The Study on Capacity Enhancement of Distributed Systems Cloud Services

DOI

10.2991/lemcs-14.2014.174How to use a DOI?

Keywords

fuzzy face; low-quality images; shape features; ASM method

Abstract

With the Number of users in distributed systems clouds rapidly growing every day, increased workload, data and network traffic are seen in the clouds. The SNP (social-net processor) part would become the bottleneck probably as it interacts with social-net providers super frequently. This need to be evaluated pro-actively and coped with before the whole cloud gets crashed due to the huge increased burden. Adding new cloud with additional hardware and equipments is a way but quite costly. As a more practical approach, optimizing existing system to lift the capacity will be extremely beneficial. This involves improving parts of system infrastructure and workflow, fully utilizing cloud resources and balancing the cooperation among components such as SNP, Core Service, DB, Memcache etc. problem identification, performance or capacity modeling, solution design and implementation, and change impact assessment are the main work-streams.This paper will detail the useful principles and proven practices applied to the optimization.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xueping Liu
PY  - 2014/05
DA  - 2014/05
TI  - The Study on Capacity Enhancement of Distributed Systems Cloud Services
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 763
EP  - 766
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.174
DO  - 10.2991/lemcs-14.2014.174
ID  - Liu2014/05
ER  -