Dynamic Clustering Based Optimization Technique and Quality Assessment Model of Mobile Cloud Computing

KIPS Transactions on Software and Data Engineering, Vol. 2, No.6, pp.383-394, June 2013
10.3745/KTSDE.2013.2.6.383, Full Text

Abstract

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile could computing(MCC), where mobile devices utilize remote resources of could services or PCs, have been proposed. Typically, in MCC, many nodes with different operating systems and platform and diverse mobile applications or services are located, and a central manager autonomously performs several management tasks to maintain a consistent level of MCC overall quality. However, as there are a larger number of nodes, mobile applications, and services subscribed by the mobile applications and their interactions are extremely increased, a traditional management method of MCC reveals a fundamental problem of degrading its overall performance due to overloaded management tasks to the central manager, i.e. a bottle neck phenomenon. Therefore, in this paper, we propose a clustering-based optimization method to solve performance-related problems on large-scaled MCC and to stabilize its overall quality. With our proposed method, we can ensure to minimize the management overloads and stabilize the quality of MCC in an active and autonomous way.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from October 15, 2016)

Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


Cite this paper

[KIPS Transactions Style]
S. D. Kim, D. Y. Kim, and H. J. La, "Dynamic Clustering Based Optimization Technique and Quality Assessment Model of Mobile Cloud Computing," KIPS Transactions on Software and Data Engineering, Vol.2, No.6, pp.383-394, 2013, DOI: 10.3745/KTSDE.2013.2.6.383.

[IEEE Style]
Soo Dong Kim, Dae Young Kim, and Hyun Jung La, "Dynamic Clustering Based Optimization Technique and Quality Assessment Model of Mobile Cloud Computing," KIPS Transactions on Software and Data Engineering, vol. 2, no. 6, pp. 383-394, 2013. DOI: 10.3745/KTSDE.2013.2.6.383.

[ACM Style]
Kim, S. D., Kim, D. Y., and La, H. J. 2013. Dynamic Clustering Based Optimization Technique and Quality Assessment Model of Mobile Cloud Computing. KIPS Transactions on Software and Data Engineering, 2, 6, (2013), 383-394. DOI: 10.3745/KTSDE.2013.2.6.383.