This document discusses research challenges in real-time multimedia monitoring in large-scale wireless multimedia sensor networks. It describes how these networks enable new monitoring applications but face challenges due to limited computational and energy resources. The document outlines solutions needed at the MAC, network, and transport layers to efficiently deliver visual data while meeting requirements for steady data flows and delay-bounded delivery. It also discusses challenges in areas like multimedia coding, in-network processing, energy harvesting, and cross-layer optimization across the protocol stack.
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Real-time monitoring challenges in large-scale wireless multimedia sensor networks
1. Real-time Multimedia Monitoring in
Large-Scale Wireless Multimedia Sensor
Networks: Research Challenges
Joint work by:
M.Cesana, A.Redondi – Politecnico di Milano
N. Tiglao, A. Grilo – INESC-ID/INOV/IST
J. M. Barcelo-Ordinas, M. Alaei – Universitat Politecnica de Catalunya
P. Todorova – Fraunhofer FOKUS
2. MWMSN Project
Multi-tier Wireless Multimedia Sensor
Networks
Goal: To enable support for enhanced
monitoring and tracking applications through
multimedia visual/audio wireless sensor nodes
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3. Outline
Introduction
Real-time multimedia monitoring applications
Efficient delivery of visual data in WMSNs
MAC Layer
Network Layer
Transport Layer
Research challenges and final discussion
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4. Introduction
WSN equipped with multimedia sensors give
birth to WMSN.
They enable a new class of monitoring
applications, but demanding in terms of:
computational resources
energy resources
Need for innovative solutions:
combination/optimization techniques at
the different layers of the protocol stack
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5. Real-Time Multimedia Monitoring
Supervised monitoring (Image/Video-based)
Delivery of compressed image/video flows,
analyzed by a human operator
Low bitrate achievable with complex encoders
(e.g. H.264/AVC), not supported by WMSN
Suitable solutions: Object-based approaches,
Distributed Video Coding
Challenge: Successful implementation of these
techniques
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6. Real-Time Multimedia Monitoring
Unsupervised monitoring (Feature-based)
Use visual features to describe the underlying pixel
content
Suitable for a broad range of monitoring tasks
(e.g., object recognition, face detection…)
Main challenges:
Coding of visual features
Low-complexity feature extraction algorithms
Rate-accuracy models for resources allocation
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7. MAC Layer
Main requirements for video streaming
over WMSN:
Steady-flow of information
Delay-bounded delivery of packets
As a consequence, the MAC layer has to:
support reliable communication
be QoS-aware
save as much energy as possible
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8. MAC Layer – available solutions
Available solutions to tune QoS metrics:
Power control
Traffic class differentiation (Q-MAC)
Contention-free vs. contention-based approaches
Duty-cycling control
Queuing and scheduling mechanisms
Error control mechanisms
For WMSN, most important features are:
Intra/Inter-node traffic class differentiation
Node synchronization (duty-cycling control)
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9. MAC Layer – available solutions
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10. Network Layer: Routing
Traditional solutions for WSN focused on energy
consumption
In the WMSN case, need also for real-time
delivery
Desirable features
Traffic differentiation and joint-optimization of
multiple QoS goals
Resource balancing
Fast adaptation to change in monitoring conditions
Support to in-network processing / cross-layer opt.
Scalability
Energy-harvesting awareness
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11. Network Layer – available solutions
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12. Transport Layer
Similarly to the network layer case, available
solutions are not suitable for WMSN.
Design guidelines
Differentiated reliability
Trade-off between reliability/timeliness
Media-centric collaborative reliability
Congestion control
Cross-layer optimization
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13. Transport Layer – available solutions
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14. Collaborative Sensing in WMSN
Multimedia nodes are characterized by a
directional sensing model (FoV)
They can be grouped basing on their common
sensing coverage
Several challenges
Directional coverage
Clustering / Scheduling
Collaboration protocols
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15. Conclusions and Research Challenges
Application Layer (feature-based):
Novel coding techniques
Practical implementations
MAC Layer
Service differentiation
Dynamic duty-cycling control
Network Layer:
In-network processing
Energy harvesting
Transport Layer
Media-centric reliability
Cross-layer optimization with routing
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16. Thank your for your attention!
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17. Project Members
M. Cesana, A. Redondi – {cesana,
redondi}@elet.polimi.it
Multimedia coding, Application
N. Tiglao, A. Grilo – {nestor.tiglao,
antonio.grilo}@inesc-id.pt
Routing and Transport
J. M. Barcelo-Ordinas, M. Alaei –
{joseb,malaei}@ac.upc.edu
MAC Layer
P. Todorova –
petia.todorova@fokus.fraunhofer.de
Collaborative Sensing
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