Localization Based Routing in WSN for Smart City Applications  
  Authors : Jamuna Rani. S; Farhana Kausar

 

In the context of Smart City environments, wireless sensor networking is playing a major role when enabling the utilization of networked infrastructures to introduce or improve a wide variety of services to be available to the citizens. How nodes communicate with each other is a key issue in these types of networks. This work presents a simple but yet efficient network discovery as well as an intelligent metric for route selection in smart environments that combines several parameters through the use of fuzzy logic. SmartSantander is a large-scale experimental framework primarily focused on enabling experimentation in the context of smart cities and Internet of Things.

 

Published In : IJCAT Journal Volume 1, Issue 4

Date of Publication : 31 May 2014

Pages : 21 - 26

Figures : 06

Tables : --

Publication Link : Localization Based Routing in WSN for Smart City Applications

 

 

 

Jamuna Rani. S : Postgraduate Student , Computer Science Department, Atria Institute Of Technology, VTU Bangalore, Karnataka.

Farhana Kausar : Associate Professor, Computer Science Department, Atria Institute Of Technology, VTU Bangalore, Karnataka.

 

 

 

 

 

 

 

Virtual back bone scheduling

fuzzy logis

shortest path

resuidal signal strength indicator

localization based routing

As the cities are becoming home for more and more people around the globe, efficient methods for the management of the cities that will ensure sustainable development while providing high quality of living are becoming one of the core challenges in front of us. The SmartSantander framework represents a significant enabler facilitating better understanding of the issues involved, technical, societal and economic, in creating smart and sustainable cities. In the last year of the project, development of the framework will be continued with deployment of more IoT devices and new services. The main focus of experimentation is expected to be on the service, application and user level, although research on the lower layers will be supported as well. The goal of the project's last year will also be to increase the number of users as well as to create mechanisms for keeping the platform running after the project ends. The applications in this context require the optimization of communication tasks. The work presented herein details a simple but yet efficient network discovery and tree construction protocol that can be executed using different metrics depending on the application and network requirements. A metric based on fuzzy logic has been also proposed. This metric combines several node and network parameters with the aim of constructing an efficient communication tree.

 

 

 

 

 

 

 

 

 

[1] “Urbanization and health”, Bulletin of the World Health Organization, Volume 88, Number 4, April 2010, pp. 245-246

[2] Gluhak A., Krco S., Nati M., Pfisterer D., Mitton N., Razafindralambo T. (2011): A survey on facilities for experimental internet of things research, Communications Magazine, IEEE Communication Magazine, Volume: 49, Issue: 11, 2011 , Page(s): 58 – 67

[3] FP7-ICT-2009-5-257992. Project SmartSantander. http://www.smartsantander.eu

[4] Smart Cities and IP-Based Sensor Networks: A conversation with Adam Dunkels. 2011. [Online]. Available: http://www. smartconnectedcommunities.org/docs/DOC-1552

[5] Z. Shelby and C. Bormann, 6LoWPAN: The Wireless Embedded Internet. Wiley Publishing, 2010.

[6] SmartSantander, Future Internet Research and Experimentation. [Online]. Available: http://www.smartsantander.eu/

[7] V. Shnayder, M. Hempstead, B.-r. Chen, G.W. Allen, and M. Welsh, “Simulating the Power Consumption of Large-Scale Sensor Network Applications,” Proc. Second Int’l Conf. Embedded Networked Sensor Systems (SenSys ’04), pp. 188-200, 2004.

[8] Longadge, Rushi, and Snehalata Dongre. "Class Imbalance Problem in Data Mining Review." arXiv preprint arXiv:1305.1707 (2013).

[9] C. Misra and R. Mandal, “Rotation of CDS via Connected Domatic Partition in Ad Hoc Sensor Networks,” IEEE Trans. Mobile Computing, vol. 8, no. 4, pp. 488-499, Apr. 2009.

[10] W. Ye, J. Heidemann, and D. Estrin, “An Energy- Efficient MAC Protocol for Wireless Sensor Networks,” Proc. IEEE INFOCOM, pp. 1567-1576, 2002.

[11] Q. Cao, T. Abdelzaher, T. He, and J. Stankovic, “Towards Optimal Sleep Scheduling in Sensor Networks for Rare-Event Detection,” Proc. ACM Fourth Int’l Symp. Information Processing in Sensor Networks (IPSN ’05), pp. 20-27, 2005.

[12] A. Keshavarzian, H. Lee, and L. Venkatraman, “Wakeup Scheduling in Wireless Sensor Networks,” Proc. Seventh ACM Int’l Symp. Mobile Ad Hoc Networking and Computing (MobiHoc ’06),pp. 322- 333, 2006.

[13] R. Cohen and B. Kapchits, “An Optimal Wake-Up Scheduling Algorithm for Minimizing Energy Consumption while Limiting Maximum Delay in a Mesh Sensor Network,” IEEE/ACM Trans. Networking, vol. 17, no. 2, pp. 570-581, Apr. 2009.

[14] Y. Li, W. Ye, and J. Heidemann, “Energy and Latency Control in Low Duty Cycle MAC Protocols,” Proc. IEEE Wireless Comm. And Networking Conf. (WCNC ’05), pp. 676-682, 2005.

[15] J.W. Hui and D.E. Culler, “IP is Dead, Long Live IP for Wireless Sensor Networks,” Proc. Sixth ACM Conf. Embedded Network Sensor Systems (SenSys ’08), pp. 15-28, 2008.

[16] L. Doherty, W. Lindsay, and J. Simon, “Channel- Specific Wireless Sensor Network Path Data,” Proc. Int’l Conf. Computer Comm. And Networks (ICCCN ’07), pp. 89-94, 2007.

[17] F. Dai and J. Wu, “An Extended Localized Algorithm for Connected Dominating Set Formation in Ad Hoc Wireless Networks,” IEEE Trans. Parallel Distributed Systems, vol. 15, no. 10, pp. 908-920, Oct. 2004.