Middleware: a model for distributed system services
Communications of the ACM
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
The many faces of publish/subscribe
ACM Computing Surveys (CSUR)
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Body sensor networks: can we use them?
M-PAC '09 Proceedings of the International Workshop on Middleware for Pervasive Mobile and Embedded Computing
To hop or not to hop: network architecture for body sensor networks
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
MobiSense: Mobile body sensor network for ambulatory monitoring
ACM Transactions on Embedded Computing Systems (TECS)
Semantic streams: a framework for composable semantic interpretation of sensor data
EWSN'06 Proceedings of the Third European conference on Wireless Sensor Networks
AMON: a wearable multiparameter medical monitoring and alert system
IEEE Transactions on Information Technology in Biomedicine
Middleware to support sensor network applications
IEEE Network: The Magazine of Global Internetworking
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Body Sensor Networks (BSNs) are the natural candidates to provide multi-parameter patient monitoring. Tapping into multiple inputs and correlating them to infer new information, cleaning received data and inferring state should be objectives of BSNs. These systems will need to deduce information from a variety of raw sensor data and accuracy in their results will be paramount. Apart from having several different types of sensors (producing different types of data), BSNs will also have several applications wanting to access information. Not all of the information will be directly sensed, but some can be inferred from the raw sensor data. We propose a framework that enables modularization of information and its correlation. This enables re-use by different applications and optimization of the collection and calculation of the requested information by the system (the BSN). The framework also allows defining dependencies between modules for information production. Our architecture provides an abstraction on the way information is assessed and its processing flow. Applications issue requests to the middleware with requirements to be met. So we will discuss the optimization of resources, while honouring requirements.