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Physical Sciences and Mathematics Commons

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Databases and Information Systems

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Research Collection School Of Computing and Information Systems

2020

Cloud computing

Articles 1 - 3 of 3

Full-Text Articles in Physical Sciences and Mathematics

A 2020 Perspective On "Client Risk Informedness In Brokered Cloud Services: An Experimental Pricing Study", Di Shang, Robert J. Kauffman May 2020

A 2020 Perspective On "Client Risk Informedness In Brokered Cloud Services: An Experimental Pricing Study", Di Shang, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Cloud computing and the cloud services market have advanced in the past ten years. Cloud services now include most information technology (IT) services from fundamental computing services to more cutting- edge artificial intelligence (AI) services. Accordingly, opportunities have emerged for research on the design of new market features to improve the cloud services market to benefit providers and users. Based on our observation of the recent development of cloud services, in this short research commentary, we share our agenda for future studies of this important sector of IT services.


Privacy-Preserving Data Processing With Flexible Access Control, Wenxiu Ding, Zheng Yan, Robert H. Deng Mar 2020

Privacy-Preserving Data Processing With Flexible Access Control, Wenxiu Ding, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud computing provides an efficient and convenient platform for cloud users to store, process and control their data. Cloud overcomes the bottlenecks of resource-constrained user devices and greatly releases their storage and computing burdens. However, due to the lack of full trust in cloud service providers, the cloud users generally prefer to outsource their sensitive data in an encrypted form, which, however, seriously complicates data processing, analysis, as well as access control. Homomorphic encryption (HE) as a single key system cannot flexibly control data sharing and access after encrypted data processing. How to realize various computations over encrypted data in …


Scalable, Adaptable And Fast Estimation Of Transient Downtime In Virtual Infrastructures Using Convex Decomposition And Sample Path Randomization, Zhiling Guo, Jin Li, Ram Ramesh Jan 2020

Scalable, Adaptable And Fast Estimation Of Transient Downtime In Virtual Infrastructures Using Convex Decomposition And Sample Path Randomization, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

Network function virtualization enables efficient cloud-resource planning by virtualizing network services and applications into software running on commodity servers. A cloud-service provider needs to manage and ensure service availability of a network of concurrent virtualized network functions (VNFs). The downtime distribution of a network of VNFs can be estimated using sample-path randomization on the underlying birth–death process. An integrated modeling approach for this purpose is limited by its scalability and computational load because of the high dimensionality of the integrated birth–death process. We propose a generalized convex decomposition of the integrated birth-death process, which transforms the high-dimensional multi-VNF process into …