Cloud Computing Placement Optimization Under Ubiquitous Power Internet of Things Background

Zhang, Ziyi; Guo, Chao; Sun, Yan; Hu, Kaiqiang; Wang, Qinghai; Wu, Yuzhao; Cai, Zexiang

doi:10.1109/smartcloud.2019.00012

Cited by 4 publications

(2 citation statements)

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“…The emergence of the UPIoT has brought about numerous new difficulties. Despite being used in the UPIoT, present cloud computing cannot yet address the issues we list below [36]: Low latency requirements, network capacity restrictions, device resource limitations, and continuous connection to and communication with the cloud center, privacy protection, and data security are all factors that must be taken into consideration. Three crucial IoT technologies sensor, connectivity, In order to get beyond these obstacles and see UPIoT expand, and edge computing are essential components of its overall architecture.…”

Section: H Ubiquitous Power Internet Of Things (Upiot)mentioning

confidence: 99%

“…Under certain conditions, this mode may fulfill the need for users and equipment connected to smart grids to deliver prompt replies. The internal architecture of the edge computing gateway is shown in [36]. Its software architecture is composed of a number of containers in addition to the host operating system.…”

Section: H Ubiquitous Power Internet Of Things (Upiot)mentioning

confidence: 99%

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Deep Learning for Edge Computing Applications: A Comprehensive Survey

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et al. 2022

AJCST

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Edge computing is a modern computer architecture that processes data quickly and efficiently close to its point of origin, hence avoiding slowdowns caused by network latency and capacity limitations. By moving processing power to the network’s perimeter, edge computing decreases the load on central data centers and reduces the time it takes for users to submit data. Therefore, access latency may become a barrier, potentially negating the benefits of edge computing, particularly for applications that need a great deal of data.. Edge computing has some challenges, such as security, incomplete data, investment costs, and maintenance costs. In this research, we undertake a thorough analysis of edge computing, how edge device placement improves performance in IoT networks, compare various edge computing implementations, and explain various difficulties encountered during edge computing implementation. This study aims to promote creative edge-based Internet of Things security design by thoroughly examining existing Internet of Things security solutions at the edge layer and facilitate the dynamic deployment of edge devices.

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Section: H Ubiquitous Power Internet Of Things (Upiot)mentioning

confidence: 99%

Section: H Ubiquitous Power Internet Of Things (Upiot)mentioning

confidence: 99%