Cloud storage hub: Data management for IoT and industry 4.0 applications: Towards a consistent enterprise information management system

Petrasch, Roland; Hentschke, Roman

doi:10.1109/miticon.2016.8025236

Cited by 15 publications

(4 citation statements)

References 13 publications

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“…The authors [14] explore Quality of Service (QOS) in IoT-based wireless networks. A new approach to data management in the space of IoT, cloud services, and Industry 4.0 is proposed in [15]. A new architectural model is discussed in [16] for edge, fog, and cloud IoT platforms.…”

Section: Related Workmentioning

confidence: 99%

Snap IoT: A Decentralized Network Design Model

Reed,

Şaman Tosun,

Korkmaz

2024

IEEE Access

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IoT edge computing is a network design model that captures and processes data at the network edge. The results are forwarded to a cloud service or, if additional processing is needed, a middle tier. By processing data at the edge and middle tier, edge networks achieve better load-balancing and improve performance; however, traditional edge network deployments represent a rigid participation model. Edge networks require physical access to an IoT device and often lock the device to a single edge network. These constraints make it difficult to construct the ideal network, as they reject IoT devices deployed at the network edge but not owned by the network administrator. Our goal is to remove these limitations by creating a network protocol that supports broader participation of IoT devices, cryptographically secures network data, and improves network performance by increasing captured data at the network edge. The protocol is named Snap to symbolize the ease of self assembly. Our experimental research focuses on temperature stability and the cycle efficiency of an HVAC system by utilizing a Snap network to combine two existing edge networks and increase the number of temperature measurement points. The additional measurement points improved the efficiency of the HVAC cycle strategy by increasing the square footage of measured building space. The additional temperature capture points supported an adjustment to the HVAC cycle strategy which resulted in reducing the disparity between the requested temperature and the resulting temperatures. Snap networks support a broader range of IoT sensors leading to increased measurement density, sample rate frequency, and coverage of the network edge.

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Section: Related Workmentioning

confidence: 99%

Snap IoT: A Decentralized Network Design Model

Reed,

Şaman Tosun,

Korkmaz

2024

IEEE Access

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“…In 2016, Petrasch proposed in Reference 12 that the cloud storage center (CSH) should be used to integrate different data sources and provide enterprises with an API for enterprise information management with real-time and consistent data. In 2019, Cui of Renmin University of China studied the application of data management technology in machine learning based on the application scenario of machine learning using data sets for model training 11 .…”

Section: Data Managementmentioning

confidence: 99%

Research on intelligent construction data resource catalogue based on power grid business

Chen

Gao

liu³

et al. 2022

Third International Conference on Computer Science and Communication Technology (ICCSCT 2022)

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With the high-quality development of informatization, power grid enterprises promote the steady development of various businesses by virtue of strong technical barriers. In this paper, it is urgent to carry out research on the construction of intelligent data resource catalogue based on machine learning technology for the sake of consolidating the data application foundation of power grid enterprises, facilitating the potential value of data and optimizing the intelligent level of data services rapidly. Additionally, in this work, we analyze the framework, construction process and key technologies of intelligent data resource catalogue. Ultimately, this work realizes the intelligent construction of data resources in power grid enterprises.

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“…Romero et al [16] the paper provides the future perception on the enterprise information system by providing a short history on the Journal of ISMAC ( 2019 enterprise information system and the various aspects of the engineering involved in the EIS design. Petrarch et al [17] the concept of enterprise data management and enterprise information system has shifted to new epoch by the IOT and cloud by converging different data sources through the mapping and the rule system to provide a real time and consistent data. Fang et al [18] the integrated information system combined with the cloud computing and the IOT is used in the monitoring of the climatic and the environmental changes.…”

Section: Related Workmentioning

confidence: 99%

Virtual Structure for Sustainable Wireless Networks in Cloud Services and Enterprise Information System

Raj¹,

Smys²

2019

JISMAC

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The wireless network virtualization for the cloud and the enterprise information system would enable maximum utilization of resources, causing an enhancement in the enterprise information system efficiency, by sharing the infrastructure among multiple applications or service provisioning’s. The physical wireless structure of the network and the radio resources are split and shared among different applications by abstraction and isolation to provide a cost effective and efficient handling of the enormous amount of the services. Further the virtualization also provides a migration to the latest products and the technologies at ease. In spite of all these potentials there are several challenges that are to be handled before embedding the virtual wireless network over the physical infrastructure. The paper focuses on developing a virtual wireless network that are sustainable(VSWN) for the cloud and enterprise information system involving the software defined networks that includes network function virtualizing and deep packet inspection for improving the agility and the flexibility of the Cloud enterprise information system. The further validation of the proposed model using the network simulator shows throughput enhancements with cost efficiency when compared to the other wireless network management of cloud.

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Cloud storage hub: Data management for IoT and industry 4.0 applications: Towards a consistent enterprise information management system

Cited by 15 publications

References 13 publications

Snap IoT: A Decentralized Network Design Model

Snap IoT: A Decentralized Network Design Model

Research on intelligent construction data resource catalogue based on power grid business

Virtual Structure for Sustainable Wireless Networks in Cloud Services and Enterprise Information System

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