Efficient Data Collection for Mobile Wireless Sensor Network using Ant Based Routing

N. Karthigavani *, P. Sundaram **, G. Sridevi ***, V. Sowndarya ****
*,***,**** Department of Computer Science and Engineering, AVS Engineering College, Salem, Tamil Nadu, India.
** Rajaji Polytechnic College, Salem, India.
Periodicity:October - December'2019
DOI : https://doi.org/10.26634/jwcn.8.3.17236

Abstract

Mobility management in Mobile Wireless Sensor Networks (MWSNs) is a complex problem that must be taken into account. In MWSN, nodes move in and out of the network randomly. Hence, a path formed between two distant nodes is highly susceptible to changes due to unpredictable node movement. Also, due to the limited resources in WSN, the paths used for data transmission must be tested for the link quality and time consumed for data forwarding. In order to solve these issues, in this paper, an Ant based routing protocol with QoS effective data collection mechanism is proposed. In this protocol, the link quality and link delay are estimated for each pair of nodes. Link quality is estimated in terms of Packet Reception Rate (PRR), Received Signal Strength Indicator (RSSI) and Link Quality Index (LQI). A reliable path is chosen from the source to the destination based on the paths traversed by forward ants and backward ants. Then, if the link is found to be defective during data transmission, a link reinforcement technique is used to deliver the data packet at the destination successfully. The mobile robots collect the information with high data utility. In addition each mobile robot is equipped with multiple antennas and Space Division Multiple Access (SDMA) technique is then applied for effective data collection from multiple mobile robots. Simulation results show that the proposed routing protocol provides reliability by reducing the packet drop and end-to-end delay when compared to existing protocols.

Keywords

Mobile Wireless Sensor Networks (MWSNs), Link Quality Index (LQI), Space Division Multiple Access (SDMA), Antennas.

How to Cite this Article?

Karthigavani, N., Sundaram, P., Sridevi, G., and Sowndarya, V. (2019). Efficient Data Collection for Mobile Wireless Sensor Network using Ant Based Routing. i-manager’s Journal on Wireless Communication Networks , 8(3), 26-37. https://doi.org/10.26634/jwcn.8.3.17236

References

[1]. Alayev, Y., Chen, F., Hou, Y., Johnson, M. P., Bar-Noy, A., La Porta, T. F., & Leung, K. K. (2014). Throughput maximization in mobile WSN scheduling with power control and rate selection. IEEE Transactions on Wireless Communications, 13(7), 4066- 4079. https://doi.org/10.1109/TWC.2014.2315196
[2]. Awwad, S. A., Ng, C. K., Noordin, N. K., & Rasid, M. F. A. (2011). Cluster based routing protocol for mobile nodes in wireless sensor network. Wireless Personal Communications, 61(2), 251- 281. https://doi.org/10.1007/s11277-010-0022-8
[3]. Ba, P. D., Niang, I., & Gueye, B. (2014). An optimized and power savings protocol for mobility energy-aware in wireless sensor networks. Telecommunication Systems, 55(2), 271-280. https://doi.org/10.1007/s11235-013-9780-4
[4]. Bijarbooneh, F. H., Flener, P., Ngai, E., & Pearson, J. (2013, June). Optimising quality of information in data collection for mobile sensor networks. In 2013, IEEE/ACM 21st International Symposium on Quality of Service (IWQoS) (pp. 1-10). IEEE. https://doi.org/10.1109/IWQoS. 2013. 6550277
[5]. Karim, L., & Nasser, N. (2012). Reliable location-aware routing protocol for mobile wireless sensor network. IET communications, 6(14), 2149-2158. https://doi.org/10.1049/iet-com.2011.0696
[6]. Koucheryavy, A., & Salim, A. (2010, February). Prediction-based clustering algorithm for mobile wireless sensor networks. In 2010, The 12th International Conference on Advanced Communication Technology (ICACT) (Vol. 2, pp. 1209-1215). IEEE.
[7]. Le, D. V., Oh, H., & Yoon, S. (2013). RoCoMAR: robots' controllable mobility aided routing and relay architecture for mobile sensor networks. Sensors, 13(7), 8695-8721. https://doi.org/10.3390/s130708695
[8]. Li, K., & Hua, K. A. (2013, December). Mobility-assisted distributed sensor clustering for energy-efficient wireless sensor networks. In 2013, IEEE Global Communications Conference (GLOBECOM) (pp. 316-321). IEEE. https://doi.org/10.1109/ GLOCOM.2013.6831090
[9]. Peng, L., & Xu, J. B. (2009, December). ECDGA: An energyefficient cluster-based data gathering algorithm for mobile wireless sensor networks. In 2009, International Conference on Computational Intelligence and Software Engineering (pp. 1- 4). IEEE. https://doi.org/10.1109/CISE.2009. 5366773
[10]. Rondinone, M., Ansari, J., Riihijärvi, J., & Mähönen, P. (2008, April). Designing a reliable and stable link quality metric for wireless sensor networks. In Proceedings of the workshop on Real-world wireless sensor networks (pp. 6-10). https://doi.org/ 10.1145/1435473.1435476
[11]. Sara, G. S., Kalaiarasi, R., Pari, N. S., & Sridharan, D. (2010). Energy Efficient Clustering And Routing in Mobile Wireless Sensor Network. International Journal of Wireless & Mobile Networks, 2(4), 106-114.
[12]. Xiong, Y. P., Niu, J. W., Ma, J., & Sun, L. M. (2010). Efficient data delivery in mobile sensor networks. Journal of Communication and Computer, 7(5), 23-29.
[13]. Yoon, S., Soysal, O., Demirbas, M., & Qiao, C. (2008, June). Coordinated locomotion of mobile sensor networks. In 2008, 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (pp. 126-134). IEEE. https://doi.org/10.1109/SAHCN.2008.25
[14]. Zhang, X., He, J., & Wei, Q. (2010, July). Energy-efficient routing for mobility scenarios in wireless sensor networks. In Proceedings of the 3rd International Symposium on Electronic Commerce and Security Workshops. (pp. 80-83). Cuangzhou.
[15]. Zhao, M., Ma, M., & Yang, Y. (2010). Efficient data gathering with mobile collectors and space-division multiple access technique in wireless sensor networks. IEEE Transactions on computers, 60(3), 400-417. https://doi. org/10.1109/ TC.2010.140
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