

communication protocol for wireless micro sensor networks. In the

Proceedings of the IEEE Hawaii international conference on system

sciences, vol.8, pp. 8020-8030, 2000.


  • There are currently no refbacks.

International Journal of Electronics and Telecommunications
is a periodical of Electronics and Telecommunications Committee
of Polish Academy of Sciences

eISSN: 2300-1933