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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Main Authors: Jinghua Zhu, Xuming Yin, Jingsi Bai, Yake Wang
Format: Article
Language:English
Published: SAGE Publishing 2016-08-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147716664235
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spelling 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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