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Information Superbahn: Towards a Planet-Scale, Low-Entropy and High-Goodput Computing Utility.

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Title: Information Superbahn: Towards a Planet-Scale, Low-Entropy and High-Goodput Computing Utility.
Authors: Xu, Zhi-Wei1,2 (AUTHOR), Li, Zhen-Ying1,2 (AUTHOR) lizhenying20b@ict.ac.cn, Yu, Zi-Shu1,2 (AUTHOR), Li, Feng-Zhi1,2 (AUTHOR)
Source: Journal of Computer Science & Technology (10009000). Feb2023, Vol. 38 Issue 1, p103-114. 12p.
Subjects: On-demand computing, Grid computing, Cloud computing
Abstract: In a 1961 lecture to celebrate MIT's centennial, John McCarthy proposed the vision of utility computing, including three key concepts of pay-per-use service, large computer and private computer. Six decades have passed, but Mc- Carthy's computing utility vision has not yet been fully realized, despite advances in grid computing, services computing and cloud computing. This paper presents a perspective of computing utility called Information Superbahn, building on recent advances in cloud computing. This Information Superbahn perspective retains McCarthy's vision as much as possible, while making essential modern requirements more explicit, in the new context of a networked world of billions of users, trillions of devices, and zettabytes of data. Computing utility offers pay-per-use computing services through a 1) planet-scale, 2) low-entropy and 3) high-goodput utility. The three salient characteristics of computing utility are elaborated. Initial evidence is provided to support this viewpoint. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computer Science & Technology (10009000) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: <searchLink fieldCode="DE" term="%22On-demand+computing%22">On-demand computing</searchLink><br /><searchLink fieldCode="DE" term="%22Grid+computing%22">Grid computing</searchLink><br /><searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink>
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  Data: In a 1961 lecture to celebrate MIT's centennial, John McCarthy proposed the vision of utility computing, including three key concepts of pay-per-use service, large computer and private computer. Six decades have passed, but Mc- Carthy's computing utility vision has not yet been fully realized, despite advances in grid computing, services computing and cloud computing. This paper presents a perspective of computing utility called Information Superbahn, building on recent advances in cloud computing. This Information Superbahn perspective retains McCarthy's vision as much as possible, while making essential modern requirements more explicit, in the new context of a networked world of billions of users, trillions of devices, and zettabytes of data. Computing utility offers pay-per-use computing services through a 1) planet-scale, 2) low-entropy and 3) high-goodput utility. The three salient characteristics of computing utility are elaborated. Initial evidence is provided to support this viewpoint. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Computer Science & Technology (10009000) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Feb2023
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