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dc.contributor.authorLin, Chun-Chengen_US
dc.contributor.authorDeng, Der-Jiunnen_US
dc.contributor.authorChen, Zheng-Yuen_US
dc.contributor.authorChen, Kwang-Chengen_US
dc.date.accessioned2017-04-21T06:55:51Z-
dc.date.available2017-04-21T06:55:51Z-
dc.date.issued2016-10en_US
dc.identifier.issn0163-6804en_US
dc.identifier.urihttp://hdl.handle.net/11536/132888-
dc.description.abstractIn the Industry 4.0 framework based on IoT and smart manufacturing, it is essential to support factory automation and flexibility in harsh or dynamic industrial environments. State-of-the-art technology suggests building a controlled work-space using large-scale deployment of wireless sensors. To overcome the technological challenges in scalability and heterogeneity for large-scale industrial deployment, group-based industrial wireless sensor networks (GIWSNs) are suggested, in which wireless sensors are divided into multiple groups for multiple monitoring tasks, and each group of sensors is deployed densely within a subarea in a large plant or along a long production/assembly line, while connectivity between groups is required. As wireless sensors are equipped with batteries with limited power, it has been challenging to plan sleep schedules of sensors, which are influenced significantly by deployment of such a large-scale GIWSN. However, most previous works on wireless sensor networks independently investigated deployment and sleep scheduling problems, both of which have been shown to be NP-hard. Therefore, this work jointly considers deployment and sleep scheduling of sensors in a GIWSN along a production line. Via the theory of symmetries, we alleviate the computational concerns from multiple groups to one group and another medium-size group. Then we propose a hybrid harmony search and genetic algorithm, which incorporates deployment and sleep schedules to reduce energy consumption. Simulations verify this joint methodology to effectively achieve energy efficiency.en_US
dc.language.isoen_USen_US
dc.titleKey Design of Driving Industry 4.0: Joint Energy-Efficient Deployment and Scheduling in Group-Based Industrial Wireless Sensor Networksen_US
dc.identifier.journalIEEE COMMUNICATIONS MAGAZINEen_US
dc.citation.volume54en_US
dc.citation.issue10en_US
dc.citation.spage46en_US
dc.citation.epage52en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000388423000007en_US
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