Multirate adaptive awake-sleep cycle in hierarchical heterogeneous sensor network

1. Multirate adaptive awake-sleep cycle in hierarchical heterogeneous sensor network BY HELAL CHOWDHURY presented by : Helal Chowdhury Telecommunication laboratory, university of Oulu

2. contents • Introduction • Hierarchical Heterogeneous network • Multirate • Adaptive multirate Scheduling • Future Work and conclusion • Reference

3. Introduction (1/3) • Sensor network • low power, low cost, small size communication node which send sensed data to the receiver. • Self organised • Deployment • random • deterministic • Application • Battle field • Habitat monitoring • Health monitoring • Power Consumption • In WSN, energy is consumed by sensing, processing and in communication • less power • sensing • procesing • major power • communication • power amplifier • other electronics

4. Introduction (2/3) • Topology • Flat Nodes communicate with the sink via possibly multi-hop routes by using peer nodes as relays. • Hierarchical cluster are formed so that sources within a cluster send their data (via a single hop or multi-hop depending on the size of the cluster. • Communication method • Single-Hop • The simplest is direct transmission, where each sensor directly sends gathered information to the remote receiver independent of each other. • Multi-Hop • no direct transmission from source to final destination. • uses multi-hop routing. • Clustering • Cluster head can be selected dynamically or pre-assigned depending on the application. • clustering is arguably one of the most frequently proposed and used methods to organize communications in large scale network.

5. Introduction (3/3) • Transmission Rate • Single Rate • All sensor nodes use fixed transmission rate. • Multi Rate Sensor nodes uses multi transmission rate • Higher rate • Middle rate • Lower rate • bit rate varies according to the constraints • correlation • channel conditions • etc • MAC • Non contention • Fixed assigned channel for each sensor node using different multiple access techniques. • TDMA. • Contention • Not fixed assigned channel, nodes are competing to get access the channel • Coordinate • RTS/CTS • Non coordinate • less control overhead

6. Hierarchical Heterogeneous network (1/1) • Hierarchical Heterogeneous has two types sensors • Normal node • low power • mainly for sensing data and limited range of communication capabilities. • Relay node • High power • Data is processed, compressed, aggregated and relayed • Communication • Single Hop • many-to-one • Multi-Hop • Four group of sensors have been formed according to tthe relative power from the relay node.

7. Multirate (1/1) • Correlation based multi-rate adaption • All sensor nodes transmit to relay node • Higher correlation lower transmission rate • Correlation(highermiddlelower)transmission rate(1.5.7)

8. Adaptive multirate Scheduling (1/3) • The reservation access control protocol is an implementation of the RTS/CTS collision avoidance protocol and is part of the Distributed Coordination Function (DCF) in the IEEE 802.11 MAC. • Modified 802.11 RTS and CTS control frames • rate subfield uses for rate information. • length subfield gives the size of the data packet in octets.

9. Adaptive multirate Scheduling(2/3)

10. Adaptive multirate Scheduling (3/3) • Imact of multi rate in hirarchical heterogeneous network increase the sleep time. • The more lower the bit rate the more sleep time which ultimately reduces energy consumption in the normal sensor node as well as relay node • data preventation algorithm can be employed either in normal sensor node or in relay node for deep sleep.

11. Future Work and conclusion • We have proposed multi rate strategies to examine power efficient adaptive awake-sleep cycle in hierarchical heterogeneous network. • Correlation based adaptive scheduling has been demonstrated to reduce energy consumption. • We are looking at the impact of adaptive awake-sleep cycle on the mixed rate system.

12. Reference [1] Carlos Pomalaza-Raez, “Hierarchical Heterogeneous Architectures for Wireless Sensor Networks,” Center for Wireless Communications, University of Oulu, Finland. [2] W.Heinzelman, A. Chandraksan, and H.Balakrishnan, “Energy-Efficient Communications Protocols for Wireless Microsensor Networks,” Proceedings of the 33rd International Conference on System Sciences, January 2000. [3] E.J.Duarte-Melo and M.Liu, “Analysis of Energy Consumption and Lifetime of Heterogeneous Wireless Sensor Networks,” Proc. IEEE Globecom, November 2002, Taipei, Taiwan. [4] A. Depedri, A. Zanella, R. Verdone, "An Energy Efficient Protocol for Wireless Sensor Networks," Autonomous Intelligent Networks and Systems (AINS 2003), Menlo Park, CA, June 30-July 1, 2003, pp. 1-6. [5] W. Rabiner Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proceedings of the 33rd International Conference on System Sciences (HICSS '00), January 2000, pp. 1-10. [6] F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” Computer Networks, 2002, pp. 393-422. [7] G. Holland, N. Vaidja, P.Bahl, “A Rate-Adaptive MAC Protocol for Wireless Networks,” ACM/IEEE Int. Conf. on Mobile Computing and Networking (MOBICOM'01), Rome, Italy, July 2001.

13. Thank you for your attention!