Continuous Residual Energy Monitoring i n Wireless Sensor Network s
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Transcript of Continuous Residual Energy Monitoring i n Wireless Sensor Network s
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1Department of Computer ScienceCity University of Hong Kong
Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring
in Wireless Sensor Networks
Song Han and Edward Chan
Department of Computer Science, City University of Hong Kong83 Tat Chee Avenue, Kowloon, HONG KONG
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Agenda
Introduction Objective Related Work System Model Methodology Performance Analysis Conclusion
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Introduction
Features of Wireless Sensor Network (WSN) Large scale Static nodes Limited resources
Residual Energy Monitoring (REM) Get WSN’ s energy information Maintain the WSN active Accurate vs. Approximate monitoring
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Objective
To propose an approach for monitoring residual energy information continuously in the WSN
Scalability
Accuracy
Maximized lifetime & Minimized message cost
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Related Work
Energy Consumption Prediction by Nath et al. Energy dissipation model Probabilistic prediction scheme
Residual Energy Scan by Zhao et al. Notion of energy map In-network aggregation Abstract representation of energy graph
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
System Model
Base Station
m
Communication Range Rm
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Methodology
Topology Discovery Divide the WSN into several clusters Construct a monitoring tree
Residual Energy Monitoring Abstracted Representation of Energy Graph Determining the Local Energy Graph In-Network Aggregation of Energy Graphs
Topology Maintenance
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Discovery
Step 1: A “Topology Discovery Request” is initiated from the base station and propagates through controlled flooding.
Step 2: WSN is divided into clusters based on TopDisc algorithm by Nath et al.
A simple greedy log (n)-approximation algorithm. Communication range is reduced to R/2.
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Discovery (cont.)
Base Station
Topology Discovery Request
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Discovery (cont.)
Base Station
Topology Discovery Request
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Discovery (cont.)
Base Station
Topology Discovery Request
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Discovery (cont.)
Base Station
Topology Discovery Request
Become Black after an interval
And broadcast the request again
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Discovery (cont.)
At the end of this phase, Monitoring tree is constructed (Figure.2)
Consists of black nodes and grey nodes:
Black node: Cluster head
Grey node: Bridge between two heads
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Discovery (cont.)
Ordinary Node
Cluster Boundary
Cluster Head
Delivery Node
Figure.2. Monitoring Tree
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Residual Energy Monitoring
Abstracted Representation of Energy Graph
Structure of the message
Structure of the polygon information
Sender ID Receiver ID Energy Range Polygon Information
Part 1 Part 2 Part 3 Part 4
Outside contour
Hole 1
Hole 2
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Residual Energy Monitoring (cont.)
Determining the Local Energy Graph
1) Divide sensors according to energy range
2) Get the convex contour for each energy range
3) Perform Boolean Computing on the set of polygons
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Residual Energy Monitoring (cont.)
In-Network Energy Graph Aggregation
Scheme:
Forward energy information along the monitoring tree from leaf to root.
Non-leaf node merges two polygons if they are in the same energy range and adjacent physically.
Vertex number and communication cost are reduced.
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Maintenance
Node Selection Criteria Residual energy Proximity to lower energy range
X Y
After Selection Initial State
X Y
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Topology Maintenance (cont.)
Static topology maintenance schema
Parent cluster selects a new head; Child cluster selects new head and deliver node; Both new head nodes broadcast the change in
their clusters.
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Performance Analysis
Performance Metrics:
Residual reachable nodes Fidelity Total Message Cost
Methods to compare: Continuous Residual Energy Monitoring (CREM) Centralized Collection Static Clustering
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Cost ratio CREM vs. Centralized Collection
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Fidelity vs. Network Size
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
CREM Fidelity vs. Monitoring Cycles
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Residual reachable nodes vs. Monitoring Cycle
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Methods Comparison:Fidelity vs. Monitoring Cycles
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Message Cost: CREM vs. static clustering
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
Conclusion
In this paper, we proposed a hierarchical structure for energy monitoring, in the monitoring process, we use the in-network graph aggregation and node selection schema to reduce the message cost, expand the lifetime of the WSN and at the same time, we maintain the accuracy of the result energy graph.
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Department of Computer Science
City University of Hong Kong
Continuous Residual Energy Monitoring in Wireless Sensor Networks
References [1] A. F. Mini, Badri Nath and Antonio A. F. Loureiro, “Prediction-
based Approaches to Construct the Energy Map for Wireless Sensor Networks”, Proc. 21st Brasilian Symposium on Computer Networks, Natal, RN, Brazil, May 19-23, 2003.
[2] J. Zhao, R. Govindan, and D. Estrin, “Computing aggregates for monitoring wireless sensor networks”, Technical Report 02-773, USC, September 2003.
[3] B. Deb, S. Bhatangar, and B. Nath, “A Topology Discovery Algorithm for Sensor Networks with Applications to Network Management”, Proc. IEEE CAS Workshop on Wireless Communications and Networking, Pasadena, USA, Sept. 2002.
[4] Michael V. Leonov, Alexey G. Nikitin, “An Efficient Algorithm for a Closed Set of Boolean Operations on Polygonal Regions in the Plane”, Preprint 46, Novosibirsk, A. P. Ershov Institute of Informatics Systems, 1997.