A New Approach for Task Scheduling Optimization in Mobile Cloud Computing

  • Pham Phuoc Hung
  • Tuan-Anh Bui
  • Eui-Nam Huh
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 301)


Mobile cloud computing is growing rapidly because its device (i.e., smart phone) is becoming one of the main processing devices for users nowadays. However, there are still some negative impacts that affect cloud access, especially when access to cloud becomes expensive but recent studies are not yet efficient in eliminating these. In this paper, we present an effective task scheduling by collaborating thick–thin clients and cloud to guarantee a better accessibility to cloud network and boost up the processing time in the mobile cloud platform while considering the network bandwidth and cost for cloud service usage. Intensive simulation proves that our method can improve the task scheduling efficiency and is better cost-effective than other works.


Task scheduling Offloading Parallel computing Thin–thick client 



This research was supported by the MSIP (Ministry of Science, ICT&Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (NIPA-2013-H0301-13-4006) supervised by the NIPA (National IT Industry Promotion Agency). The corresponding author is Eui-Nam Huh.


  1. 1.
  2. 2.
  3. 3.
    Vallina-Rodriguez N, Crowcroft J (2012) Energy management techniques in modern mobile handsets. IEEE Commun Surv Tutorials 99:1–20Google Scholar
  4. 4.
    Huang D (2011) Mobile cloud computing. IEEE COMSOC Multimedia Commun Tech Committee (MMTC) E-Lett 6(10):27–31Google Scholar
  5. 5.
    Kumar K, Yung-Hsiang L (2010) Cloud computing for mobile users: can offloading computation save energy. IEEE Comput 43(4):51–56CrossRefGoogle Scholar
  6. 6.
    Huerta-Canepa G, Lee D (2010) A virtual cloud computing provider for mobile devices. In: MCS’10, USAGoogle Scholar
  7. 7.
    Hung PP, Tuan-Anh B (2013) A solution of thin-thick client collaboration for data distribution and resource allocation in cloud computing. In: 2013 International conference on information networking (ICOIN), pp 238–243Google Scholar
  8. 8.
    Wolf J (2008) SODA: an optimizing scheduler for large-scale stream-based distributed computer systems. In: International conference on middleware, pp 306–325Google Scholar
  9. 9.
    Sinnen O, Leonel A (2005) Communication contention in task scheduling. IEEE Trans Parallel Distrib Syst 16(6)Google Scholar
  10. 10.
    Lee Y-C, Zomaya A (2008) A novel state transition method for metaheuristic-based scheduling in heterogeneous computing systems. IEEE Trans Parallel Distrib Syst 19(9):1215–1223CrossRefGoogle Scholar
  11. 11.
    Van den Bossche R (2011) Cost-efficient scheduling heuristics for deadline constrained workloads on hybrid clouds. In: CloudCom, pp 320–327Google Scholar
  12. 12.
    Ghanbari S, Othman M (2012) A priority based job scheduling algorithm in cloud computing. ICASCE 50(2012):778–785Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Computer EngineeringKyung Hee UniversityYongin-siSouth Korea
  2. 2.Louvain School of EngineeringCatholic University of LouvainLouvain-la-NeuveBelgium

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