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Cluster Computing
Published in: Cluster Computing 2/2015

01-06-2015

Securely and efficiently perform large matrix rank decomposition computation via cloud computing

Authors: Xinyu Lei, Xiaofeng Liao, Xiaoxi Ma, Liping Feng

Published in: Cluster Computing | Issue 2/2015

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Abstract

Cloud computing enables resource-constrained clients to economically outsource their huge computation workloads to a powerful cloud server. This promising computing paradigm is able to realize client-cloud cooperative computations. It also brings in new security concerns and challenges, such as input/output privacy and efficiency. Since large matrix rank decomposition computation (RDC) is ubiquitous in the fields of science and engineering, a first step is taken forward to design a protocol that enables clients to securely and efficiently outsource RDC to a public cloud in this paper. It is analytically shown that the proposed protocol is correct and secure. Extensive theoretical analysis and experimental evaluation also show its high-efficiency and immediate practicability. It is hoped that the proposed protocol can shed light on designing other novel secure outsourcing protocols, and inspire powerful companies and working groups to finish the programming of the demanded all-inclusive scientific computations outsourcing software system. It is believed that such software system can be profitable by means of providing large-scale scientific computation services for so many potential clients. The proposed RDC outsourcing protocol is a step forward to realize such integrated software system.
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Metadata
Title
Securely and efficiently perform large matrix rank decomposition computation via cloud computing
Authors
Xinyu Lei
Xiaofeng Liao
Xiaoxi Ma
Liping Feng
Publication date
01-06-2015
Publisher
Springer US
Published in
Cluster Computing / Issue 2/2015
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-015-0444-x

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