A Framework for Partitioning and Execution of Data Stream Applications in Mobile Cloud Computing

  Priyanka Singh,  Ashish Tiwari,  Sanjay Singh

The advances in technologies of cloud computing and mobile computing enable the newly emerging mobile cloud computing paradigm. Three approaches have been proposed for mobile cloud applications: 1) extending the access to cloud services to mobile devices; 2) enabling mobile devices to work collaboratively as cloud resource providers; 3) augmenting the execution of mobile applications on portable devices using cloud resources. In this paper, we focus on the third approach in supporting mobile data stream applications. More specifically, we study the computation partitioning, which aims at optimizing the partition of a data stream application between mobile and cloud such that the application has maximum speed/throughput in processing the streaming data. To the best of our knowledge, it is the first work to study the partitioning problem for mobile data stream applications, where the optimization is placed on achieving high throughput of processing the streaming data rather than minimizing the make span of executions in other applications. We first propose a framework to provide runtime support for the dynamic partitioning and execution of the application.

Keywords- mobile cloud computing; application partitioning; genetic algorithm;

Unique Identification Number - IJEDR1604115
Page Number(s) - 751-764
Pubished in - Volume 4 | Issue 4 | December 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Priyanka Singh,  Ashish Tiwari,  Sanjay Singh,   "A Framework for Partitioning and Execution of Data Stream Applications in Mobile Cloud Computing", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 4, pp.751-764, December 2016, Available at :http://www.ijedr.org/papers/IJEDR1604115.pdf