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Department Of Computer Science

  1. 1. Department of Computer Science Southern Illinois University Carbondale Mobile & Wireless Computing Routing Protocols for Sensor Networks Hierarchical & Location-based and QoS Protocols Dr. Kemal Akkaya E-mail: kemal@cs.siu.edu
  2. 2. Hierarchical Protocols <ul><li>When sensor density increases single tier networks cause </li></ul><ul><ul><li>Sink overloading </li></ul></ul><ul><ul><li>Increased latency </li></ul></ul><ul><ul><li>Large energy consumption </li></ul></ul><ul><li>Clustered Network allow coverage of large area of interest and additional load without degrading the performance </li></ul><ul><li>Hierarchical clustering schemes are the most suitable for wireless sensor networks </li></ul><ul><ul><li>Uses Multi - hop communication within a cluster </li></ul></ul><ul><ul><li>Performs data aggregation and fusion on data to reduce number of transmitted messages to the sink </li></ul></ul><ul><ul><li>Maintain the energy reserves of nodes efficiently </li></ul></ul>
  3. 3. Hierarchical Routing
  4. 4. LEACH <ul><li>LEACH (Low Energy Adaptive Clustering Hierarchy) is the first hierarchical routing protocol for sensor networks </li></ul><ul><li>W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, &quot;Energy-efficient communication protocol for wireless sensor networks,&quot; in the Proceeding of the Hawaii International Conference System Sciences, Hawaii, January 2000. </li></ul><ul><li>Self-Organizing, adaptive clustering protocol </li></ul><ul><li>Even distribution of energy load among the sensors </li></ul><ul><li>Nodes organize themselves into clusters </li></ul><ul><li>Cluster-heads communicate data with the base station (sink) </li></ul>
  5. 5. LEACH <ul><li>Dynamic cluster formation - Cluster-heads are not fixed </li></ul><ul><ul><li>They rotate at each round randomly </li></ul></ul><ul><li>Data-fusion at each cluster – reduces energy dissipation and enhances lifetime </li></ul>Cluster-heads at time t Cluster-heads at time t + d Dynamic Clustering
  6. 6. LEACH uses First Order Radio Model <ul><li>Transmit k-bit message a distance d using the radio model </li></ul>Fig 1: First Order Radio Model E Tx-elec = Energy dissipated/bit at Transmitter E Rx-elec = Energy dissipated/bit at Receiver Є amp = Amplification factor Energy equation at the Transmitter: Energy equation at the Receiver:
  7. 7. LEACH Algorithm <ul><li>Algorithm is broken into rounds, and each rounds consists of following 4 phases: </li></ul><ul><li>Advertisement phase </li></ul><ul><ul><li>Each node decides whether or not to become cluster-head </li></ul></ul><ul><ul><li>Advertises itself as cluster-head </li></ul></ul><ul><li>Cluster Set-up phase </li></ul><ul><ul><li>Each node decides to which cluster it belongs </li></ul></ul><ul><ul><li>Notification to the cluster-head </li></ul></ul><ul><li>Schedule Creation </li></ul><ul><ul><li>Cluster-head creates a TDMA schedule notifying each node when it can transmit </li></ul></ul><ul><li>Data transmission </li></ul><ul><ul><li>Each node send data during their allotted time </li></ul></ul>
  8. 8. Simulation Results Energy dissipation System Lifetime Direct: Direct Transmission to the Sink MTE: Minimum Transmission Energy
  9. 9. Sensor Lifetimes <ul><li>System life time after 1200 rounds </li></ul>Live nodes (circled) Dead nodes (dotted)
  10. 10. What about MTE & Direct Communication? <ul><li>No of rounds: 180 </li></ul><ul><li>Alive (circles); Dead (dots) </li></ul>Direct Communication MTE
  11. 11. LEACH Summary <ul><li>Factor of 7 reduction in energy dissipation as compared to Direct Communication </li></ul><ul><li>Uniform distribution of energy-usage in the network </li></ul><ul><li>Doubles the system lifetime compared to other methods </li></ul><ul><li>Nodes die essentially in random fashion, thus maintain the network coverage </li></ul><ul><li>Completely distributed, no network knowledge required </li></ul><ul><li>Problems: </li></ul><ul><ul><li>Nodes use single-hop communication </li></ul></ul><ul><ul><ul><li>Not good for large domains </li></ul></ul></ul><ul><ul><li>Cluster-head change overhead </li></ul></ul>
