WSN  Vol.6 No.6 , June 2014
Connectivity-Based Data Gathering with Path-Constrained Mobile Sink in Wireless Sensor Networks
ABSTRACT
The design of an effective and robust data gathering algorithm is crucial to the overall performance of wireless sensor networks (WSN). However, using traditional routing algorithms for data gathering is energy-inefficient for sensor nodes with limited power resources and multi-hop communication protocols. Data gathering with mobile sinks provided an effective solution to this problem. The major drawback of this approach is the time and path constraints of the mobile sink, which limit the mobile sink to collect data from all sensor nodes and, then, data routing is still required for these unreachable parts by the mobile sink. This paper presents a new data gathering algorithm called Connectivity-Based Data Collection (CBDC). The CBDC algorithm utilizes the connectivity between sensor nodes so as to determine the trajectory of the mobile sink whilst satisfying its path constraint and minimizing the number of multi-hop communications. The presented results show that CBDC, in comparison with the LEACH-C algorithm, prolongs the network life time at different connectivity levels of sensor networks, varying number of sensor nodes and at different path constraints of the mobile sink.

Cite this paper
Alhasanat, A. , Matrouk, K. , Alasha'ary, H. and Al-Qadi, Z. (2014) Connectivity-Based Data Gathering with Path-Constrained Mobile Sink in Wireless Sensor Networks. Wireless Sensor Network, 6, 118-128. doi: 10.4236/wsn.2014.66013.
References
[1]   Akyildiz, I., Su, W., Sankarasubramaniam, Y. and Cayirci, E. (2002) A Survey on Sensor Networks. IEEE Communication Magazine, 40, 102-114.

[2]   Li, D., Wong, K.D., Hu, Y.H. and Sayeed, A.M. (2002) Detection, Classification and Tracking of Targets. IEEE Signal Processing Magazine, 19, 17-29.
http://dx.doi.org/10.1109/79.985674

[3]   Di Francesco, M. and Das, S.K. (2011) Data Collection in Wireless Sensor Networks with Mobile Elements: A Survey. ACM Transactions on Sensor Networks (TOSN), 8, Article No. 7.

[4]   Shangguan, L., Mai, L., Du, J., He, W. and Liu, H. (2011) Energy-Efficient Heterogeneous Data Collection in Mobile Wireless Sensor Networks. Proceedings of 5th PMECT International Workshop Co-Located with the 20th International Conference on Computer Communication Networks (ICCCN’2011), Hawaii.

[5]   Tang, B., Wang, J., Geng, X., Zheng, Y. and Kim, J. (2012) A Novel Reliable and Efficient Data Harvesting Mechanism in Wireless Sensor Networks with Path-Constrained Mobile Sink. Proceedings of SPDA/NT/ICE 2012 Conference, Hangzhou, 158-163.

[6]   Xing, G., Li, M., Wang, T., Jia, W. and Huang, J. (2012) Efficient Rendezvous Algorithms for Mobility-Enabled Wireless Sensor Networks. IEEE Transactions on Mobile Computing, 11, 47-60.

[7]   Somasundara, A., Ramamoorthy, A. and Srivastava, B. (2004) Mobile Element Scheduling for Efficient Data Collection in Wireless Sensor Networks with Dynamic Deadlines. Proceedings of the 25th IEEE International Real-Time Systems Symposium (RTSS), Lisbon, 05-08 December 2014, 296305.
http://dx.doi.org/10.1109/REAL.2004.31

[8]   Xing, G., Wang, T., Jia, W. and Li, M. (2008) Rendezvous Design Algorithms for Wireless Sensor Networks with a Mobile Base Station. Proceedings of the 9th ACM International Symposium on Mobile ad Hoc Networking and Computing (MobiHoc), Hong Kong, 26-30 May 2008, 231-240.

[9]   Heinzelman, W., Chandrakasan, A. and Balakrishnan, H. (2002) An Application-Specific Protocol Architecture for Wireless Microsensor Networks. IEEE Transactions on Wireless Communications, 1, 660-670.

[10]   Gao, S., Zhang, H. and Das, S.K. (2011) Efficient Data Collection in Wireless Sensor Networks with Path-Constrained Mobile Sinks. IEEE Transactions on Mobile Computing, 10, 592-608.
http://dx.doi.org/10.1109/TMC.2010.193

[11]   Gao, S., Zhang, H., Song, T. and Wang, Y. (2010) Network Lifetime and Throughput Maximization in Wireless Sensor Networks With a Path-Constrained Mobile Sink. Proceeding of International Conference on Communications and Mobile Computing, Shenzhen, 12-14 April 2010, 298-302.

