An Intelligent Approach to Resource Allocation on Heterogeneous Cloud Infrastructures

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{marquez:2021:AS,

• author = "Jack Marquez and Oscar H. Mondragon and Juan D. Gonzalez",
• title = "An Intelligent Approach to Resource Allocation on Heterogeneous Cloud Infrastructures",
• journal = "Applied Sciences",
• year = "2021",
• volume = "11",
• number = "21",
• keywords = "genetic algorithms, genetic programming, cloud computing, resource allocation",
• ISSN = "2076-3417",
• URL = "https://www.mdpi.com/2076-3417/11/21/9940",
• DOI = "doi:10.3390/app11219940",
• abstract = "Cloud computing systems are rapidly evolving toward multicloud architectures supported on heterogeneous hardware. Cloud service providers are widely offering different types of storage infrastructures and multi-NUMA architecture servers. Existing cloud resource allocation solutions do not comprehensively consider this heterogeneous infrastructure. In this study, we present a novel approach comprised of a hierarchical framework based on genetic programming to solve problems related to data placement and virtual machine allocation for analytics applications running on heterogeneous hardware with a variety of storage types and nonuniform memory access. Our approach optimises data placement using the Hadoop File System on heterogeneous storage devices on multicloud systems. It guarantees the efficient allocation of virtual machines on physical machines with multiple NUMA (nonuniform memory access) domains by minimizing contention between workloads. We prove that our solutions for data placement and virtual machine allocation outperform other state-of-the-art approaches.",
• notes = "also known as \cite{app11219940}",

}

Genetic Programming entries for Jack Marquez Oscar Hernan Mondragon Martinez Juan D Gonzalez

Citations