An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks

The Compressive Data Collection (CDC) scheme is an efficient data-acquiring method that uses compressive sensing to decrease the bulk of data transmitted. Most existing schemes are modeled as Non-Uniform Sparse Random Projection (NSRP), and an NSRP-based estimator is used. These models cannot deal w...

Полное описание

Сохранить в:

Библиографические подробности
Главные авторы:	Lapina, M. A., Лапина, М. А.
Формат:	Статья
Язык:	English
Опубликовано:	Springer Science and Business Media Deutschland GmbH 2024
Темы:	Compressive data collection Wireless sensor network Maximum likelihood estimator Margin-free estimator Gaussian regression Covariance function
Online-ссылка:	https://dspace.ncfu.ru/handle/123456789/29357
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!

id	ir-123456789-29357
record_format	dspace
spelling	ir-123456789-293572024-12-11T08:45:24Z An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks Lapina, M. A. Лапина, М. А. Compressive data collection Wireless sensor network Maximum likelihood estimator Margin-free estimator Gaussian regression Covariance function The Compressive Data Collection (CDC) scheme is an efficient data-acquiring method that uses compressive sensing to decrease the bulk of data transmitted. Most existing schemes are modeled as Non-Uniform Sparse Random Projection (NSRP), and an NSRP-based estimator is used. These models cannot deal with anomaly readings that deviate from their standards and norms. Therefore, we provide a new CDC strategy in this study that uses an opportunistic estimator and routing. Initially, neighbor nodes are identified using the covariance function following the Gaussian process regression, and the data transfer to the neighbor node is done using the compressive sensing technique. Compressed data are then projected by using conventional random projection. Finally, the sample required to retrieve data is estimated using margin-free and maximum likelihood estimators. Results show that the sample needed to retrieve the data is less in the proposed scheme. 2024-12-11T08:44:40Z 2024-12-11T08:44:40Z 2024 Статья Mary Anita, E.A., Jenefa, J., Vinodha, D., Lapina, M. An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks // Lecture Notes in Networks and Systems. - 2024. - 1207 LNNS. - pp. 31-47. - DOI: 10.1007/978-3-031-77229-0_5 https://dspace.ncfu.ru/handle/123456789/29357 en Lecture Notes in Networks and Systems application/pdf Springer Science and Business Media Deutschland GmbH
institution	СКФУ
collection	Репозиторий
language	English
topic	Compressive data collection Wireless sensor network Maximum likelihood estimator Margin-free estimator Gaussian regression Covariance function
spellingShingle	Compressive data collection Wireless sensor network Maximum likelihood estimator Margin-free estimator Gaussian regression Covariance function Lapina, M. A. Лапина, М. А. An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks
description	The Compressive Data Collection (CDC) scheme is an efficient data-acquiring method that uses compressive sensing to decrease the bulk of data transmitted. Most existing schemes are modeled as Non-Uniform Sparse Random Projection (NSRP), and an NSRP-based estimator is used. These models cannot deal with anomaly readings that deviate from their standards and norms. Therefore, we provide a new CDC strategy in this study that uses an opportunistic estimator and routing. Initially, neighbor nodes are identified using the covariance function following the Gaussian process regression, and the data transfer to the neighbor node is done using the compressive sensing technique. Compressed data are then projected by using conventional random projection. Finally, the sample required to retrieve data is estimated using margin-free and maximum likelihood estimators. Results show that the sample needed to retrieve the data is less in the proposed scheme.
format	Статья
author	Lapina, M. A. Лапина, М. А.
author_facet	Lapina, M. A. Лапина, М. А.
author_sort	Lapina, M. A.
title	An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks
title_short	An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks
title_full	An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks
title_fullStr	An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks
title_full_unstemmed	An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks
title_sort	efficient compressive data collection scheme for wireless sensor networks
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2024
url	https://dspace.ncfu.ru/handle/123456789/29357
work_keys_str_mv	AT lapinama anefficientcompressivedatacollectionschemeforwirelesssensornetworks AT lapinama anefficientcompressivedatacollectionschemeforwirelesssensornetworks AT lapinama efficientcompressivedatacollectionschemeforwirelesssensornetworks AT lapinama efficientcompressivedatacollectionschemeforwirelesssensornetworks
_version_	1842245527447535616

An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks

Схожие документы