A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing

Li, Xiaomin; Wan, Jiafu; Dai, Hong-Ning; Imran, Muhammad; Xia, Min; Celesti, Antonio

doi:10.1109/tii.2019.2899679

Cited by 180 publications

(66 citation statements)

References 33 publications

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“…Content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2020.3001277, IEEE Access IEEE Access formance of the manufacturing system can be significantly improved [169]. On another view, to achieve higher goodput, [160] enabled the MEC platform to improve the caching management for IIoT system.…”

Section: ) Industrial Internetmentioning

confidence: 99%

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

et al. 2020

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Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.

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Section: ) Industrial Internetmentioning

confidence: 99%

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

et al. 2020

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“…On top of virtual machines, we further utilize Hadoop distributed computing platforms to support big data processing tasks. In order to coordinate the edge and cloud computing tasks, we design and implement a hybrid edge/cloud computing framework (details can be referred to the work [77]). Figure 5(b) gives the realistic prototype of a printed circuit board (PCB) production line based on our proposed system framework.…”

Section: Case Studiesmentioning

confidence: 99%

Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies

Dai

Wang

et al. 2019

Enterprise Information Systems

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235

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“…In [56], an intelligent resource scheduling strategy is proposed with an underlying hybrid computing framework. The computing system consists four layers for supporting artificial intelligent tasks: device computing layer, edge computing layer, cloud computing layer, and SDN layer.…”

Section: Extended Reality (Xr) and Industry 40 Applicationsmentioning

confidence: 99%

5G support for Industrial IoT Applications— Challenges, Solutions, and Research gaps

Varga

Pető

Frankó

et al. 2020

Sensors

186

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Industrial IoT has special communication requirements, including high reliability, low latency, flexibility, and security. These are instinctively provided by the 5G mobile technology, making it a successful candidate for supporting Industrial IoT (IIoT) scenarios. The aim of this paper is to identify current research challenges and solutions in relation to 5G-enabled Industrial IoT, based on the initial requirements and promises of both domains. The methodology of the paper follows the steps of surveying state-of-the art, comparing results to identify further challenges, and drawing conclusions as lessons learned for each research domain. These areas include IIoT applications and their requirements; mobile edge cloud; back-end performance tuning; network function virtualization; and security, blockchains for IIoT, Artificial Intelligence support for 5G, and private campus networks. Beside surveying the current challenges and solutions, the paper aims to provide meaningful comparisons for each of these areas (in relation to 5G-enabled IIoT) to draw conclusions on current research gaps.

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A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing

Cited by 180 publications

References 33 publications

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies

5G support for Industrial IoT Applications— Challenges, Solutions, and Research gaps

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