Covering Points of Interest with Mobile Sensors
-
Upload
quinn-vega -
Category
Documents
-
view
18 -
download
0
description
Transcript of Covering Points of Interest with Mobile Sensors
Covering Points of Interest Covering Points of Interest with Mobile Sensorswith Mobile Sensors
Milan Erdelj, Tahiry Razafindralambo and David Simplot-RylINRIA Lille - Nord Europe
IEEE Transactions on Parallel and Distributed Systems (TPDS)Digital Object Identifier (DOI): 10.1109/TPDS.2012.46
Outline
• Introduction
• Problem & Goals
• Assumptions and Network Model
• PoI Deployment Algorithm (PDA)– Simulations for Static PoI
• Strategies and simulations for Moving PoI
• Strategies and simulations for Multiple PoIs
• Conclusion
Introduction
• Recently, wireless sensor networks have received a lot of attention due to their potential applications in various areas– such as environmental monitoring.
• The placement of sensors related to coverage issues is intensively studied in the literature, and can be divided into three categories.– Full coverage
– Barrier coverage
– Target coverage
Introduction
• The full coverage problem (Areas of Interest, AoI)– aims at covering the whole area.
– Sensors are deployed to maximize the covered area.
• The barrier coverage problem (Lines of Interest, LoI)– aims at detecting intrusion on a given area.
– Sensors have to form a dense barrier in order to detect each event that crosses the barrier.
Introduction
USA
Intruder
Introduction
• The target coverage problem (Points of Interest, PoI) – aims at monitoring specific points in the field of interest.
Museum Campus Military
Introduction
• The target coverage problem (Points of Interest, PoI) – aims at monitoring specific points in the field of interest.
• Indeed, sensors have to be correctly placed – to monitor the events
– connection between the monitoring sensors and a base station have to be kept to report data.
Problem
• However, existing sensor deployment algorithms belong to the offline schemes– To provide optimal placement of sensors
– For static sensors and PoIs
Goals
• Design the online and distributed sensor deployment schemes for sensors with motion capabilities– To cover PoIs
• (1) Static PoI, (2) Moving PoI, (3) Multiple PoIs
– To maintain the connectivity between each sensor and base station all along the deployment procedure
base station
Point of interest
Goals
• Design the online and distributed sensor deployment schemes for sensors with motion capabilities– To cover PoIs
• (1) Static PoI, (2) Moving PoI, (3) Multiple PoIs
– To maintain the connectivity between each sensor and base station all along the deployment procedure
Assumptions and Network Model
• This paper considers a network composed by mobile sensors and a fixed base station. – At the beginning of the deployment, the base station already
possesses all the information about PoI locations.
• Tasks of the base station– Spread out the information about PoI locations among the sensors
– Collect the information reported from the sensors about the events happening at the PoI
Assumptions and Network Model
• At the beginning of the deployment, the sensors are connected to the base station. – Communication range: R
• Sensors are randomly spread out around the base station at a maximum distance of d < R/4
– Each sensor has the location knowledge of its 2-hop neighborhood.
Assumptions and Network Model
• Let G(V,E) be the graph representing the sensor network.
• V is the set of vertices each one representing a sensor.
• E V2 is the set of edges
G(V,E)
Assumptions and Network Model
• E = {(u,v) V2 | u v d(u,v) ≤ R}, – where d(u,v) is the Euclidean distance between sensors u and v
• N(u) = {v V | d(u,v) ≤ R} is the set of 1-hop neighbors of sensor u.
G(V,E)
Assumptions and Network Model
• Depending on the chosen subset of neighbors– keeping these local connections can provide a global connectivity
of the network.
– Relative Neighborhood Graphs (RNG)
RNG(G)G(V,E)
• Let RNG(G) be the Relative Neighborhood Graph extracted from G(V,E).
• RNG(G) = (V,Erng), where Erng = {(u,v) E | w (N(u) ∩N(v)) d(u,w) < d(u,v) d(v,w) < d(u,v)}.
Assumptions and Network Model
vuw
Assumptions and Network Model
• NRNG(u) is the set of u's RNG neighbors.NRNG(u) = {v,w N(u) v N(w) | d(u,v) < d(v,w) d(u,w) < d(v,w)}.
• RNG+(u) is the farthest sensor of NRNG(u)
• d+(u) is distance between u and RNG+(u)
wvu
• RNG– keeps sensor connectivity with short-distance neighbors
– minimizes the number of connectivity sensors
– improves the coverage quality
Assumptions and Network Model
pbu v
R
R/4
R/4
b: base station
PoI Deployment Algorithm (PDA)
• RNG+(u) is the farthest sensor of NRNG(u)
• d+(u) is distance between u and RNG+(u)
• The maximum distance – which the sensor can travel while maintaining connectivity with its
RNG neighbors
PoI Deployment Algorithm (PDA)
• The maximum distance d – if d < 1 or d < 2, then d = 0
1 is used to avoid an infinite sequence of sensor movements
2 is used to stop sensor movement when their distance to the PoI is below this threshold
Simulations for Static PoI
• Simulation parameters
– PoI is located at position p(70,100)
– Number of sensors: 20
Simulations for Static PoI
• Coverage quality– Number of covering sensors
– Distance between the base station and PoI
Simulations for Static PoI
• Deployment speed (BS to PoI distance: 100, 20 sensors)– Number of covering sensors
– Time
• Mean speed: 0.75m/s, 90m covered distance after 120s
• Max speed: 1m/s, communication range(10)/ decision period(5)=2m/s
• 2/2=1m/s
Implementation
• Wifibot Robots– Wifibot. Mobile robots, www.wifibot.com.
– equipped with • VGA video camera
• user control software
• WiFi device for communicating
• two IR proximity sensors on the front side of the chassis
Implementation
• I-PDA for implementation– In case of obstacle detection
– obstacle avoidance steps are run iteratively until all the auxiliary PoIs are covered or the boundary of the communication range is reached
Conclusion
• This paper proposes PDA algorithm to achieve PoI coverage. – static, moving and multiple PoI coverage are provided
• Connectivity between each sensor and the base station is kept all along the deployment procedure.
• The proposed algorithm is local i.e., every decision taken is based on local neighborhood information only and does not require synchronization.
TheEND