[12]   Shah, R., Roy, S., Jain, S. and Brunette, W. (2003) Data MULEs: Modeling a Three-Tier Architecture for Sparse Sensor Networks. Proceedings of the 1st IEEE International Workshop Sensor Network Protocols and Applications, Anchorage, 11 May 2003, 30-41.

[13]   Jain, S., Shah, R.C., Brunette, W., Borriello, G. and Roy, S. (2006) Exploiting Mobility for Energy Effcient Data Collection in Sensor Networks. Mobile Networks and Applications, 11, 327-339.
http://dx.doi.org/10.1007/s11036-006-5186-9

[14]   Chakrabarti, A., Sabharwal, A. and Azhang, B. (2003) Using Predictable Observer Mobility for Power Effcient Design of Sensor Networks. Proceedings of the 2nd International Workshop on Information Processing in Sensor Networks (IPSN 2003), Palo Alto, 26-27April 2004, 129-145.

[15]   Wang, G., Cao, G. and La Porta, T. (2006) Movement-Assisted Sensor Deployment. IEEE Transactions on Mobile Computing, 5, 640-652.
http://dx.doi.org/10.1109/TMC.2006.80

[16]   Song, L. and Hatzinakos, D. (2007) Architecture of Wireless Sensor Networks with Mobile Sinks: Sparsely Deployed Sensors. IEEE Transactions on Vehicular Technology, 56, 1826-1836.

[17]   Xing, G.L., Wang, T., Xie, Z.H. and Jia, W.J. (2008) Rendezvous Planning in Wireless Sensor Networks with Mobile Elements. IEEE Transactions on Mobile Computing, 7, 1430-1443.

[18]   Wang, G., Cao, G. and La Porta, T. (2006) Movement-Assisted Sensor Deployment. IEEE Transactions on Mobile Computing, 5, 640-652.

[19]   Rao, J., Wu, T. and Biswas, S. (2008) Network Assisted Sink Navigation Protocols for Data Harvesting in Sensor Networks. Proceeding of the 2008 Conference in Wireless Communication and Networking (WCNC 2008), Las Vegas, 31 March-3 April 2008, 2887-2892.

[20]   Kansal, A., Somasundara, A., Jea, D., Srivastava, M. and Estrin, D. (2004) Intelligent Fluid Infrastructure for Embedded Networks. Proceedings of the 2nd International Conference on Mobile Systems, Applications and Services 2004, Boston, 6-9 June 2004, 111-124.

[21]   Somasundara, A., Kansal, A., Jea, D., Estrin, D. and Srivastava, M. (2006) Controllably Mobile Infrastructure for Low Energy Embedded Networks. IEEE Transactions on Mobile Computing, 5, 958-973.
http://dx.doi.org/10.1109/TMC.2006.109

[22]   Luo, J., Panchard, J., Piorkowski, M., Grossglauser, M. and Hubaux, J.P. (2006) MobiRoute: Routing towards a Mobile Sink for Improving Lifetime in Sensor Networks. Proceedings of 2nd IEEE/ACM International Conference Distributed Computing in Sensor Systems (DCOSS), San Francisco, 18-20 June 2006, 480-497.
http://dx.doi.org/10.1007/11776178_29

[23]   He, L., Xu, J.D. and Yu, Y.T. (2009) Optimize Multiple Mobile Elements Touring in Wireless Sensor Networks. IEEE International Symposium on Parallel and Distributed Processing with Applications, Chengdu, 10-12 August 2009, 317-323.

[24]   Goldsmith, A. (2005) Wireless Communications. Cambridge University Press, Cambridge.
http://dx.doi.org/10.1017/CBO9780511841224

[25]   Siek, J.G., Lee, L.Q. and Lumsdaine, A. (2002) The Boost Graph Library: User Guide and Reference Manual. Pearson Education, Upper Saddle River.

[26]   Li, X.R. (2007) Collaborative Localization with Received-Signal Strength in Wireless Sensor Networks. IEEE Transactions on Vehicular Technology, 56, 3807-3817.
http://dx.doi.org/10.1109/TVT.2007.904535

 
 
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