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Optimizing Parameters of Prioritized Data Reduction in Sensor Networks

Authors:
Cosmin Dini
Pascal Lorenz

Keywords: sensor, data management, data sensor storage, data priority optimized parameters, prediction models

Abstract:
Wireless Sensor Networks are popular and proven useful in various service areas. Energy optimization, processing optimization and storage optimization are the main challenges. While there is a debate for complete or partial data extraction from sensors, having special data process functions and operation primitives proves useful for sensor operating systems. To deal with robustness and reliability, data processing at the network/sensor level satisfies some of the reliability requirements, especially when communications are not operational. There are situations where data reduction is an alternative when storage is no longer available and data is accumulating, especially when some sensor links are not operational. Using predictions and optimized parameters to prioritize data reduction is a solution. In this article, we define special heuristics for data reduction using a set of data processing primitives and special data parameters. We apply these heuristics via a methodology that enables various factors, both internal and external to the sensor, to influence the data aging process and the data reduction operations.

Pages: 346 to 350

Copyright: Copyright (c) IARIA, 2010

Publication date: October 25, 2010

Published in: conference

ISSN: 2308-4278

ISBN: 978-1-61208-100-7

Location: Florence, Italy

Dates: from October 25, 2010 to October 30, 2010