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Distributed spatiotemporal suppression for environmental data collection in real-world sensor networks

Related publications (50)

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A Parallel Evolutionary Algorithm to Optimize Dynamic Data Types in Embedded Systems

David Atienza Alonso, José Luis Risco Martin

New multimedia embedded applications are increasingly dynamic, and rely on dynamically-allocated data types (DDTs) to store their data. The optimization of DDTs for each target embedded system is a time-consuming process due to the large searching space of ...

2008

Graphical display for annual climate-based daylight simulation

Marilyne Andersen, Magali Bodart

Due to daylight variability, a design cannot be thoroughly assessed using single-moment simulations, which is why we need dynamic performance metrics like Daylight Autonomy and Useful Daylight Illuminance. Going one step further, the annual variation in pe ...

2008

A distributed minimum-distortion routing algorithm with in-network data processing

Ramin Khalili

In many wired and wireless networks, nodes process input traffic to satisfy a network constraint (e.g., a capacity constraint) and to increase the utility of data in the output flows given these constraints. In this paper we focus on the special case in wh ...

2008

Survey Propagation Inspired Algorithms for Satisfiability

Nicolas Macris, Shrinivas Kudekar

In this note we develop generalized Survey Propagation (SP) equations from the cavity method. We quantize the message space of the messages to develop a message passing rule. We investigate a framework of greedy algorithms for finding out satisfying assign ...

2008

Experiences with Reproducible Research in Various Facets of Signal Processing Research

Martin Vetterli, Andrea Ridolfi, Guillermo Barrenetxea Kobas, Ivana Jovanovic, Patrick Vandewalle

How often have you been able to implement an algorithm as it is described in a paper? And when you did, were you confident that you had exactly the same parameter values and results as the authors of the paper? All too often, articles do not describe all t ...

2007

Adaptive processing over distributed networks

Ali H. Sayed

The article describes recent adaptive estimation algorithms over distributed networks. The algorithms rely on local collaborations and exploit the space-time structure of the data. Each node is allowed to communicate with its neighbors in order to exploit ...

The Institute of Electronics, Information and Communication Engineers2007

Optimal maneuvering of seismic sensors for localization of subsurface targets

Volkan Cevher

We consider the problem of detecting and locating buried land mines and subsurface objects by using a maneuvering array that receives scattered seismic surface waves. We demonstrate an adaptive system that moves an array of receivers according to an optima ...

Institute of Electrical and Electronics Engineers2007

Adaptive estimation algorithms over distributed networks

Ali H. Sayed

We provide an overview of adaptive estimation algorithms over distributed networks. The algorithms rely on local collaborations and exploit the space-time structure of the data. Each node is allowed to communicate with its neighbors in order to exploit th ...

2006

Global mixed-integer dynamic optimization

Benoît Chachuat

Recent advances in process synthesis, design, operations, and control have created an increasing demand for efficient numerical algorithms for optimizing a dynamic system coupled with discrete decisions; these problems are termed mixed-integer dynamic opti ...

2005

Tree-Based Pursuit

Pascal Frossard, Pierre Vandergheynst, Philippe Jost

Building good sparse approximations of functions is one of the major themes in approximation theory. When applied to signals, images or any kind of data, it allows to deal with basic building blocks that essentially synthesize all the information at hand. ...

2004