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Transcript of 1 Distributed Adaptive Sampling, Forwarding, and Routing Algorithms for Wireless Visual Sensor...
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Distributed Adaptive Sampling, Forwarding, and Routing Algorithms for
Wireless Visual Sensor Networks
Johnsen Kho, Long Tran-Thanh,Alex Rogers, Nicholas R. Jennings
{jk05r,ltt08r,acr,nrj}@ecs.soton.ac.uk
12th May 2009
Third International Workshop on Agent Technology for Sensor Networks (ATSN-09)
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Background: Wireless Visual Sensor Network (WVSN). Research Challenge & Aims.
Inter-Related Adaptive S/F and Routing : Problem Description. Information Metric. The Mechanism:
Algorithm with Fixed Routing. Algorithm with Flexible Routing.
Empirical Evaluations. Conclusions & Future Work.
Outline
12th May 2009 ATSN-09
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Wireless VisualSensor Network WVSN characteristics:
Array of smart camera devices, Basic processing and compression of (usually large) visual data Decentralised control regime A base-station (BS) to fuse and analyse collected data.
WVSNs are increasingly being deployed for: Object tracking, Unattended area surveillance, Other security related applications.
Both pictures are taken from Kleihorst et al., 2006
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Inter-Related S/F +Routing in WVSNs
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Constraints: Heavy energy constraints on the nodes Sampling is relatively expensive (due to large size of data packets) Forward own data vs. relay data from the others
Sampling, Forwarding (and Routing) share the same energy budget Their performance in efficient data collection are inter-related Efficient coordination is needed
Related research works: USAC: Utility-based Sensing and Communication Protocol (Padhy et al.
2006)
Goal of deployment: efficient information collection
Problem: these algorithms are not efficient for maximising information collection in WVSNs due to the myopic decisions of the agents during operation
Research Challenge: Efficient energy-aware coordination between sampling and
routing actions in WVSNs Minimise energy waste on taking useless actions Non-myopic decisions are needed
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Research Challenges and Aims
12th May 2009
Research Aims: Information metric to measure the usefulness of data Efficient S/F + routing mechanisms
Small control messages in the coordination phase Energy-awareness
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Background: Wireless Visual Sensor Network (WVSN). Research Challenge & Aims.
Inter-Related Adaptive S/F and Routing: Problem Description. Information Metric. The Mechanism:
Algorithm with Fixed Routing. Algorithm with Flexible Routing.
Empirical Evaluations. Conclusions & Future Works.
Outline
12th May 2009 ATSN-09
The goal is to maximise the total information value delivered to BS in each round
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Model Description
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Set of heterogeneous cooperative nodes I={1,…..,n}. Each node i ∈ I :
mi different sampling (or frame) rates
Each data packet p has the information value of
Bi energy budget to:
Sampling data Forwarding data
)( pVi
The BS collects data from the nodes periodically rounds
},...,{ 21 imiiii cccC
Each node’s memory is flushed and reinitialised after each round
Not delivered data is useless for the application
The nodes can choose one sampling rate for each round
Assumptions:
Nodes are rechargeable Bi can be entirely used in each round
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Information Metric
Several techniques for valuing information: Kalman Filter [Guestrin et al. 2005; Rogers et al. 2006]. Simple Linear Regression [Padhy et al. 2006]. GP Regression Technique [Mackay 1998; Seeger 2004, Stranders et al. 2008, Kho et al. 2009].
