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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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/ |
work_keys_str_mv |
AT yaqiangzhang graphbasedmechanismforschedulingmobilesensorsintimesensitivewsnsapplications AT zhangbingzhou graphbasedmechanismforschedulingmobilesensorsintimesensitivewsnsapplications AT dengzhao graphbasedmechanismforschedulingmobilesensorsintimesensitivewsnsapplications AT mahmoudbarhamgi graphbasedmechanismforschedulingmobilesensorsintimesensitivewsnsapplications AT tajrahman graphbasedmechanismforschedulingmobilesensorsintimesensitivewsnsapplications |
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1724195561977937920 |