Please use this identifier to cite or link to this item: http://localhost:80/handle/Hannan/482776
Title: A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks
Authors: Halil Yetgin;Kent Tsz Kan Cheung;Mohammed El-Hajjar;Lajos Hanzo Hanzo
Year: 2017
Publisher: IEEE
Abstract: Emerging technologies, such as the Internet of Things, smart applications, smart grids, and machine-to-machine networks stimulate the deployment of autonomous, self-configuring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints, and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteria.
URI: http://dl.kums.ac.ir/handle/Hannan/482776
volume: 19
issue: 2
More Information: 828,
854
Appears in Collections:2017

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Title: A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks
Authors: Halil Yetgin;Kent Tsz Kan Cheung;Mohammed El-Hajjar;Lajos Hanzo Hanzo
Year: 2017
Publisher: IEEE
Abstract: Emerging technologies, such as the Internet of Things, smart applications, smart grids, and machine-to-machine networks stimulate the deployment of autonomous, self-configuring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints, and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteria.
URI: http://dl.kums.ac.ir/handle/Hannan/482776
volume: 19
issue: 2
More Information: 828,
854
Appears in Collections:2017

Files in This Item:
File Description SizeFormat 
7812629.pdf5.18 MBAdobe PDFThumbnail
Preview File
Title: A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks
Authors: Halil Yetgin;Kent Tsz Kan Cheung;Mohammed El-Hajjar;Lajos Hanzo Hanzo
Year: 2017
Publisher: IEEE
Abstract: Emerging technologies, such as the Internet of Things, smart applications, smart grids, and machine-to-machine networks stimulate the deployment of autonomous, self-configuring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints, and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteria.
URI: http://dl.kums.ac.ir/handle/Hannan/482776
volume: 19
issue: 2
More Information: 828,
854
Appears in Collections:2017

Files in This Item:
File Description SizeFormat 
7812629.pdf5.18 MBAdobe PDFThumbnail
Preview File