CBPM: a dynamic pricing model for cloud-based sensing infrastructure

CBPM: a dynamic pricing model for cloud-based sensing infrastructure

Автор: Rane Dheeraj, Shakhov Vladimir, Srivastava Abhishek

Журнал: Проблемы информатики @problem-info

Рубрика: Прикладные информационные технологии

Статья в выпуске: 1 (38), 2018 года.

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Wireless sensor networks with cloud computing arc drivers to a new stream of technologies like the Internet of Things and innovations in the communications. Cloud computing triumphs with multifaceted benefits to enterprises with cost saving economies, reduced operational, and support costs but higher productivity. The significant functionality of data collected and processed at wireless sensor nodes is rendered fast, uninterrupted and reliably with cloud computing and its optimized implementations. Therefore, sensor network firms arc partnering with cloud service providers, which lease computing infrastructure as required. This paper suggests a model for optimizing the computing potential of the wireless sensor network in conjunction with the pricing model of the cloud. Integration of concepts of cloud and sensor networks takes the advantage of the sealable and dynamic aspect of cloud being exploited for sensory data. The results show that the proposed method adapts well with performance expectations of sensor networks and reduces the cost specific overheads for its largely processing based functioning...

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Cloud computing, dynamic pricing, pricing band, pricing analysis, cloud broker pricing model

Короткий адрес: https://sciup.org/143167044

IDR: 143167044

Список литературы CBPM: a dynamic pricing model for cloud-based sensing infrastructure

