Title :
A penalty-based genetic algorithm for the composite SaaS placement problem in the Cloud
Author :
Yusoh, Zeratul Izzah Mohd ; Tang, Maolin
Author_Institution :
Fac. of Inf., Commun. & Technol., Univ. Teknikal Malaysia Melaka, Malaysia
Abstract :
Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications´ placement methods in data centres are not concerned with the placement of the component´s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider´s servers. Experimental results demonstrate the feasibility and the scalability of the GA.
Keywords :
Internet; genetic algorithms; Internet; Software as a Service; cloud computing; composite SaaS placement problem; data centres; data components; penalty-based genetic algorithm; Biological cells; Clouds; Computational modeling; Equations; Mathematical model; Servers; Software;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586151