An introduction to analog and digital communications
An introduction to analog and digital communications
A framework for evaluating design tradeoffs in packet processing architectures
Proceedings of the 39th annual Design Automation Conference
Middleware challenges for wireless sensor networks
ACM SIGMOBILE Mobile Computing and Communications Review
On Quality of Service Optimization with Discrete QoS Options
RTAS '99 Proceedings of the Fifth IEEE Real-Time Technology and Applications Symposium
An Energy-Aware QoS Routing Protocol for Wireless Sensor Networks
ICDCSW '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
SPEED: A Stateless Protocol for Real-Time Communication in Sensor Networks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Versatile low power media access for wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Multi-objective design space exploration of embedded systems
Journal of Embedded Computing - Low-power Embedded Systems
A calculator for Pareto points
Proceedings of the conference on Design, automation and test in Europe
Analysing qos trade-offs in wireless sensor networks
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Fundamenta Informaticae - The Fourth Special Issue on Applications of Concurrency to System Design (ACSD05)
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Issues in designing middleware for wireless sensor networks
IEEE Network: The Magazine of Global Internetworking
QoS Management for Wireless Sensor Networks with a Mobile Sink
EWSN '09 Proceedings of the 6th European Conference on Wireless Sensor Networks
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Quality of Service (QoS) support for wireless sensor networks (WSN) is a fairly new topic that is gaining more and more interest. This paper introduces a method for determining the node configurations of a WSN such that application-level QoS constraints are met. This is a complex task, since the search space is typically extremely large. The method is based on a recent algebraic approach to Pareto analysis, that we use to reason about QoS trade-offs. It features an algorithm that keeps the working set of possible configurations small, by analysing parts of the network in a modular fashion, and meanwhile discarding configurations that are inferior to other configurations. Furthermore, we give WSN models for two different applications, spatial mapping and target tracking, in which QoS trade-offs are made explicit. Test results for these applications and a heterogeneous WSN combining these two applications show that the models are accurate and that the method is scalable and thus practically usable for WSN, even with large numbers of nodes. Details are given on how to efficiently implement the algorithm.