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![REFERENCES [1] J. A. Carballido, I. Ponzoni, and N. B. Brignole, “CGD-GA: A graphbased genetic algorithm for sensor network design,” Inf. Sci., vol. 177,no. 22, pp. 5091– 5102, 2007. [2] F. C. Chang and H. C. Huang, “A refactoring method for cache-efficient swarm intelligence algorithms,” Inf. Sci., vol. 192, no. 1, pp. 39–49,Jun. 2012.](https://image.slidesharecdn.com/faultnoderecovery-150510174740-lva1-app6892/75/Fault-Node-Recovery-Algorithm-for-a-Wireless-Sensor-Network-29-2048.jpg)
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Fault Node Recovery Algorithm for a Wireless Sensor Network
The document discusses a fault node recovery (FNR) algorithm for wireless sensor networks (WSN) aimed at enhancing the network's lifespan by recharging malfunctioning sensor nodes. It compares the FNR with existing algorithms like grade diffusion and directed diffusion, highlighting its advantages in power management and routing efficiency. The proposal includes a detailed design, system architecture, and future enhancements to minimize sensor replacement and optimize routing paths.
Fault Node Recovery Algorithm for a Wireless Sensor Network
- 1. Implementation of FaultNode Recovery Algorithm For a Wireless Sensor Network Presented By: Yogesh V K
- 2. Agenda Introduction RelatedWork Problem Statement Proposed Approach System Design Detail Design Pseudo Code Snap Shots Conclusion Future Enhancement
- 3. INTRODUCTION Wireless Sensor Networks WSN combines sensing, computation, and communication into single tiny device called sensor node. Group of sensors nodes linked by wireless media to perform distributed sensing task The main goal of the WSN is to collect data from the environment and send it to a sink node.
- 5. Types of wirelesssensor networks Unstructured WSN Ad-hoc deployment Structured WSN Pre-planned deployment
- 6. Related work GradeDiffusion algorithm Directed Diffusion algorithm
- 7. Grade Diffusion algorithm The source node will broadcast the RREQ packets to all its neighbors The neighbors will broadcast to its neighbors The process repeats until the RREQ packet is received by the destination node.
- 8. Disadvantages of GradeDiffusion Algorithm Huge transmission of data will consume lot of power. Decrease the battery life.
- 9. Directed Diffusion algorithm Overcomes the disadvantages of Grade Diffusion algorithm. Broadcasting the neighbors to only first neighbor set. After that nodes are picked up based on hop count. The amount of RREQ exchange is reduced. Amount of power required is less as compared to Grade Diffusion.
- 10. Problem Statement InGrade Diffusion Algorithm it creates Multiple Routing path. Consume lot Power and Energy Decrease the Battery life Reasons for fault Node Due to low battery power Software failure Hardware failure
- 11. Fig1: Wireless sensornode routing. Fig 2: Wireless sensor node routing path when some nodes are not functioning.
- 12. PROPOSED APPROACH FAULT NODERECOVERY ALGORITHM FNR is based on the Grade Diffusion Algorithm. Recharges the sensor nodes which are not functioning. Increase the life time of the wireless sensor network.
- 13. The processof finding the set of nodes whose battery power is less than threshold is called Fault Node Determination. The proposed algorithm finds the dead node and recharge with new battery power. Find the Single shortest path.
- 14. SYSTEM DESIGN Node Placement Algorithm Routing Table Formation Route Determination FaultNode Prediction Fault Node Recovery Analysis as compared to Grade Diffusion
- 15. Data Flow Diagram– Routing Formation Algorithm Node id and positions of nodes Create a routing table for a node Compute distance between nodes to other nodes Create a map of node id and distance Store the map ( node id, distance) Node Information
- 16. Data Flow Diagram– Fault Node Detection Battery Threshold, Rechargeable Battery Neighbor Discovery Compare Threshold Battery Add it to the Dead Node List List of Dead Nodes Neighbor Discovery
- 17. Detail Design Grade DiffusionAlgorithm
- 18. Pseudo Code Like thisrouting tables are generated for 20 nodes. Finding the Route from the source to Destination Source Node=2 Destination Node=8 Coverage Area=20 Grade Diffusion
- 19. Route Discovery forRoute1 using Grade Diffusion Step1: The source Node 2 will first find the nodes in its routing table {1,2,3,4,5,6,7,8,9,10.11,12,13,14,15,16,17,18,19,20} Step2: Find the nodes in the coverage area which are within 20 m {1,3,4} Step3: Check whether the destination node is present in the neighbor l node list {8} is present in {1,3,4} or not Step4: Find the nodes in the forward direction towards destination node {3,4} Step5: Pick the first node {3} Step6: Now the source node will be {3} The route1 that is discovered is given as {2->3->5->6->8}
- 20. Route Discovery forRoute2 using Grade Diffusion Step1: The source Node 2 will first find the nodes in its routing table {1,2,3,4,5,6,7,8,9,10.11,12,13,14,15,16,17,18,19,20} Step2: Find the nodes in the coverage area which are within 20 m {1,3,4} Step3: Check whether the destination node is present in the neighbor node list {8} is present in {1,3,4} or not Step4: Find the nodes in the forward direction towards destination node {3,4} Step5: Pick the second node {4} Step6: Now the source node will be {4} Step7: The route discovered until now will be {2->4} Step8: The source node 4 will fetch nodes in its routing table ……… The route2 that is discovered is given as {2->4->6->8}
- 21. Fault Node RouteDiscovery
- 22. Min - HopRouting
- 23.
- 27. Conclusion The FNRalgorithm recharge fewer sensor nodes. Reuses the most routing paths. Increasing the WSN lifetime Reducing the replacement cost.
- 28. Future Enhancement The FNRalgorithm requires replace fewer sensor nodes. Reuses the most routing paths. Increasing the WSN lifetime
- 29. REFERENCES [1] J.A. Carballido, I. Ponzoni, and N. B. Brignole, “CGD-GA: A graphbased genetic algorithm for sensor network design,” Inf. Sci., vol. 177,no. 22, pp. 5091– 5102, 2007. [2] F. C. Chang and H. C. Huang, “A refactoring method for cache-efficient swarm intelligence algorithms,” Inf. Sci., vol. 192, no. 1, pp. 39–49,Jun. 2012.
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