QoS Prediction for the Cloud Service Marketplace: A Grassmann Manifold Approach

Yao Zhao, Zongpeng Li, Xiaowen CHU

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

The emerging cloud computing technologies enable a cloud platform to provide diverse cloud services to its service subscribers. By federating different services within and across cloud boundaries, cloud service developers can provision new, composite cloud services in the marketplace of apps and services on a cloud platform. Complete and accurate service QoS information is important for service recommendation and service pricing. However, measuring the entire QoS matrix for all user-service pairs incurs a tremendous overhead and is practically infeasible. This work designs efficient algorithms for recovering the complete QoS matrix from partial measurements, exploiting the low rank feature of the matrix. Our solution applies tools from differential geometry for transforming rank-constrained matrix optimization in a flat space into an unconstrained geometric optimization in a smooth manifold. Besides QoS matrix completion, future QoS matrix prediction based on manifold algorithms is also studied in this work, for the first time in the literature.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015
EditorsCalton Pu, Ajay Mohindra
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages221-228
Number of pages8
ISBN (Electronic)9781467372879
DOIs
Publication statusPublished - 19 Aug 2015
Event8th IEEE International Conference on Cloud Computing, CLOUD 2015 - New York, United States
Duration: 27 Jun 20152 Jul 2015

Publication series

NameProceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015

Conference

Conference8th IEEE International Conference on Cloud Computing, CLOUD 2015
Country/TerritoryUnited States
CityNew York
Period27/06/152/07/15

Scopus Subject Areas

  • Computer Networks and Communications

User-Defined Keywords

  • Cloud Services
  • Grassmann Manifold
  • Prediction
  • QoS

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