Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
A wireless sensor network For structural monitoring
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
A Programmable Service Architecture for Mobile Medical Care
PERCOMW '06 Proceedings of the 4th annual IEEE international conference on Pervasive Computing and Communications Workshops
Telos: enabling ultra-low power wireless research
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Health monitoring of civil infrastructures using wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th symposium on Operating systems design and implementation
Design of large-scale agricultural wireless sensor networks: email from the vineyard
International Journal of Sensor Networks
Parallel processing of data from very large-scale wireless sensor networks
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
IEEE Communications Magazine
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The potentially widespread adoption of Wireless Sensor Networks presents a unique challenge both for the communication infrastructure of the Internet as well as for backend systems responsible for processing the data and making it available in useful form. In this paper we explore this space by making careful estimates on the traffic volumes of sensing data in a number of scenarios explored in the literature. Examples of the scenarios covered are patient monitoring, structural monitoring, vehicular applications and environmental monitoring. The results show that if there were a "flag day" for sensor network deployments in the near future they would as a whole dominate over other forms of mobile and wireless network traffic at least until the middle of the next decade. However, the overall data volumes would still appear to be manageable, although only barely. Based on these forecasts, we comment on the feasibility of processing data from large sensor deployments. We also present first results from our ongoing work towards developing a highly scalable framework for storing and processing data obtained from planet-scale WSN deployments. In particular, we study how MapReduce-based data processing could be used to deal with the scalability challenge, and argue using selected case studies that platforms such as Hadoop could indeed be used to deal with such data volumes.