Mobility-assisted big data collecting in wireless sensor networks
In recent years, the big data emerged as a hot topic because of the rapid growth of the information and wireless communication technology. One of the significant sources of the big data is wireless sensor networks. Due to the power limitation of sensor nodes, energy-efficient big data collecting is...
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/1550147716664235 |
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doaj-9df391474fbf4725a540ab68a9ecdc352020-11-25T03:34:12ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772016-08-011210.1177/1550147716664235Mobility-assisted big data collecting in wireless sensor networksJinghua Zhu0Xuming Yin1Jingsi Bai2Yake Wang3Key Laboratory of Database and Parallel Computing of Heilongjiang Province, Harbin, ChinaKey Laboratory of Database and Parallel Computing of Heilongjiang Province, Harbin, ChinaKey Laboratory of Database and Parallel Computing of Heilongjiang Province, Harbin, ChinaKey Laboratory of Database and Parallel Computing of Heilongjiang Province, Harbin, ChinaIn recent years, the big data emerged as a hot topic because of the rapid growth of the information and wireless communication technology. One of the significant sources of the big data is wireless sensor networks. Due to the power limitation of sensor nodes, energy-efficient big data collecting is a challenging task in wireless sensor networks. Being considered as an effective solution to address this challenge is to utilize sink’s mobility to assist data collecting. Although this method can reduce the volume of data transfer between sensor nodes and thus save energy consumption of nodes, the low speed of mobile sink hinders its use in data-intensive sensing applications with time constraint. In this article, we propose a four-phase mobility-assisted data collecting protocol consisting of network clustering, routes planning, routes combination, and data collecting. Two heuristic routes planning algorithms are presented to build a set of trajectories which satisfy the deadline constraint and have the minimum overall movement cost. Numeric results show that our approaches have better performance in terms of energy saving, latency, and movement cost.https://doi.org/10.1177/1550147716664235 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jinghua Zhu Xuming Yin Jingsi Bai Yake Wang |
spellingShingle |
Jinghua Zhu Xuming Yin Jingsi Bai Yake Wang Mobility-assisted big data collecting in wireless sensor networks International Journal of Distributed Sensor Networks |
author_facet |
Jinghua Zhu Xuming Yin Jingsi Bai Yake Wang |
author_sort |
Jinghua Zhu |
title |
Mobility-assisted big data collecting in wireless sensor networks |
title_short |
Mobility-assisted big data collecting in wireless sensor networks |
title_full |
Mobility-assisted big data collecting in wireless sensor networks |
title_fullStr |
Mobility-assisted big data collecting in wireless sensor networks |
title_full_unstemmed |
Mobility-assisted big data collecting in wireless sensor networks |
title_sort |
mobility-assisted big data collecting in wireless sensor networks |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2016-08-01 |
description |
In recent years, the big data emerged as a hot topic because of the rapid growth of the information and wireless communication technology. One of the significant sources of the big data is wireless sensor networks. Due to the power limitation of sensor nodes, energy-efficient big data collecting is a challenging task in wireless sensor networks. Being considered as an effective solution to address this challenge is to utilize sink’s mobility to assist data collecting. Although this method can reduce the volume of data transfer between sensor nodes and thus save energy consumption of nodes, the low speed of mobile sink hinders its use in data-intensive sensing applications with time constraint. In this article, we propose a four-phase mobility-assisted data collecting protocol consisting of network clustering, routes planning, routes combination, and data collecting. Two heuristic routes planning algorithms are presented to build a set of trajectories which satisfy the deadline constraint and have the minimum overall movement cost. Numeric results show that our approaches have better performance in terms of energy saving, latency, and movement cost. |
url |
https://doi.org/10.1177/1550147716664235 |
work_keys_str_mv |
AT jinghuazhu mobilityassistedbigdatacollectinginwirelesssensornetworks AT xumingyin mobilityassistedbigdatacollectinginwirelesssensornetworks AT jingsibai mobilityassistedbigdatacollectinginwirelesssensornetworks AT yakewang mobilityassistedbigdatacollectinginwirelesssensornetworks |
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1724560000763822080 |