Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs Applications

Wireless sensor networks (WSNs) have been widely adopted in many domains like military and environment monitoring.In general, sensors in WSNs aim to sense and collect various types of information from environments. Sensors usually can be divided into two types as static or mobile sensors, where mobi...

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Main Authors: Yaqiang Zhang, Zhangbing Zhou, Deng Zhao, Mahmoud Barhamgi, Taj Rahman
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7857024/
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spelling doaj-d1bfe8054a804c05bf795b593432bf672021-03-29T20:00:19ZengIEEEIEEE Access2169-35362017-01-0151559156910.1109/ACCESS.2017.26676877857024Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs ApplicationsYaqiang Zhang0https://orcid.org/0000-0001-9935-0606Zhangbing Zhou1Deng Zhao2Mahmoud Barhamgi3Taj Rahman4School of Information Engineering, China University of Geosciences, Beijing, ChinaSchool of Information Engineering, China University of Geosciences, Beijing, ChinaSchool of Information Engineering, China University of Geosciences, Beijing, ChinaClaude Bernard University of Lyon1, Villeurbanne, FranceSchool of Computer Science and Communication Engineering, University of Science and Technology Beijing, Beijing, ChinaWireless sensor networks (WSNs) have been widely adopted in many domains like military and environment monitoring.In general, sensors in WSNs aim to sense and collect various types of information from environments. Sensors usually can be divided into two types as static or mobile sensors, where mobile sensors can move to collect the information from static sensors. How to make the best use of sensor's energy and prolong network lifetime is a challenge, which has attracted the attention of researchers in recent years. In this paper, we schedule mobile sensors by applying techniques derived from ant colony optimization and genetic algorithm in order to balance the energy consumption of mobile sensors. The network where static sensors are deployed are divided into relatively small regions, then we use our technique to allocate these regions to each mobile sensor, while ensuring that energy consumption of each mobile sensor is close to each other. Experimental evaluation shows that our technique can effectively balance the load of each mobile sensor and thus prolong the networks lifetime.https://ieeexplore.ieee.org/document/7857024/Wireless sensor networksmobile sensorsenergy-balancedheuristic algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Yaqiang Zhang
Zhangbing Zhou
Deng Zhao
Mahmoud Barhamgi
Taj Rahman
spellingShingle Yaqiang Zhang
Zhangbing Zhou
Deng Zhao
Mahmoud Barhamgi
Taj Rahman
Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs Applications
IEEE Access
Wireless sensor networks
mobile sensors
energy-balanced
heuristic algorithm
author_facet Yaqiang Zhang
Zhangbing Zhou
Deng Zhao
Mahmoud Barhamgi
Taj Rahman
author_sort Yaqiang Zhang
title Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs Applications
title_short Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs Applications
title_full Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs Applications
title_fullStr Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs Applications
title_full_unstemmed Graph-Based Mechanism for Scheduling Mobile Sensors in Time-Sensitive WSNs Applications
title_sort graph-based mechanism for scheduling mobile sensors in time-sensitive wsns applications
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2017-01-01
description Wireless sensor networks (WSNs) have been widely adopted in many domains like military and environment monitoring.In general, sensors in WSNs aim to sense and collect various types of information from environments. Sensors usually can be divided into two types as static or mobile sensors, where mobile sensors can move to collect the information from static sensors. How to make the best use of sensor's energy and prolong network lifetime is a challenge, which has attracted the attention of researchers in recent years. In this paper, we schedule mobile sensors by applying techniques derived from ant colony optimization and genetic algorithm in order to balance the energy consumption of mobile sensors. The network where static sensors are deployed are divided into relatively small regions, then we use our technique to allocate these regions to each mobile sensor, while ensuring that energy consumption of each mobile sensor is close to each other. Experimental evaluation shows that our technique can effectively balance the load of each mobile sensor and thus prolong the networks lifetime.
topic Wireless sensor networks
mobile sensors
energy-balanced
heuristic algorithm
url https://ieeexplore.ieee.org/document/7857024/
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