Efficient System And Localisation of Faulty Nodes

Efficient Database System and Localisation of Faulty Nodes in Wireless Sensor Network

Introduction.

This research seeks to optimise the application of Wireless Sensor Systems by addressing three key areas; they are Faulty node detection/Localisation, Sensor node Database creation and Real-time monitoring via dynamic graph Plotter. To achieve this we propose an algorithm that explore the use of Object Oriented Analysis and design method, here object are assigned to variables bearing in mind the size of its field and memory ,  the magnitude of the object measured  accounts for the resultant change in the output. Faulty nodes were detected and localized with their location shown on the map using real-time. The result of the event monitored were captured and displayed in the Output interface generated by JAVA, ORACLE and C-Sharp Software. Activity and data processed in the field were displayed with the aid of a dynamic graph interface. This work reports new design, practical issues and battery life management upon the measurement and simulation results.

Method

This work evolve methods of achieving this by adopting Object Oriented Analysis and Design, while Object Oriented Analysis lay emphasis on phase increases the understanding of problem domains, that OOA promotes a smooth transition from the analysis phase to the design phase, and that OOA provides a more natural way of organizing specifications, The design aspect that is Object Oriented Design (OOD) is the solution domain representation, created by OOD.  This system adopts the use of Object Oriented Program like C-Sharp, JAVA, and ORACLE Database.

In synthesizing the Program an Algorithm was developed from the interconnection of blocks that make up the system, a flow diagram to represent the sequence of program implementation was evolved to solve the problem of faulty node detection and also evolving an efficient database system.

In implementing this, nodes were placed in the map within the geographical area where they can be detected using signal strength level in real-time, the state of the nodes changes from green to red in the event of a faulty node, with name and address of the location displayed.

Results

Database Management interface was realized with JAVA and ORACLE Programs, and the sensor nodes were queried with My SQL Query Language.

Results of data transmitted by the nodes were obtained by the Dynamic Graph Plotter interface generated by C-Sharp software (Figure 1.0), and events were monitored in real-time.

A novel approach called Power Ratio method was used in analyzing power consumption in the node with a view to coming up with an energy saving technique.

Conclusion

This work opened a new paradigm in the optimization of Wireless Sensor Systems as some basic and fundamental problems listed below were solved,

  1. Real time faulty node detection and localisation
  2. Database creation for sensor nodes with data querying facility and enhance web resource sharing facility
  3. Real-time remote monitoring via a Dynamic Graph Plotter

The three items stated is a way out towards enhancing the application of Sensor Systems in various areas of need and challenges. We encourage the extensive use of sensor network for effective monitoring by creating networks to cover a particular sample size.

 

References

  1. Sun, L.M.; Li, J.Z.; Chen, Y.; Zhu, H.S. Wireless Sensor Networks; Tsinghua Publishing

House: Beijing, China, 2005.

  1. A. K. Somani and V. K. Agarwal. Distributed Diagnosis Algorithms for

Regular Interconnected Structures. IEEE Transaction of Computers, Vol.41, No.7: 899-906, July 1992.

  1. Habib F. Rashvand , Jose M. Alcaraz, Distributed Sensor Network Practice and Application, John Wiley & Sons Ltd Publication pp81-91 2012
  2. Rajeev Ranjan,  Shirshu Varma , Object-oriented Design for Wireless Sensor

Network assisted Global Patient Care Monitoring System, International 

        Journal of Computer Applications (0975 – 8887) Volume 45– No.2, May 2012

5         D. M. Fraser. Biosensors: Making sense of them. Medical Device Technology, 5(8):38-41, Feb 1994.

6         Janani, K.; Dhulipala, V.R.S.; Chandrasekaran, R.M.; , “A WSN Based Framework for Human Health Monitoring,” Devices and Communications (ICDeCom), 2011 International Conference on , vol., no., pp.1-5, 24- 25 Feb. 2011.

7         D. Konstantas, A. van Halteren, R. Bults, K. Wac, I. Widya, N. Dokovsky, G. Koprinkov, V. Jones, and R. Herzog. Mobile patient monitoring: the mobihealth system. Stud Health Technol Inform, 103:307-314, 2004.

wsn3

 

Figure 1.0 Dynamic Graph Plotter

Authors

James Agajo 

Department of Electrical/Electronics Engineering, Auchi Polytechnic, Auchi Edo State, Nigeria

agajojul@gmail.com

Philipa Idogho  

Rector Division/School of Information and Communication Technology

Auchi Polytechnic, Auchi. Edo State, Nigeria

philipaidogho@yahoo.com

C.O. Iwendi and A.R Allen

Electronics and Optical Engineering Research Group

University of Aberdeen, Scotland, UK

ciwendi@abdn.ac.uk,

 

 

Figure 1.0 Dynamic Graph Plotter