Title :
Service optimization in cloud using family gene technology
Author :
Ananth, Alaka ; Chandra Sekaran, K.
Author_Institution :
Dept. of Comput. Sci. & Eng., Nat. Inst. of Technol. Karnataka, Surathkal, India
Abstract :
Cloud computing is the upcoming technology in current day scenario. It has emerged as a solution for providing resources to the consumers in the form of software, infrastructure or platform as a service. Cloud Service Storage enables users to synchronize their files across devices and also allows them to backup online. The main aim of this paper is to provide service optimization. Scheduling of services is a NP hard problem. Thus exhaustive approaches are not suitable for these kinds of algorithms. This paper presents a genetic algorithm based approach for optimization of services by using family gene technology. Family gene technology is used to classify individuals to different families based on gene parameters and evaluate the fitness function for each individual in that family. Optimization is achieved by mapping the service requests to appropriate service instances which satisfy the request and then by applying family gene based genetic algorithm to those mapped service requests.
Keywords :
cloud computing; genetic algorithms; scheduling; storage management; NP hard problem; cloud service storage; family gene technology; genetic algorithm based approach; infrastructure as a service; platform as a service; service optimization; service request mapping; service scheduling; software as a service; Biological cells; Genetic algorithms; Optimization; Quality of service; Scheduling; Sociology; Statistics; Cloud Computing; Family gene; Genetic Algorithm; Service Optimization;
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4799-3078-4
DOI :
10.1109/ICACCI.2014.6968491