TY - JOUR
T1 - Economic impact of energy saving techniques in cloud server
AU - Ahmad, Bilal
AU - Maroof, Zaib
AU - McClean, Sally
AU - Charles, Darryl
AU - Parr, Gerard
PY - 2020/6/1
Y1 - 2020/6/1
N2 - In recent years, lot of research has been carried in the field of cloud computing and distributed systems to investigate and understand their performance. Economic impact of energy consumption is of major concern for major companies. Cloud Computing companies (Google, Yahoo, Gaikai, ONLIVE, Amazon and eBay) use large data centers which are comprised of virtual computers that are placed globally and require a lot of power cost to maintain. Demand for energy consumption is increasing day by day in IT firms. Therefore, Cloud Computing companies face challenges towards the economic impact in terms of power costs. Energy consumption is dependent upon several factors, e.g., service level agreement, virtual machine selection techniques, optimization policies, workload types etc. We address a solution for the energy saving problem by enabling dynamic voltage and frequency scaling technique for gaming data centers. The dynamic voltage and frequency scaling technique is compared against non-power aware and static threshold detection techniques. This helps service providers to meet the quality of service and quality of experience constraints by meeting service level agreements. The CloudSim platform is used for implementation of the scenario in which game traces are used as a workload for testing the technique. Selection of better techniques can help gaming servers to save energy cost and maintain a better quality of service for users placed globally. The novelty of the work provides an opportunity to investigate which technique behaves better, i.e., dynamic, static or non-power aware. The results demonstrate that less energy is consumed by implementing a dynamic voltage and frequency approach in comparison with static threshold consolidation or non-power aware technique. Therefore, more economical quality of services could be provided to the end users.
AB - In recent years, lot of research has been carried in the field of cloud computing and distributed systems to investigate and understand their performance. Economic impact of energy consumption is of major concern for major companies. Cloud Computing companies (Google, Yahoo, Gaikai, ONLIVE, Amazon and eBay) use large data centers which are comprised of virtual computers that are placed globally and require a lot of power cost to maintain. Demand for energy consumption is increasing day by day in IT firms. Therefore, Cloud Computing companies face challenges towards the economic impact in terms of power costs. Energy consumption is dependent upon several factors, e.g., service level agreement, virtual machine selection techniques, optimization policies, workload types etc. We address a solution for the energy saving problem by enabling dynamic voltage and frequency scaling technique for gaming data centers. The dynamic voltage and frequency scaling technique is compared against non-power aware and static threshold detection techniques. This helps service providers to meet the quality of service and quality of experience constraints by meeting service level agreements. The CloudSim platform is used for implementation of the scenario in which game traces are used as a workload for testing the technique. Selection of better techniques can help gaming servers to save energy cost and maintain a better quality of service for users placed globally. The novelty of the work provides an opportunity to investigate which technique behaves better, i.e., dynamic, static or non-power aware. The results demonstrate that less energy is consumed by implementing a dynamic voltage and frequency approach in comparison with static threshold consolidation or non-power aware technique. Therefore, more economical quality of services could be provided to the end users.
KW - Dynamic frequency scaling
KW - Economic impact
KW - Energy saving technique
KW - Quality of service
KW - Service level agreement
KW - Static threshold and non-power aware technique
UR - http://www.scopus.com/inward/record.url?scp=85067305003&partnerID=8YFLogxK
UR - https://pure.ulster.ac.uk/en/publications/economic-impact-of-energy-saving-techniques-in-cloud-server
U2 - 10.1007/s10586-019-02946-w
DO - 10.1007/s10586-019-02946-w
M3 - Article
AN - SCOPUS:85067305003
VL - 23
SP - 611
EP - 621
JO - Cluster Computing
JF - Cluster Computing
SN - 1386-7857
IS - 2
ER -