Cost reduction for data allocation in heterogenous cloud computing using dynamic programming

Hui Zhao, Meikang Qiu*, Keke Gai, Jie Li, Xin He

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Heterogeneous clouds are helpful for improving performance when the data processing task becomes a challenge in big data within different operating environment. Non-distributive manner has some limitation, such as overload energy and low performance resource allocation mechanism. This paper address on this issue and propose an approach to find out the optimal data allocation plan for minimizing total costs of the distributed heterogeneous cloud memories in mobile cloud systems. In this paper, we propose a novel approach to find out the optimal data allocation plan to reduce data processing cost through heterogeneous cloud memories for efficient MaaS. The experimental results proved that our approach is an effective mechanism.

Original languageEnglish
Title of host publicationSmart Computing and Communication - 1st International Conference, SmartCom 2016, Proceedings
EditorsMeikang Qiu
PublisherSpringer Verlag
Pages1-11
Number of pages11
ISBN (Print)9783319520148
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event1st International Conference on Smart Computing and Communication, SmartCom 2016 - Shenzhen, China
Duration: 17 Dec 201619 Dec 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10135 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Smart Computing and Communication, SmartCom 2016
Country/TerritoryChina
CityShenzhen
Period17/12/1619/12/16

Keywords

  • Cost reduction
  • Data allocation
  • Dynamic programming
  • Heterogenous cloud computing

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