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Enhancing Techniques for Detection and Avoidance of Congestion in Wireless Sensor Networks Scholar C. Ram Kumar Assistant Professor SNS College of Engineering.

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Presentation on theme: "Enhancing Techniques for Detection and Avoidance of Congestion in Wireless Sensor Networks Scholar C. Ram Kumar Assistant Professor SNS College of Engineering."— Presentation transcript:

1 Enhancing Techniques for Detection and Avoidance of Congestion in Wireless Sensor Networks Scholar C. Ram Kumar Assistant Professor SNS College of Engineering Guide Dr S Karthik Dean - CSE SNS College of Technology

2 Introduction Wireless Sensor Networks are networks that consists of sensors which are distributed in an ad hoc manner. These sensors work with each other to sense some physical phenomenon and then the information gathered is processed to get relevant results. Wireless sensor networks consists of protocols and algorithms with self-organizing capabilities. 2

3 Example of WSN 3

4 Objectives The main objective is to detect the congestion and also to avoid that using WSN. Parameters: To reduce packet loss. To improve energy efficiency. To reduce delay.

5 Congestion which comprises three mechanisms Use dual buffer thresholds and weighted buffer difference for congestion detection, Flexible Queue Scheduler for packets scheduling, A bottleneck-node-based source sending rate control scheme.

6 Network topology

7 7 Wireless Sensor Network(WSN) vs. Mobile Ad Hoc Network (MANET) WSNMANET SimilarityWirelessMulti-hop networking SecuritySymmetric Key CryptographyPublic Key Cryptography RoutingSupport specialized traffic pattern. Cannot afford to have too many node states and packet overhead Support any node pairs Some source routing and distance vector protocol incur heavy control traffic ResourceTighter resources (power, processor speed, bandwidth) Not as tight.

8 Route Requests in DSR B A S E F H C G I Represents a node that has received RREQ for D from S D

9 Route Requests in DSR B A S E F H C G I Represents transmission of RREQ Broadcast transmission D

10 Route Requests in DSR B A S E F H C G I RREQ keeps a list of nodes on the path from the source D

11 Route Reply in DSR S E F D Represents links on path taken by RREP B A H C G I

12 Ad Hoc On-Demand Distance Vector Routing (AODV) Now RFC 3561, based on DSDV Destination sequence numbers provide loop freedom Source sends Route Request Packet (RREQ) when a route has to be found Route Reply Packet (RREP) is sent back by destination Route Error messages update routes

13 Route Requests in AODV B A S E F H C G I Represents a node that has received RREQ for D from S D

14 Route Requests in AODV B A S E F H C G I Represents transmission of RREQ Broadcast transmission D

15 Route Requests in AODV B A S E F H C G I Represents links on Reverse Path D

16 Reverse Path Setup in AODV B A S E F H D C G I Node C receives RREQ from G and H, but does not forward it again, because node C has already forwarded RREQ once

17 Route Reply in AODV B A S E F H D C G I Represents links on path taken by RREP

18 Congestion Detection Congestion Detection can be found by using Buffer State. Buffer state contains 1. Accept state, 2. Filter state, 3. Reject state.

19 Buffer state If 0≤N≤Qmin (Accept State), If Qmin≤N≤Qmax ( Filter State), If Qmax≤N≤Q (Reject State).

20 Flexible Queue Scheduler In this method, it will dominate the low priority packet when high priority packet arrives in queue. When the queue overflows, high priority data may be dropped. Dynamically select the next packet to send based on the Round Robin algorithm. In order to overcome the disadvantage in this method, Bottleneck node based source data sending rate control is used.

21 Bottleneck method Determine routing path status from a certain node to sink. Bottleneck node detection and source data sending rate control. Using this scheme, source data sending rate can be regulated more accurately.

22 Determination of routing path status from a certain node to sink Its child node overhears this information and compares its own forwarding delay D (i) with its parent p’s data forwarding delay D (p) and does the following calculation: Dmax (i) =MAX {D (p), D (i)} Where, Dmax (i) is the path status from node i to sink. This process is recursively computed up to the final source node.

23 Bottleneck node detection and data sending rate control When source node s overhears data from its parent p, it extracts the delay information piggybacked in the data packets and set its data sending rate Gs as: Gs=1/Dmax (p)

24 Energy Efficiency The drawbacks of packet drop and improves the energy efficiency as well as, if the energy level is reduced to the particular child node during transmission of packets, it informs the parent node to change the transmission to another child node which is nearest to it for preventing the packet drop.

25 Routing challenges and design issues Node deployment Data routing methods Node/link heterogeneity Fault tolerance Coverage Transmission media Connectivity Data aggregation Quality of Service

26 Data Mule Data Mule – a mobile entity present in the environment that will pick up data from the node when in range, buffer it, and drop off the data at base station ex: People, Vehicles, Livestock

27 Data Mule Base Station Leaf Node

28 Data Mule

29 Base Station

30 Data Mule - Applications Collecting a data in a sparse sensor network Tracking movement of mobile elements Vehicles Livestock Wild Animals

31 Data Mule Base Station

32 Habitat Monitoring on Great Duck Island http://www.greatduckisland.net/ Intel Research Laboratory at Berkeley initiated a collaboration with the College of the Atlantic in Bar Harbor and the University of California at Berkeley to deploy wireless sensor networks on Great Duck Island, Maine (in 2002) Monitor the microclimates in and around nesting burrows used by the Leach's Storm Petrel Goal : habitat monitoring kit for researchers worldwide

33 Fire Bug Wildfire Instrumentation System Using Networked Sensors Allows predictive analysis of evolving fire behavior Firebugs: GPS-enabled, wireless thermal sensor motes based on TinyOS that self-organize into networks for collecting real time data in wild fire environments Software architecture: Several interacting layers (Sensors, Processing of sensor data, Command center) A project by University of California, Berkeley CA.

34 Preventive Maintenance on an Oil Tanker in the North Sea: The BP Experiment Collaboration of Intel & BP Use of sensor networks to support preventive maintenance on board an oil tanker in the North Sea. A sensor network deployment onboard the ship System gathered data reliably and recovered from errors when they occurred. The project was recognized by InfoWorld as one of the top 100 IT projects in 2004,

35 Rumor Routing Basic scheme Each node maintain A lists of neighbors An event table When a node detects an event Generate an agent Let it travel on a random path The visited node form a gradient to the event When a sink needs an event Transmit a query The query meets some node which lies on the gradient Route establishment

36 Schemes to be used DCAR Mechanism Water drop Algorithm Ant Algorithm LEACH – Low Energy Adaptive Clustering Hierarchy

37 THANKING YOU


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