1 Prediction-based Strategies for Energy Saving in Object Tracking Sensor Networks Tzu-Hsuan Shan...
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Transcript of 1 Prediction-based Strategies for Energy Saving in Object Tracking Sensor Networks Tzu-Hsuan Shan...
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Prediction-based Strategies for Energy Saving in Object Tracking Sensor Networks
Tzu-Hsuan Shan2006/11/06J. Winter, Y. Xu, and W.-C. Lee, “Prediction Based Strategies for Energy Saving in Object Tracking Sensor Networks,” IEEE International Conference on Mobile Data Management (MDM'04), Berkeley, CA, Jan. 2004, pp. 346-357.
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Outline
Introduction
Background and Basic schemes
The Prediction-based Energy Saving scheme (PES)
Performance evaluation
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Introduction
What is Object Tracking Sensor Network?A sensor network that the task of the nodes is to report the position of a certain type of object to the base station periodically.
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Background
Application requirements :Suppose each sampling duration takes X seconds.
The application requires the nodes to report the objects’ location every T seconds.
Problem definition :Develop energy saving schemes which minimize overall energy consumption of the OTSN under an acceptable missing rate.
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Basic schemes
Naïve scheme :In this scheme, all the nodes stay in active mode to monitor their detection areas all the time.
The most energy cost scheme with 0 missing rate.
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Basic schemes
Scheduled monitoring scheme :In this scheme, nodes are activated only when needed.
All the nodes wake up every (T-X) seconds for X seconds and go to sleep.
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Basic schemes
Continuous monitoring scheme :In this scheme, only the node who has the object in its detection area will be activated.
An awake node actively monitors the object until the object enters a neighboring cell.
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Basic schemes
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Prediction-based Energy Saving scheme
The basic idea of PES is that all sensor nodes should stay in sleep mode as long as possible.
After a current node performs sensing for X seconds, it will predict the position of the object for the next (T-X) seconds and informs the target node, then go to sleep.
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Prediction-based Energy Saving scheme
PES consists of three parts :Prediction model ─ which anticipates the future movement of an object.
Wake up mechanism ─ decide which nodes will be the target node.
Recovery mechanism ─ is initiated when the network loses the track of an object.
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Prediction model
There are three heuristics for selecting the speed and the direction used by the prediction model :
Heuristics INSTANT ─ assumes that the objects will stay in the current speed and direction.
Heuristics AVERAGE ─ the speed and direction are derived from the average of the object movement history.
Heuristics EXP_AVG ─ it assigns different weights to the different stages of history.
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Wake up mechanism
Based on the different levels of conservativeness, three mechanisms are proposed :
Heuristic DESTINATION ─ only the destination node will be informed.
Heuristic ROUTE ─ the nodes on the route from the current node to the destination node will also be informed.
Heuristic ALL_NBR ─ the neighboring nodes surrounding the route, the current node and the destination node will also be informed.
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Wake up mechanism
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Recovery mechanism
The recovery mechanism contains two steps :Upon the object miss, the previous current node uses the heuristic ALL_NBR to wake up those nodes.
In case that ALL_NBR recovery fails, the previous current node will initiate flooding recovery which wakes up all of the nodes in the network.
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Performance evaluation
The simulation model :Number of nodes : 95 logical sensor nodes.
Monitored region : 120 x 120 m2.
Sensing coverage range : 15m.
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Performance evaluation
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Performance evaluation
Pause time = the time interval that the object changes its speed and direction.
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Performance evaluation
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Performance evaluation
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Performance evaluation
Sampling duration = X.
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Performance evaluation
Sampling frequency = T.