wireless multimedia sensor networks

Real-time Multimedia Monitoring in Large-Scale Wireless Multimedia Sensor

Networks: Research Challenges Joint work by:M.Cesana, A.Redondi – Politecnico di MilanoN. Tiglao, A. Grilo – INESC-ID/INOV/ISTJ. M. Barcelo-Ordinas, M. Alaei – Universitat Politecnica de CatalunyaP. Todorova – Fraunhofer FOKUS

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

2NGI 2012, Karlskrona, Sweden

Outline

Introduction Real-time multimedia monitoring applications Efficient delivery of visual data in WMSNsMAC Layer Network Layer Transport Layer

Research challenges and final discussion

3NGI 2012, Karlskrona, Sweden

Introduction

WSN equipped with multimedia sensors givebirth to WMSN.

They enable a new class of monitoringapplications, but demanding in terms of: computational resources energy resources

Need for innovative solutions: combination/optimization techniques atthe different layers of the protocol stack

4NGI 2012, Karlskrona, Sweden

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

5NGI 2012, Karlskrona, Sweden

Real-Time Multimedia Monitoring

Unsupervised monitoring (Feature-based) Use visual features to describe the underlying pixelcontent

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

6NGI 2012, Karlskrona, Sweden

MAC Layer

Main requirements for video streamingover 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

7NGI 2012, Karlskrona, Sweden

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)

8NGI 2012, Karlskrona, Sweden

MAC Layer – available solutions

9NGI 2012, Karlskrona, Sweden

Network Layer: Routing

Traditional solutions for WSN focused on energyconsumption In the WMSN case, need also for real-time delivery Desirable features Traffic differentiation and joint-optimization ofmultiple QoS goals Resource balancing Fast adaptation to change in monitoring conditions Support to in-network processing / cross-layer opt. Scalability Energy-harvesting awareness

10NGI 2012, Karlskrona, Sweden

Network Layer – available solutions

11NGI 2012, Karlskrona, Sweden

Transport Layer

Similarly to the network layer case, availablesolutions are not suitable for WMSN.

Design guidelines Differentiated reliability Trade-off between reliability/timelinessMedia-centric collaborative reliability Congestion control Cross-layer optimization

12NGI 2012, Karlskrona, Sweden

Transport Layer – available solutions

13NGI 2012, Karlskrona, Sweden

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

14NGI 2012, Karlskrona, Sweden

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 LayerMedia-centric reliability Cross-layer optimization with routing

15NGI 2012, Karlskrona, Sweden

Thank your for your attention!

16NGI 2012, Karlskrona, Sweden

Project Members

M. Cesana, A. Redondi – {cesana, redondi}@elet.polimi.itMultimedia 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.eduMAC Layer

P. Todorova –petia.todorova@fokus.fraunhofer.de

Collaborative Sensing17NGI 2012, Karlskrona, Sweden