  • Botts, Mike and Percivall, George and Reed, Carl and Davidson, John. OGCA Sensor Web Enablement: Overview and High Level Architecture//GeoSensor Networks: Second International Conference, GSN 2006, Boston, MA, USA, October 1 3. 2006, Revised Selected and Invited Papers. Springer Berlin Heidelberg, 2008. P. 175-190.
  • Mell, Peter and Grance, Tim. The NIST definition of cloud computing//Computer Security Division, Information Technology Laboratory, National Institute of Standards and Technology Gaithersburg. 2011.
  • Fox, Armando and Griffith, Rean and Joseph, Anthony and Katz, Randy and Konwinski, Andrew and Lee, Gunho and Patterson, David and Rabkin, Ariel and Stoica, Ion. Above the clouds: A Berkeley view of cloud computing. Dept. Electrical Engineering and Computer Sciences, University of California, Berkeley, Rep. UCB/EECS. 2009. V. 28. N 13.
  • Intacct Corporation. Moving to the Cloud: Understanding the Total Cost of Ownership. 2011.
  • Buyya, Rajkumar and Ranjan, Rajiv and Calheiros, Rodrigo N. Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities//International Conference on High Performance Computing k, Simulation, 2009. HPCS'09. IEEE. P. 1-11.
  • Gartner : http://www.gartner.com/it-glossary/cloud-services-brokerage-csb/.
  • Supply on demand: Adapting to change in consumption and delivery models//The Economist. 2013. : https://www.eiuperspectives.economist. com/sites/default/files/EIU_Zuora_WEB_Final.pdf.
  • Al-Roomi, May and Al-Ebrahim, Shaikha and Buqrais, Sabika and Ahmad, Imtiaz. Cloud computing pricing models: A survey//International Journal of Grid k, Distributed Computing. Citeseer, 2013. V. 6. N 5. P. 93-106.
  • Gabriel Bitran and Rene Caldentey. An Overview of Pricing Models for Revenue Management//Manufacturing and Service Operations Management. 2003. V. 5. N 3. P. 203-229.
  • Amazon EC2 spot request volatility. : https://moz.com/devblog/amazon-ec2-spot-request-volatility-hits-1000hour/.
  • M. yousif. A Plethora of Challenges and Opportunities//IEEE Cloud Computing. 2014. V. 1. N 2. P. 7 12.
  • Sharma, Bhanu and Thulasiram, Ruppa K. and Thulasiraman, Parimala and Garg, Saurabh K. and Buyya, Rajkumar. Pricing Cloud Compute Commodities: A Novel Financial Economic Model//Proc. of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2012). IEEE Computer Society, 2012. P. 451-457.
  • Agmon Ben-Yehuda, Orna and Ben-Yehuda, Muli and Schuster, Assaf and Tsafrir, Dan. Deconstructing Amazon EC2 spot instance pricing//ACM Transactions on Economics and Computation. ACM, 2013. V. 1. P. 16.
  • BUYYA, rajkumar and abramson, david and GlDDY, jonathan and stockinger, Heinz. Economic models for resource management and scheduling in Grid computing//Concurrency and Computation: Practice and Experience. 2002. V. 14. P. 1507-1542.
  • Abramson, David and Buyya, Rajkumar and Giddy, Jonathan. A Computational Economy for Grid Computing and Its Implementation in the Nimrod-G Resource Broker. Future Generation Computer Systems. Elsevier Science Publishers В. V. 2002. V. 18. P. 1061-1074
  • Gunther Stuer and Kurt Vanmechelen and Jan Broeckhove. A commodity market algorithm for pricing substitutable Grid resources//Future Generation Computer Systems. 2007. V. 23. 688-701.
  • Caracas, Alexandru and Altmann, jorn. A Pricing Information Service for Grid Computing//Proc. of the 5th International Workshop on Middleware for Grid Computing: Held at the ACM/IFIP/USENIX 8th International Middleware Conference. ACM, 2007. P. 4:1-4:6.
  • Chee Shin Yeo and Srikumar Venugopal and Xingchen Chu and Rajkumar Buyya. Autonomic metered pricing for a utility computing service//Future Generation Computer Systems. 2010. V. 26. N 8. P. 1368-1380.
  • Roovers, Joris and Vanmechelen, Kurt and Broeckhove, Jan. A Reverse Auction Market for Cloud Resources//Proceedings of the 8th International Conference on Economics of Grids, Clouds, Systems, and Services. Springer-Verlag, 2012.
  • Barkha Javed and Peter Bloodsworth and Raihan Ur Rasool and Kamran Munir and Omer Rana. Cloud Market Maker: An automated dynamic pricing marketplace for cloud users//Future Generation Computer Systems. 2016.V. 54. P. 52-67.
  • Y. M. Teo and M. MlHAlLESCU. A Strategy-proof Pricing Scheme for Multiple Resource Type Allocations//International Conference on Parallel Processing, 2009. ICPP '09. 2009. 172-179.
  • M. MlHAlLESCU and Y. M. Teo. Dynamic Resource Pricing on Federated Clouds//10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid). 2010. 513-517.
  • Karunakaran, Sowmya and Krishnaswamy, Venkataraghavan and Sundarraj, R. P. Service Research and Innovation: Third Australian Symposium, ASSRI 2013, Sydney, NSW, Australia, November 27-29, 2013, Revised Selected Papers//Decisions, Models and Opportunities in Cloud Computing Economics: A Review of Research on Pricing and Markets. Springer International Publishing, 2014. P. 85-99.
  • Li, Chu Fen. Cloud Computing System Management Under Flat Rate Pricing//Journal of Network and Systems Management. 2011. V. 19. N 3. P. 305-318.
  • macias, Mario and Guitart, Jordi. A Genetic Model for Pricing in Cloud Computing Markets//Proceedings of the 2011 ACM Symposium on Applied Computing. ACM, 2011. P. 113-118.
  • Wu, Shin-yi and Banker, Rajiv D. Best pricing strategy for information services//Journal of the Association for Information Systems. 2010. N 3. V. 11. P. 339-366.
  • Jianhui Huang and Robert J. Kauffman and Dan Ma. Pricing strategy for cloud computing: A damaged services perspective//Decision Support Systems. 2016. V. 78. P. 80-92.
  • Chun S., Choi В., Ко Y., Hwang S. Frontier and Innovation in Future Computing and Communications//The Comparison of Pricing Schemes for Cloud Services. Springer Netherlands, 2014. P. 853-861.
  • Amazon EC2 spot cloud. : http://spotcloud. com/.
  • Cloudorado: Cloud computing comparison engine. : https://www.cloudorado.com/.
  • SlVADON Chaisiri and Bu-Sung I. к к and DusiT NlYATO. Optimization of Resource Provisioning Cost in Cloud Computing//IEEE Transactions on Services Computing. 2012. V. 5. P. 164^177.
  • H. Li and J. Liu and G. Tang. A Pricing Algorithm for Cloud Computing Resources//Proceedings of the International Conference on Network Computing and Information Security (NCIS). 2011. V. 1. P. 69-73.
  • Chun, Se-Hak and Choi, Byong-Sam. Service models and pricing schemes for cloud computing // Cluster Computing. Springer // 2014. V. 17. P. 529-535.
  • Sharma, Bhanu and Thulasiram, Ruppa К and Thulasiraman, Parimala and Buyya, Rajkumar. Clabacus: a risk-adjusted cloud resources pricing model using financial option theory//IEEE Transactions on Cloud Computing. IEEE, 2015. V. 3. P. 332-311.
  • Mashayekhy, Lena and Nejad, Mahyar Movahed and Grosu, Daniel and Vasilakos, Athanasios V. An online mechanism for resource allocation and pricing in clouds//IEEE Transactions on Computers. IEEE, 2016. V. 65. P. 1172-1184.
  • K. Ahmed and M. gregory. Integrating Wireless Sensor Networks with Cloud Computing//Proc. Seventh International Conference on Mobile Ad-hoc and Sensor Networks. 2011. P. 364-366.
  • D. Rane and A. Srivastava. Cloud Brokering Architecture for Dynamic Placement of Virtual Machines//2015 IEEE 8th International Conference on Cloud Computing. 2015. P. 661-668.
  • Smart Cloud Broker. : http://www. smartcloudbroker.com/.
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