1. WIRELESS SENSOR NETWORKS: POWER RELATED ISSUES Jay Wiley, #26445709 CSE 7344,Computer Networks and Distributed Systems II Dr. Golla

2. Agenda  Sensor networks – Part 1  Applications  Components  Design factors  Types  Examples of sensor networks  How to defeat  Paper Review – Part 2  Using Individualized Link Power Settings for Energy Optimization Using Individualized Link Power Settings for Energy Optimization  Modeling the Performance of Wireless Sensor Networks Modeling the Performance of Wireless Sensor Networks  Application of Wireless Sensor Networks in Energy Automation Application of Wireless Sensor Networks in Energy Automation  Battery Power Efficiency of PPM and FSK Battery Power Efficiency of PPM and FSK  Energy-Efficient Dynamic Clustering Algorithm Energy-Efficient Dynamic Clustering Algorithm  Summary  References

3. Sensor Networks  Sensors are cheap, small, and intelligent  May be easy to deploy  Wide selection  Power consumption

4. Applications  Military  Environmental  Office / home climate control  Oceanography  Medicine

5. Components  Sensing Unit  Seismic, infrared, optical, acoustic, and motion  Processing Unit  Power Unit

6. Design Factors  Fault tolerance / reliability  Scalability  Environment  Transmission method  Power

7. Types of WSNs  Terrestrial WSN  Underground WSN  Underwater WSN  Multi-media WSN  Mobile WSN

8. How to Defeat  Avoid the specific technology  Leverage dead spots  Probability of detection  Probability of false alarm

9. Using Individualized Link Power Settings for Energy Optimization  Neighborhood Node ratings (e.g. link state routing)

10. Modeling the Performance of WSNs  Confirmed earlier characteristics  Limited availability of power  Performance trade-offs  functionality and power  Nodes cannot transmit and receive at the same time  Two formal states of a node - active and sleep.  sleep mode saves power; still uses energy

11. Application of Wireless Sensor Networks in Energy Automation  WSN useful in energy automation  Focused on route and topology  Confirmed earlier characteristics  topology, power, design constraints & routing methods

12. Battery Power Efficiency  Battery power-conserving schemes for two modulation types  pulse position modulation (PPM) and frequency shift keying (FSK)  Modulation can conserve power  Consider the physical network topology  FSK is better than PPM  Intended mission will dictate what method you use

13. Energy-Efficient Dynamic Clustering Algorithm  Battery power is the most crucial resource  EE-DCA algorithm performs better than other algorithms  Low energy adapting clustering hierarchy, or “LEACH”, makes the lead node, called a cluster head, rotate  Base station controlled dynamic clustering protocol (BCDCP) is very similar to EE-DCA  EE-DCA updates the neighborhood tables dynamically from the nodes as opposed to the base station / cluster node.  Individual nodes themselves to more accurately fill out the neighborhood tables and keep the scores updated

14. Summary  Many applications / uses for WSNs  Multiple topologies / detection methods  Function dictates design  Power key to everything  Key points from articles

15. References  Ahmed Badi, Imad Mahgoub and Mohammad Ilyas, Using Individualized Link Power Settings for Energy Optimization in Hierarchical Wireless Sensor Networks (WSNs), July 2009.  C.-F. Chiasserini and M. Garetto, Modeling the Performance of Wireless Sensor Networks, IEEE INFOCOM 2004, March 2004.  Ling Tan, Shunyi Zhang, and Yanfeng Sun, Jing Qi, Application of Wireless Sensor Networks in Energy Automation, International Conference on Sustainable Power Generation and Supply, April 2009.  Qiuling Tang, Liuqing Yang, Georgios B. Giannakis, and Tuanfa Qin, Battery Power Efficiency of PPM and FSK in Wireless Sensor Networks, IEEE Transactions on Wireless Communications, vol. 6, no. 4, April 2007.  Ming Zhang and Chenglong Gong, Energy-Efficient Dynamic Clustering Algorithm in Wireless Sensor Networks, 2008 International Symposium on Computer Science and Computational Technology, May 2008.  N.B. – all retrieved March 2010 from www.ieee.orgwww.ieee.org