12th May 2009 ATSN-09
In our model, we use a generic information valuation function
)( ii rV non-decreasing function
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The Algorithms (Overview)
Algorithm with fixed routing: routing tree is already established by a
routing protocol (e.g. AODV) calculate optimal sampling rates
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Phase I: each parent node broadcasts
its capacity to child nodes
Phase II: each node transmits maximal
possible contributions to its parent
Phase III: parents allocate packet
forwarding capacities to its children
Algorithm with flexible routing: optimal routing + optimal sampling are
to be determined
Algorithm with fixed routing
0 1 2 ... M-1 M
0 12 20 ... 27 27
0 1 2 ... 20 20
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Algorithm with Fixed Routing (Phase II)
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Each node i maintains an array of 3-tuples: iO })(),(,{ * ncnUnO iii
n : number of packets node i sends to its parent
)(nU i : maximal information value node i can contribute with n packets
)(* nci : sampling rate at node i in this case (node i’s own contribution)
If i is a leaf node: Only its own data is considered Filling is straightforwardiO
MJJJ ,..., 21
If i is not a leaf node: Its child nodes: Wait until all has arrived Maintain a table as follows
kJO
iT
:)(0JI OO
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Algorithm with Fixed Routing (Phase II) - cont’d
12th May 2009
:0J
O]}[],1[{max],[
0mlOmkTlkT kJlm
Dynamic programming:
0 1 2 ... M-1 M
:1JO
:iT
)( 0JI Own data (similar to the previous case)
1JI Own data + data from J1
0 1 2 ... M-1 M
0 12 20 ... 27 27
0 1 2 ... 20 20
0 1 2 ... M-1 M
0 16 22 ... 58 58
0 1 2 ... 31 31
0 12 20 ... 27 27
0 16 ... 75 75
21 JJI Own data + data from J1 and J2 0 18 30 ... 100 120
MJJI ...1Own data + data from all children
0 ... ... ... ... ...
0 30 40 ... 100 125
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0 1 2 ... M-1 M
0 30 40 ... 100 125
0 1 2 ... 12 14
:iO
M: the capacity of node i’s parent
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Algorithm with Fixed Routing (Phase III)
Efficient: it satisfies the data flow
conservation of the network no energy is wasted by
transmitting data that later will not be delivered to BS
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When control messages reach the leaf nodes, that node start to transmit data
The BS maintains its own T table Easily detects the contributions
of its children
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Algorithm with Flexible Routing (Overview)
The data readings from different nodes could be sent through different
routes if there are more than one option to choose from.
Minor restrictions:
Nodes always forward their data toward the BS; that is, they will not forward
data to a node that is further from the BS (in terms of hop count) than
themselves.
Sampled data from a same
node must be sent in bundle
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Algorithm with Flexible Routing
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: set of parents of node i
: set of descendants of node i
bundles to send
combinations
iOnode i has to send -s for all of the combinations
curse of dimensionality!!!
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Background: Wireless Visual Sensor Network (WVSN). Research Challenge & Aims.
Inter-Related Adaptive S/F and Routing: Problem Description. Information Metric. The Mechanism:
Algorithm with Fixed Routing. Algorithm with Flexible Routing.
Empirical Evaluations. Conclusions & Future Work.
Outline
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Algorithm with flexible routing: deliver more information, but has greater computational and communicational cost
Algorithm with fixed routing can be applied on an efficiently chosen spanning tree Fast, but sub-optimal result
A trade-off between the loss in information and the saving in resources
Empirical Evaluation
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Benchmark Algorithm: The Uniform Non-Adaptive S/F and Routing
each sensor divides its energy budget equally
Linear information valuation function
Empirical Evaluation (cont’d)
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Algorithm with flexible routing is used here Random tree is generated, algorithm with fixed routing is used on this tree
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Empirical Result I
Algorithm with flexible routing produces optimal performance
Uniform non-adaptive algorithm has the worst performance
By choosing a spanning tree efficiently, fixed routing can achieve near-optimal performance
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Empirical Result II
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Conclusion & Future Work
Two novel and optimal decentralised algorithm: Algorithm with fixed routing: calculates the optimal sampling actions
Algorithm flexible routing : optimal in both sampling and routing
Algorithm with flexible routing is optimal, but has higher communication and computational cost
Algorithm with fixed routing can achieve near-optimal result on an efficiently chosen spanning tree
Future work: Develop an efficient way to choose the best spanning tree (e.g. using learning
approach)
Relax the assumptions (topology hierarchy, flexible sampling rate)
Take more rounds into account (long-term data collection)
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Thank you (Any Questions?)