Planning the loading of data centers' resources based on download statistics
DOI:
https://doi.org/10.20535/RADAP.2016.65.62-72Keywords:
telecommunication system, tariffing of services, quality of services, hybrid cloud, cloud computing, data centers, utility computing, virtualization, market-oriented resource allocationAbstract
The customer service quality depends on the procedure of the application maintenance in data center of the communication provider. In the article the control approach of dynamic resource involvement has been suggested in order to ensure the input flow maintenance that takes into account the random nature of applications’ inflow and utilizes both short-term and long-term load statistics. The proposed approach consists of two methods that manage the number of the implicated serving nodes. The first one verifies the resource amount adequacy, provides the evaluation of input load’s dynamics based on the short-term statistics as well as the current state of the technical facilities. The second one accounts for the long-term statistics according to which the implication of additional resources can be scheduled during the load peaks. The simulation results of technical resources management have been presented for the data center infrastructure of the communication provider, that prove the effectiveness of the proposed methods.References
Ruben Van den Bossche, Kurt Vanmechelen and Jan Broeckhove (2010) Cost-Optimal Scheduling in Hybrid IaaS Clouds for Deadline Constrained Workload. IEEE 3rd International Conference on Cloud Computing, pp. 228-235.
Javadi B., Abawajy J. and Buyya R. (2012) Failure-aware resource provisioning for hybrid Cloud infrastructure. Journal Parallel Distrib. Comput., No 72, pp. 1318–1331.
Vecchiola Ch., Calheiros R. N., Karunamoorthy D. and Buyya R. (2012) Deadline-driven provisioning of resources for scientific applications in hybrid clouds with Aneka. Future Generation Computer Systems, No 28, pp. 58–65.
Ardagna D. and Ciavotta M. (2014) Long-term Auto-Scaling Algorithm for Multi-Cloud IaaS Systems. Politecnico di Milano, Technical Report, No 13.
Kumar Das A., Adhikary T., Razzaque Md. A., Cho E. J. and Hong Ch. S. (2014) A QoS and Profit Aware Cloud Confederation Model for IaaS Service Providers. IMCOM(ICUIMC)’14. Siem Reap, Cambodia, pp. 9-11.
Buyya R., Ranjan R. and Calheiros R. N. (2010) InterCloud: Utility-oriented federation of Cloud computing environments for scaling of application services. 10th Int’l Conf. on Algorithms and Architectures for Parallel Processing (ICA3PP), pp 13-31.
den Bossche R. V., Vanmechelen K. and Broeckhove J. (2010) Cost-optimal scheduling in Hybrid IaaS Clouds for deadline constrained workloads. IEEE Int’l Conf. on Cloud Computing, pp. 228-235.
Hyunjoo Kim, Yaakoub el-Khamra, Shantenu Jha and Manish Parashar (2010) Exploring application and infrastructure adaptation on hybrid Grid-Cloud infrastructure. Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, pp. 402-412.
Marcos Dias de Assunção, Alexandre di Costanzo and Rajkumar Buyya (2010) A cost-benefit analysis of using cloud computing to extend the capacity of clusters. Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, Vol. 13., No 3, pp. 335-347.
Goiri I., Guitart J. and Torres J. (2010) Characterizing Cloud Federation for Enhancing Providers' Profit. 2010 IEEE 3rd International Conference on Cloud Computing. pp. 123-130.
Lee Y., Wang C., Taheri J., Zomaya A. and Zhou B. (2010) On the effect of using third-party Clouds for maximizing profit. Algorithms and Architectures for Parallel Processing, Springer Berlin Heidelberg, Vol. 6081, pp. 381-390.
Hamilton J. Cost of power in large-scale data centers. Available at: http://perspectives.mvdirona.com/.
Barroso L. A. and Hölzle U. (2007) The case for energy-proportional computing. Computer, vol. 40, No 12, pp. 33–37.
Zhernovyi K. Y. and Zhernovyi Y. V. (2012) An M θ/G/1/m system with two-threshold hysteresis strategy of service intensity switching. Journal of Communications Technology and Electronics,Vol. 57, No 12, pp. 1340-1349.
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