TY - JOUR
T1 - A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems
AU - Hameed, Abdul
AU - Khoshkbarforoushha, Alireza
AU - Ranjan, Rajiv
AU - Jayaraman, Prem Prakash
AU - Kolodziej, Joanna
AU - Balaji, Pavan
AU - Zeadally, Sherali
AU - Malluhi, Qutaibah Marwan
AU - Tziritas, Nikos
AU - Vishnu, Abhinav
AU - Khan, Samee U.
AU - Zomaya, Albert
N1 - Publisher Copyright:
© 2014, Springer-Verlag Wien.
PY - 2016/7/1
Y1 - 2016/7/1
N2 - In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.
AB - In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.
KW - Cloud computing
KW - Energy consumption
KW - Energy efficiency
KW - Energy efficient resource allocation
KW - Power management
UR - http://www.scopus.com/inward/record.url?scp=84901734176&partnerID=8YFLogxK
U2 - 10.1007/s00607-014-0407-8
DO - 10.1007/s00607-014-0407-8
M3 - Article
SN - 0010-485X
VL - 98
SP - 751
EP - 774
JO - Computing (Vienna/New York)
JF - Computing (Vienna/New York)
IS - 7
ER -