A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data Center

作     者：Nidhika Chauhan Navneet Kaur Kamaljit Singh Saini Sahil Verma Abdulatif Alabdulatif Ruba Abu Khurma Maribel Garcia-Arenas Pedro A.Castillo 

作者机构：University Institute of ComputingChandigarh UniversityPunjab143001India Department of Computer Science and EngineeringChandigarh UniversityPunjab143001India Department of Computer Science and EngineeringUttaranchal UniversityUttarakhand248007India Department of Computer ScienceCollege of Computer Qassim UniversityBuraydah52571Saudi Arabia MEU Research UnitFaculty of Information TechnologyMiddle East UniversityAmman11831Jordan Department of Computer EngineeringAutomatics and RoboticsUniversity of GranadaGranada18071Spain Applied Science Research CenterApplied Science Private UniversityAmman11931Jordan 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2024年第48卷第3期

页      面：571-608页

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Ministerio Espanol de Ciencia e Innovación under Project Number PID2020-115570GB-C22,MCIN/AEI/10.13039/501100011033 by the Cátedra de Empresa Tecnología para las Personas(UGR-Fujitsu) 

主　　题：Cloud computing data centre task allocation performance management resource utilization 

摘      要：As cloud computing usage grows,cloud data centers play an increasingly important *** maximize resource utilization,ensure service quality,and enhance system performance,it is crucial to allocate tasks and manage performance *** purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data *** aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies,categories,and gaps.A literature review was conducted,which included the analysis of 463 task allocations and 480 performance management *** review revealed three task allocation research topics and seven performance management *** allocation research areas are resource allocation,load-Balancing,and *** management includes monitoring and control,power and energy management,resource utilization optimization,quality of service management,fault management,virtual machine management,and network *** study proposes new techniques to enhance cloud computing work allocation and performance ***-comings in each approach can guide future *** research’s findings on cloud data center task allocation and performance management can assist academics,practitioners,and cloud service providers in optimizing their systems for dependability,cost-effectiveness,and *** methodologies can steer future research to fill gaps in the literature.