e-space
Manchester Metropolitan University's Research Repository

A genetic algorithm enhanced automatic data flow management solution for facilitating data intensive applications in the cloud

Li, SL and Huang, Z and Han, Liangxiu and Jiang, C (2018) A genetic algorithm enhanced automatic data flow management solution for facilitating data intensive applications in the cloud. Concurrency and Computation: Practice and Experience. ISSN 1532-0626

[img]
Preview

Download (1MB) | Preview

Abstract

The past few years have witnessed a rapid deployment of computing infrastructures in the cloud in support of data intensive applications. The effort of the existing works is mainly focused on data reusing mechanisms without considering data processing routes, which can significantly affect the computation costs when exchanging data among the computing node in the cloud. This paper presents a genetic algorithm enhanced Automatic Data Flow Management Solution (ADFMS) that facilitates automatic routing function and a self‐adjustable intermediate data management mechanism to achieve an efficient data processing structure of cloud computing. Experimental results show that ADFMS optimizes costs in managing intermediate data in the cloud.

Impact and Reach

Statistics

Downloads
Activity Overview
14Downloads
80Hits

Additional statistics for this dataset are available via IRStats2.

Altmetric

Actions (login required)

Edit Item Edit Item