Name
Abstract | ||
|---|---|---|
Cloud computing provides virtualized, dynamically-scalable computing power. At the same time, reduction of cost is also considered as an important advantage of cloud computing. Data integration can notably benefit from cloud computing because integrating data is usually an expensive task. However, existing optimization techniques pay less attention on the fact that different execution plans of the same data integration application generate different usage costs while cloud computing provides good enough performance, so this paper introduces the cost optimization of cloud-based data integration system. The data integration system's data service layer facilitates accessing and composing information from a range of enterprise data sources through data service composition. In addition, two task scheduling algorithms for parallel part and non-parallel part are proposed to minimize the usage cost required to complete the execution of composite data service when computational capability provided by cloud computing is charged. Both of the two can obtain optimal plans in polynomial time. Experiments with the system indicate that our algorithms can lead to significant cost saving over more straightforward techniques. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/WISA.2012.13 | WISA |
Keywords | Field | DocType |
optimisation,task scheduling algorithms,virtualized dynamically-scalable computing power,information access,data service,enterprise data sources,scheduling,data service composition,data service composition layer,cloud computing-based data integration system,cost saving,dynamically-scalable computing power,organisational aspects,cloud-based data integration system,virtualisation,data service layer,enterprise data source,composite data service,data integration system,information composition,cost optimization,cloud computing,parallel part,nonparallel part,data integration,data integration application,computational capability,cost reduction,usage cost minimization,optimization,approximation algorithms,computer architecture,scheduling algorithms | Virtualization,Data integration,Computer science,Scheduling (computing),Utility computing,Data virtualization,Enterprise data management,Data as a service,Cloud computing,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4673-3054-1 | 4 | 0.38 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Zhang | 1 | 172 | 19.52 |
| Yanbo Han | 2 | 500 | 59.74 |
| Zhuofeng Zhao | 3 | 66 | 15.46 |
| Guiling Wang | 4 | 832 | 52.06 |