Boosting Edge Computing Performance Through Heterogeneous Manycore Systems

Ramneek,; Cha, Seung-Jun; Jeon, Seung Hyub; Jeong, Yeon Jin; Kim, Jin Mee; Jung, Souhwan; Pack, Sangheon

doi:10.1109/ictc.2018.8539604

Cited by 6 publications

(5 citation statements)

References 5 publications

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“…The concept of virtual reality began to be used as a theoretical approach in the field of HCI (Hyper Converged Infrastructure) in the mid-1970s, but it began to be actively used in the 1980s. Various studies and attempts have been made in the field of virtual reality [14,15]. In addition, as related contents increase, various distributions are being made in connection with culture, art, sports, and tourism.…”

Section: Attributes Of Vr Tourism and Pcp Modelmentioning

confidence: 99%

A Study on the Causal Process of Virtual Reality Tourism and Its Attributes in Terms of Their Effects on Subjective Well-Being during COVID-19

Song

Guo

2021

IJERPH

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In the landscape of Covid-19 pandemic, people’s well-being, to some extent, can be affected through virtual reality tourism because it has the opportunity to enhance their level of well-being and destination recovery. To verify this empirically an investigation was conducted among people who used Quanjingke, the largest tourism-related virtual reality website in China, during the pandemic. The specific the aim of this paper is to prove the effectiveness of virtual reality tourism in promoting people’s subjective well-being. Hence, an integrated model with the constructs of peripheral attribute, core attribute and pivotal attribute, presence, perceived value, satisfaction, and subjective well-being was proposed and tested. The results indicate that attributes of virtual reality tourism have a positive effect on presence during virtual reality experiences, which positively influences perceived value. The values of virtual reality tourism perceived by tourists result in their satisfaction. Eventually, it was found that tourists’ subjective well-being is improved due to their satisfaction with virtual reality tourism. Practical suggestions are also provided based on the findings.

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Section: Attributes Of Vr Tourism and Pcp Modelmentioning

confidence: 99%

A Study on the Causal Process of Virtual Reality Tourism and Its Attributes in Terms of Their Effects on Subjective Well-Being during COVID-19

Song

Guo

2021

IJERPH

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“…The former presents some similarities with the Cloud environment, resources are still organized in data-centers, leveraging virtualization technologies to increase application density. However, resources present heterogeneity in both computing [7] and networking [8] to cope with the geographical distribution of such small data-centers. Examples of near-edge infrastructure are given by metropolitan deployments comprising cabinets, central offices, and small data-centers.…”

Section: Differences Between Cloud and Edge Infrastructurementioning

confidence: 99%

Managing the Far-Edge: Are Today's Centralized Solutions a Good Fit?

Baldoni¹,

Cominardi²,

Groshev

et al. 2023

IEEE Consumer Electron. Mag.

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Edge computing has established itself as the foundation for next-generation mobile networks, IT infrastructure, and industrial systems thanks to promised low network latency, computation offloading, and data locality. These properties empower key use-cases like Industry 4.0, Vehicular Communication and Internet of Things. Nowadays implementation of Edge computing is based on extensions to available Cloud computing software tools. While this approach accelerates adoption, it hinders the deployment of the aforementioned use-cases that requires an infrastructure largely more decentralized than Cloud data centers, notably in the far-Edge of the network. In this context, this work aims at: (i) analyzing the differences between Cloud and Edge infrastructures, (ii) analyzing the architecture adopted by the most prominent open-source Edge computing solutions, and (iii) evaluating those solutions in terms of scalability and service instantiation time in a medium-size far Edge system. Results show that mainstream Edge solutions require powerful centralized controllers and always-on connectivity, making them unsuitable for highly decentralized scenarios in the far-Edge where stable and high-bandwidth links are not ubiquitous.

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“…With that in mind, this vibrant research area has been more and more focusing on integrating edge computing with deep learning [1] and the associated challenges due to resource constraints [2], [3]. Recent hardware developments are making more and more possible to run highly computationally demanding algorithms in the edge [4].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Deep Neural Network (DNN) Placement and Inference in Edge Computing

Bensalem¹,

Dizdarević²,

Jukan³

2020

Preprint

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With the edge computing becoming an increasingly adopted concept in system architectures, it is expected its utilization will be additionally heightened when combined with deep learning (DL) techniques. The idea behind integrating demanding processing algorithms in Internet of Things (IoT) and edge devices, such as Deep Neural Network (DNN), has in large measure benefited from the development of edge computing hardware, as well as from adapting the algorithms for use in resource constrained IoT devices. Surprisingly, there are no models yet to optimally place and use machine learning in edge computing. In this paper, we propose the first model of optimal placement of Deep Neural Network (DNN) Placement and Inference in edge computing. We present a mathematical formulation to the DNN Model Variant Selection and Placement (MVSP) problem considering the inference latency of different model-variants, communication latency between nodes, and utilization cost of edge computing nodes. We evaluate our model numerically, and show that for low load increasing model colocation decreases the average latency by 33% of millisecondscale per request, and for high load, by 21%.

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Boosting Edge Computing Performance Through Heterogeneous Manycore Systems

Cited by 6 publications

References 5 publications

A Study on the Causal Process of Virtual Reality Tourism and Its Attributes in Terms of Their Effects on Subjective Well-Being during COVID-19

A Study on the Causal Process of Virtual Reality Tourism and Its Attributes in Terms of Their Effects on Subjective Well-Being during COVID-19

Managing the Far-Edge: Are Today's Centralized Solutions a Good Fit?

Modeling of Deep Neural Network (DNN) Placement and Inference in Edge Computing

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