1 / 16

Boundary detection in sensor networks for phenomenon classification

This presentation explores innovative techniques for boundary detection in sensor networks aimed at improving phenomenon classification. The main objective is to ascertain if a target sensor is part of the edge and to identify the boundary of the measured phenomenon. Using GloMoSim and the AdHoc On-Demand Vector Routing Protocol (AODV), we present simulation results showcasing network throughput and routing overhead mitigation. The application scenarios include landmine detection, contouring, and surveillance. Future improvements will focus on resilience to security threats and enhancing protocol efficiency.

altessa
Télécharger la présentation

Boundary detection in sensor networks for phenomenon classification

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Boundary detection in sensor networks for phenomenon classification GROUP MEMBERS : AKSHAY BALASUBRAMANIAN NANDAKUMAR P VENUGOPAL SATISH RAMASWAMI SALEM INSTRUCTOR : Dr Pao-Lo Liu TA : Mr Saurav Bandyopadhyay

  2. Presentation overview • Objective • Optimization criterion • Where it can be used • Simulation tool and protocol used • Actual overview of Simulation • Results • Future Improvements • Questions

  3. OBJECTIVE • To identify whether a Target Sensor is a part of the edge • To identify the boundary of the Phenomenon being measured

  4. Optimization Criterion • Throughput in the Network layer • Routing overhead in the MAC layer Assumptions: General class of boundaries Mild regularity Achievable Performance

  5. Where it can be used? • Landmine detection • Contouring • Unit monitoring and surveillance

  6. Simulation tool and Protocol used • Choice of environment - GloMoSim • Choice of Protocol -AdHoc On Demand Vector Routing Protocol (AODV)

  7. What is GloMoSim • GloMoSim is a simulation environment for wirelesssystems. • Source Code is written primarily in C and uses the Parsec compiler to create executable. • Layer Models : Physical Data Link Network Transport Application

  8. Classification of routing Protocols • Proactive – When a packet needs to be forwarded, the route is already known. *Each node maintains routing information to all other nodes in the network. *When updates are made it is propagated throughout the network. • Reactive – Determine a route only when data has to be sent. each node *Nodes that are not selected in the path do not maintain routing information. *The route discovery process is initiated by the source node.

  9. What is AODV • It is a reactive type of routing protocol. • Packet types Used RREQ - broadcast route discovery message RREP - unicast message to validate a path RERR - Error message to inform nodes of link failure • Routing information stored at the nodes • When a route to a new destination is needed, the node broadcasts a RREQ to find a route to the destination • Routing table stores only active routes, unused routes are removed

  10. Protocol modifications • Novelty involved -Is it my packet? -Do I have to stay awake!! I am better of sleeping Power-off mode in MAC layer

  11. Results to Substantiate Claim • Throughput • Power Constraint

  12. Actual Overview of Simulation Red – Original Blue – Our Algorithm

  13. Power versus Time Red – Original Blue – Our Algorithm

  14. Scope for Improvement • Resilience to security threats and Attacks • Denial of Service • Packet flooding • Impersonation • Black hole problem

  15. QUESTIONS ?

More Related