Downloads: 102 | Views: 139
M.Tech / M.E / PhD Thesis | Software Engineering | Malaysia | Volume 3 Issue 11, November 2014
A Hybrid Algorithm Using Genetic Algorithm - Hadoop MapReduce Optimization for Energy Efficiency in Cloud Computing Platform
Izain Nurfateha Ruzan | Suriayati Chuprat | Pegah Razmara
Abstract: Cloud computing is an emerging model for distributed utility computing. It has become commercially attractive and continues to grow as it promises minimum maintenance and costs in comparison with traditional data centers. Clouds are normally composed by large and power-consuming data centers as it was designed to support the elasticity and scalability required by its customers. However, while cloud computing reduces the energy consumption at the customer site, it become an issue for the providers who have to deal with increasing demand and performance expectations. The study of this research paper is to formulate a hybrid algorithm using genetic algorithm and Hadoop MapReduce framework to further promotes the energy efficiency in cloud computing platform.
Keywords: Cloud computing, energy efficient, genetic algorithm, mapreduce
Edition: Volume 3 Issue 11, November 2014,
Pages: 1630 - 1641