The Problem of Location Determination and Tracking in Networked Systems Weikuan Yu, Hui Cao, and...
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Transcript of The Problem of Location Determination and Tracking in Networked Systems Weikuan Yu, Hui Cao, and...
The Problem of Location Determination and Tracking in
Networked Systems
Weikuan Yu, Hui Cao, and Vineet MittalThe Ohio State University
The Problem Statement of Location Determination
Devise a scheme that returns the location of the object Location
Absolute location Relative location, e.g. beamforming, web-
hosting
Object Computing device, human, car, tank Information
The Problem Statement of Tracking
Devise a scheme that tracks the location of an object Single object Multiple objects
Location and Tracking
Source localization Location service
Infrastructure based
Non-infrastructure based
Network Object
Challenges Scalability
Locating a mobile user in a large scale network
Locating a node in a mobile ad hoc network Fault-tolerance
Failure of a location server Sensor networks
Limited energy Limited processing power Limited communication range Sensor coordination
Sensor Networks Definition
A spread network of small sensors Tracking moving objects Monitoring multiple objects Detecting low observable objects
Sensor coordination Improved accuracy with aggregated
information Reduced latency with informed selective
coordination Minimize bandwidth consumption Mitigate the risk of node/link failures
Approaches “Everything is related to everything else but
near things are more related than distant things”
“Online tracking of mobile users”, by B. Awerbuch and D. Peleg
Information utility “Information driven dynamic sensor collaboration
for target tracking”, by F. Zhao, J. Shin, and J. Reich
Online Tracking of Mobile Users
Construction of a tracking structure Storing location information of users
at select nodes in the system
Access and Update Protocols Find: using the stored information to
locate the user Move: updating of stored information
on relocation of the user
Information-Driven Sensor Coordination
Making decision based on constraints regarding information, cost and resource.
Metrics: Information Utility A term that quantifies the content of
some data An example of tracking
Information Utility Information Driven Sensor Querying and
Data Routing (IDSQ)M(p(X|Z1, Z2, …, Zj)) = a * U (p(X|Z1, Z2, …, Zj-1, Zj)) – (1-a)
U(Zj)
Information Utility Function: U Based on information entropy, cost to
obtaining new information and Belief state of posterior distribution
Decision fusion in collaborative sensor
networks Collaborative signal processing tasks such as
detection, classification, localization, tracking require aggregation of sensor data.
Decision fusion allows each sensor to send quantized data (decision) to a fusion center. prevent overloading the wireless network conserve energy.
Question: What is “optimal decision fusion”?