  12. 12. PEGASIS <ul><li>Power Efficient GAthering in Sensor Information Systems </li></ul><ul><li>Improvement to LEACH </li></ul><ul><ul><li>Form chains rather than clusters </li></ul></ul><ul><li>S. Lindsey and C. S. Raghavendra, &quot;PEGASIS: Power Efficient GAthering in Sensor Information Systems,&quot; in the Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, March 2002. </li></ul><ul><li>Token-Passing Chain-Based </li></ul><ul><li>Considered Near-Optimal </li></ul><ul><li>Nodes die in random </li></ul><ul><li>Stationary Nodes and Sink </li></ul><ul><li>Every node have a global network map </li></ul><ul><li>Data Fusion </li></ul><ul><li>Greedy chain construction </li></ul>
  13. 13. Main Procedures <ul><li>Greedy Algorithm Construct Chain – Start at a node far from sink and gather everyone neighbor by neighbor </li></ul><ul><li>Node i (mod N) is the leader in round i </li></ul><ul><li>Nodes passes token through the chain to leader from both sides </li></ul><ul><li>Each node fuse its data with the rest </li></ul><ul><li>Leader transmit to sink </li></ul>
  14. 14. PEGASIS - Illustration
  15. 15. Comparison
  16. 16. Summary <ul><li>Outperforms LEACH by eliminating clustering overhead </li></ul><ul><li>Global Information assumed </li></ul><ul><li>Limited Scale: </li></ul><ul><ul><li>Information travels many nodes </li></ul></ul><ul><ul><ul><li>Excessive delay for far nodes </li></ul></ul></ul><ul><ul><li>Assumes any node can communicate with sink </li></ul></ul><ul><li>Hierarchical PEGASIS </li></ul><ul><ul><li>Extension of PEGASIS </li></ul></ul><ul><ul><li>Decrease the delay for the packets during transmission to the base station </li></ul></ul><ul><ul><li>Simultaneous transmissions of data messages </li></ul></ul><ul><ul><li>Avoid collisions and possible signal interference </li></ul></ul><ul><ul><ul><li>Signal Coding (e.g. CDMA) </li></ul></ul></ul><ul><ul><ul><li>Spatially separated nodes can transmit at the same time </li></ul></ul></ul>
  17. 17. Hierarchical PEGASIS
  18. 18. Location-based Protocols <ul><li>If the locations of the sensor nodes are known, the routing protocols can use this information to reduce the latency and energy consumption of the sensor network. </li></ul><ul><ul><li>Distance between two nodes is calculated using location information </li></ul></ul><ul><ul><li>Energy consumption can be estimated </li></ul></ul><ul><ul><ul><li>Efficient energy utilization </li></ul></ul></ul><ul><li>Location of a node can be determined using </li></ul><ul><ul><li>Global Positioning System (GPS) </li></ul></ul><ul><ul><li>Ultrasonic Systems using trilateration </li></ul></ul><ul><ul><li>Beacons </li></ul></ul><ul><li>Although GPS is not envisioned for all types of sensor networks, it can still be used if stationary nodes with large amount of energy are allowed. </li></ul><ul><li>Location based protocols assume that each node knows its location in the network </li></ul>
  19. 19. GAF (Geographic Adaptive Fidelity) <ul><li>GAF designed for both ad hoc and sensor networks </li></ul><ul><li>Y. Xu, J. Heidemann, and D. Estrin, &quot;Geography-informed energy conservation for ad hoc routing,&quot; in the Proceedings of the 7 th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom’01 ), Rome, Italy, July 2001. </li></ul><ul><li>Forms a virtual grid of the covered area </li></ul><ul><li>Each node associates itself with a point in the grid based on its location </li></ul><ul><li>Nodes associated with same point in grid are considered equivalent </li></ul><ul><li>Some nodes in an area are kept sleeping to conserve energy </li></ul><ul><li>Nodes change state from sleeping to active for load balancing </li></ul>
  20. 20. Routing in GAF Sink Representative Node for the subregion Virtual Grid
