1. Connected Sensor Cover Problem
Himanshu Gupta, Samir R. Das, and Quinyi Gu, "Connected sensor cover: self-organization of sensor networks for efficient query execution," Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing (MobiHoc03), pp , Annapolis, MD, USA, 2003.
Presented By Donghyun Kim July 2, Mobile Computing and Wireless Networking Research Group
at University of Texas at Dallas

2. Sensor Node Component Characteristics Sensor Data Processor
Wireless Communication Module
Characteristics
Small Size
Low-cost (Ideally)
Low-Power
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

3. Sensor Network Consisted of a large number of sensor nodes.
Nodes are densely deployed either inside or near to the phenomenon (event).
Support multi-hop message exchange.
Random deployment is possible
Self-organizing capabilities
Cooperative capabilities
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

4. Sensor Networks Applications
Sensing target
Temperature, humidity, vehicular movement, lightning condition, pressure, soil makeup, noise levels, and etc.
Sensor nodes can be used for
Continuous sensing, event detection, event ID, location sensing, and local control of actuators.
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

5. Sensor Networks Applications – cont’
Military application
Monitoring friendly forces, equipment and ammunition
Reconnaissance of opposing forces and terrain
Nuclear, biological and chemical attack detection and reconnaissance
Battle damage assessment
Battlefield surveillance
Targeting
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

6. Sensor Networks Applications – cont’
Environmental applications
Forest fire detection
Bio-complexity mapping of the environment
Flood detection
Precision Agriculture
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

7. Sensor Networks Applications – cont’
Health applications
Tele-monitoring of physiological data
Tracking and monitoring doctors and patients inside a hospital
Drug administration in hospitals
Home applications
Home automation
Smart environment
Other commercial applications
Environmental control in office buildings
Interactive museums
Detecting and monitoring car thefts
Managing inventory control
Vehicle tracking and detection
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

8. Connected Sensor Cover Problem
Motivation
Spatial Queries: DATA (Timestamp, Location)
Limited Battery Power
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

9. Connected Sensor Cover Problem – cont’
Objectives
The sensing regions of the selected set of sensors cover the entire region of the query.
The selected set of sensors form a connected subgraph of a Disk Graph with Bidirectional link (DGB).
It is NP-Hard.
Notations
: the set of vertices
: the sensing region of .
: connected sensor cover (at the end)
: query
: target region being queried
must satisfy…
The subgraph induced by has to be connected
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

10. Connected Sensor Cover Problem – cont’
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

11. Subelements and Valid Subelements
A subelement is a set of points.
Two points belong to same subelement iff they are covered by the same set of sensing regions.
Given a query region , a subelement is valid if its region interescts with
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

12. Greedy Algorithm Basic Idea is current cover.
A Candidate Sensor has an intersection with any node in and target region.
A Candidate Path is a set of nodes and it connects a node in to
A with the highest benefit is selected and all nodes in it is added to .
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

13. Greedy Algorithm– cont’
What is benefit?
Let a candidate path covers a set of uncovered valid subelements .
Then, benefit is defined as
Objectives function
Among all possible s and corresponding s we pick and with maximum benefit.
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

14. Performance Analysis Basic Idea
Based on “Charging (Weighting) Scheme”. We are going to compute how many sensors do we need to cover one sensing region at the worst case.
Partition all area into pieces with same size (sensing region), where is an optimal sensor cover.
Compute the maximum charge inside one sensing region. Denote this is Then, the total charge is no more than and this algorithm is - approximation algorithm.
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

15. Performance Analysis – cont’
When a candidate path is selected, we charge the uncovered valid subelements covered by with
Each uncovered valid subelement gets charged by , where is the number of uncovered valid subelemets covered by .
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

16. Performance Analysis – cont’
Assume at each stage of the algorithm, some uncovered valid subelements in the sensing region get covered.
Denote be the number of uncovered valid subelements of after iteration.
is the total number of valid subelements of .
The number of valid subelements covered during the jth iteration is
Then, assuming the loop runs of iterations, the total charge accumulated by during the entire course of the algorithm is
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

17. Performance Analysis – cont’
Link Radius
The link radius of a sensor network is defined as the maximum communication (hop) distance between any two sensor whose sensing regions interest.
Denote the maximum number of subelement is a sensing region as . Then,
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

18. Other Ideas Steiner Tree Based Approach Weighted Version
Conceptually, having the same theoretical bound.
Expected to incur more messages.
Weighted Version
Each sensor on has a weight and ’s weight is the sum of weight of sensors in it.
Objective function has to be modified accordingly.
Approximation ratio:
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

19. Distributed Version
Presented by Donghyun Kim on July 2, 2008 Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas