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Mobile Multi-Media Wireless Sensor Networks(M3WSN)

Abstract

Wireless sensor network technology is becoming more and more mature and sensors are being used in many applications in the area of security (e.g., for monitoring buildings and private areas), environmental monitoring (e.g., river monitoring in the Alps) and e-health (e.g., heart rate monitoring of patients). Sensor networks include both discrete sensor data (e.g., temperature, passive infrared levels, and sound levels) and continuous multi-media flows (e.g., continuous audio and video flows).

Moreover, in future wireless sensor network scenarios, the issue of mobility becomes more important. First, objects to be monitored (cars, persons, animals) are naturally mobile. Second, these objects might carry sensors (in particular they might be integrated into mobile personal devices such as smart phones) such that sensors might become mobile. Third, the objects or special mobile devices such as robots or unmanned aerial vehicles might carry base stations that are responsible for receiving multi-media sensor information from the sensor nodes in order to provide them to processing elements, e.g., in a cloud computing environment, for further processing.

Since there is often a huge amount of sensor data to be processed, cloud computing infrastructures are a promising candidate to achieve scalable storage and processing of sensor information. Only by sufficient (cloud) computing resources, it might be possible to achieve hard real-time requirements. The wired part of the Internet will be the network interconnecting both cloud computing infrastructure and wireless sensor networks.Sensor network research should be supported by realistic experiments performed in wireless sensor network testbeds. This should support repetition of experiments in order to achieve statistical significance, and to allow researchers to verify results. However, mobility of objects, sensors, and base stations is difficult to set up and repeat in a testbed. Therefore, we propose to use real testbeds for experiments but emulate mobility of personal devices, sensors, and base stations.

This project proposes to build an experimental research platform including both communication in wireless sensor networks and processing sensor data in cloud computing environments. The research platform will be based on existing solutions developed and used in previous projects. Mainly adaptation and integration work is needed to achieve the result of an integrated research platform covering both wireless sensor networks and cloud computing infrastructures.

This project will be performed in the context of Nano-Tera & SSSTC joint project..

Project Details

Title: Mobile Multi-Media Wireless Sensor Networks
People: Zhongliang Zhao, Prof. Dr. Torsten Braun
Duration: 10.2011 - 10.2012
state:Completed
Funding: Nano-Tera.ch & SSSTC
Index Terms: mobile multimedia network, wireles sensor network, high performance computing, cloud computing, opportunistic routing protocols
Publication:

Zhongliang Zhao, Gerald Wagenknecht, Torsten Braun, Bjoern Mosler:
Mobile Multi-Media Wireless Sensor Networks ,
Poster from Nano-Tera.ch 2012 Annual Plenary Meeting , Zurich , April 26 - 27, 2012

Zhongliang Zhao, Torsten Braun, Denis do Rosario,Eduardo Cerqueira,Roger Immich,Marilia Curado,:
QoE-aware FEC Mechanism for Intrusion Detection in Multi-tier Wireless Multimedia Sensor Networks ,
1st International Workshop on Wireless Multimedia Sensor Networks (WMSN) 2012(collocated with WiMob 2012) , Barcelona, Spain, October 8 - 10, 2012
Description: Here you can find the zip files of the M3WSN framework. To be able to access the framework, requesters need a password to download the source code. The password can be required by sending email to Zhongliang Zhao (zhao@iam.unibe.ch) or Denis Lima Rosario (denis@ufpa.br).
Downloads: ZIP file of M3WSN framework
Description: Here you can find a set of transmitted videos via LinGO, BLR, and MRR for the paper submitted to IEEE Sensors Journal Special Issue on Internet of Things: Architecture, Protocols and Services.
Downloads: ZIP file of video sequences.
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