  21. 21. States in GAF <ul><li>Nodes use GPS to associate itself to the grid </li></ul><ul><li>A node remains active for time Ta </li></ul><ul><li>Ta of a node in the grid is broadcasted to other equivalent nodes </li></ul><ul><li>The sleeping time of a node is adjusted depending on Ta </li></ul><ul><li>In the discovery state each node broadcasts discovery messages periodically (Td) </li></ul><ul><li>Handles mobility </li></ul><ul><li>Three States </li></ul><ul><li>Discovery: Determining neighbors </li></ul><ul><li>Active: Does routing </li></ul><ul><li>Sleep: Turn off radio </li></ul>
  22. 22. GAF Summary <ul><li>Increase the lifetime of the network significantly </li></ul><ul><li>Works for MANETs as well </li></ul><ul><ul><li>Handles mobility </li></ul></ul><ul><li>Also considered to be hierarchical protocol </li></ul><ul><ul><li>Each sub-region is a cluster </li></ul></ul><ul><ul><li>Representative node is the cluster-head </li></ul></ul><ul><ul><ul><li>But does not perform any data aggregation </li></ul></ul></ul><ul><li>Not very scalable. As the network size increases distance to the sink increases </li></ul><ul><li>Overhead of forming the grid </li></ul><ul><li>Only the active nodes sense and report data. </li></ul><ul><ul><li>Hence data accuracy is not very high. </li></ul></ul>
  23. 23. Minimum Energy Communication Network (MECN) <ul><li>L. Li and J.Y. Halpern, “Minimum-Energy Mobile Wireless Networks Revisited”. Proc. of IEEE Int. Conf. on Communications (ICC’01), Helsinki, Finland, June 2001. </li></ul><ul><li>Uses graph theory: </li></ul><ul><ul><li>Each node knows its exact location </li></ul></ul><ul><ul><li>Network is represented by a graph G’, and it is assumed that the resulting graph is connected </li></ul></ul><ul><li>A sub-graph G of G’ is computed. </li></ul><ul><li>G connects all nodes with minimum energy cost. </li></ul>A B Connection A requires less energy than connection B because the power required to transmit between a pair of nodes increases as the n th power of the distance between them (n>=2).
  24. 24. QoS Routing In WSN <ul><li>QoS-aware protocols consider end-to-end delay requirements while setting up paths </li></ul><ul><ul><li>End-to-end delay is the most common </li></ul></ul><ul><ul><li>Bandwidth </li></ul></ul><ul><ul><ul><li>Video or image sensors </li></ul></ul></ul><ul><li>Real-time routing in </li></ul><ul><ul><li>Disaster management </li></ul></ul><ul><ul><li>Fire detection </li></ul></ul><ul><ul><li>Tsunami alerts etc. </li></ul></ul><ul><li>QoS in WSN is very challenging </li></ul><ul><ul><li>Already have constraints such as bandwidth and energy </li></ul></ul><ul><ul><li>QoS routing will bring a lot of overhead </li></ul></ul><ul><li>QoS in WSN is still in very early stages </li></ul><ul><ul><li>May require redefinition of QoS for WSN </li></ul></ul>
  25. 25. SPEED <ul><li>A real-time routing protocol for WSN </li></ul><ul><li>T. He et al., “SPEED: A stateless protocol for real-time communication in sensor networks,” in the Proceedings of International Conference on Distributed Computing System s, Providence, RI, 2003. </li></ul><ul><li>Each node maintains info about its neighbors and uses geographic forwarding to find the paths </li></ul><ul><li>Tries to ensure a certain speed for each packet in the network </li></ul><ul><li>Congestion avoidance </li></ul>
  26. 26. Energy-aware QoS Routing Protocol <ul><li>K. Akkaya and M. Younis, &quot;Energy-aware routing of time-constrained traffic in wireless sensor networks,&quot; in the International Journal of Communication Systems, Vol. 17(6), pp. 663-687, 2004. </li></ul><ul><li>Finds least cost and energy efficient paths that meet the end-to-end delay during connection </li></ul><ul><ul><li>Energy reserve, transmission energy </li></ul></ul><ul><li>WFQ (Weighted Fair Queuing) packet scheduling model used to support best-effort and real-time traffic </li></ul><ul><ul><li>WFQ can provide upper delay bound </li></ul></ul><ul><ul><ul><li>Used with constant data rate </li></ul></ul></ul>
  27. 27. Summary of Protocols for WSN

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