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Private Cloud in 6G Networks: A Study from the Total Cost of Ownership Perspective

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6GN for Future Wireless Networks (6GN 2020)

Abstract

Security and privacy concerns are increasingly important when massive data processing and transferring becomes a reality in the era of the Sixth Generation (6G) Networks. Under this circumstance, it becomes a trend that the enterprises tend to host their data and services on private clouds dedicated to their own use, rather than the public cloud services. However, in contrary to the well-investigated total cost of ownership (TCO) for public clouds, the analytic research on the cost of purchase and operation for private clouds is still a blank. In this work, we first review the state-of-the-art TCO literature to summarize the models, tools, and cost optimization techniques for public clouds. Based on our survey, we envision the TCO modeling and optimization for private clouds by comparing the differences of features between public and private clouds.

This work was supported by Project 61902333 supported by National Natural Science Foundation of China, by the Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS).

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References

  1. Ardagna, D., Francalanci, C., Trubian, M.: A cost-oriented approach for infrastructural design. In: SAC (2004)

    Google Scholar 

  2. Bhimani, J., Yang, Z., Leeser, M., Mi, N.: Accelerating big data applications using lightweight virtualization framework on enterprise cloud, 09 2017. https://doi.org/10.1109/HPEC.2017.8091086

  3. Bittencourt, L.F., Madeira, E.R.M.: HCOC: a cost optimization algorithm for workflow scheduling in hybrid clouds. J. Internet Serv. Appl. 2, 207–227 (2011)

    Article  Google Scholar 

  4. Brocke, J.V., Lindner, M.: Service portfolio measurement - a framework for evaluating the financial consequences of out-tasking decisions, pp. 203–211, 01 2004. https://doi.org/10.1145/1035167.1035197

  5. Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging it platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25, 599–616 (2009)

    Article  Google Scholar 

  6. Calheiros, R., Netto, M., De Rose, C., Buyya, R.: EMUSIM: an integrated emulation and simulation environment for modeling, evaluation, and validation of performance of cloud computing applications. Softw. Pract. Exp. 43, 595–612 (2013). https://doi.org/10.1002/spe.2124

  7. Chang, V.I., Wills, G.B., Roure, D.D.: A review of cloud business models and sustainability. In: 2010 IEEE 3rd International Conference on Cloud Computing, pp. 43–50 (2010)

    Google Scholar 

  8. Chen, F., Schneider, J., Yang, Y., Grundy, J., He, Q.: An energy consumption model and analysis tool for cloud computing environments. In: 2012 First International Workshop on Green and Sustainable Software (GREENS), pp. 45–50, June 2012. https://doi.org/10.1109/GREENS.2012.6224255

  9. Choo, K.R., Gritzalis, S., Park, J.H.: Cryptographic solutions for industrial Internet-of-Things: research challenges and opportunities. IEEE Trans. Industr. Inf. 14(8), 3567–3569 (2018). https://doi.org/10.1109/TII.2018.2841049

    Article  Google Scholar 

  10. Dantas, J., Matos, R.R.M., Araujo, J., Maciel, P.R.M.: Eucalyptus-based private clouds: availability modeling and comparison to the cost of a public cloud. Computing 97, 1121–1140 (2015)

    Article  MathSciNet  Google Scholar 

  11. Development, H.P.E.: HPE Helion OpenStack (2019). https://www.hpe.com/us/en/product-catalog/detail/pip.hpe-helion-openstack-cloud-software.1010838414.html. Accessed 15 Oct 2019

  12. Dropbox: Dropbox (2019). https://www.dropbox.com/. Accessed 15 Oct 2019

  13. Centre for Economics and Business Research Ltd.: The cloud dividend: part one. The economic benefits of cloud computing to business and the wider EMEA economy-France, Germany, Italy, Spain and the UK. Business & Information Systems Engineering (2010)

    Google Scholar 

  14. Ellram, L.M.: Total cost of ownership: a key concept in strategic cost management decisions (1993)

    Google Scholar 

  15. Ellram, L.M.: Total cost of ownership: elements and implementation (1993)

    Google Scholar 

  16. Etro, F.: The economic consequences of the diffusion of cloud computing (2010)

    Google Scholar 

  17. Filiopoulou, E., Mitropoulou, P., Tsadimas, A., Michalakelis, C., Nikolaidou, M., Anagnostopoulos, D.: Integrating cost analysis in the cloud: a SoS approach. 2015 11th International Conference on Innovations in Information Technology (IIT), pp. 278–283 (2015)

    Google Scholar 

  18. Ghule, D., Gopal, A.: Comparison parameters and evaluation technique to help selection of right IaaS cloud. In: 2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), pp. 1–6, November 2018. https://doi.org/10.1109/UPCON.2018.8597059

  19. Google: Cloud Healthcare API (2019). https://cloud.google.com/healthcare/. Accessed 15 Oct 2019

  20. Google: Google App Engine (2019). https://cloud.google.com/appengine/. Accessed 15 Oct 2019

  21. Group, A.: Apsara Stack (2009). https://www.alibabacloud.com/product/apsara-stack. Accessed 15 Oct 2019

  22. Hamilton, J.: Cooperative expendable micro-slice servers (CEMS): low cost, low power servers for internet-scale services, 01 2009

    Google Scholar 

  23. Han, Y.: Cloud computing: case studies and total cost of ownership (2011)

    Google Scholar 

  24. Iglesias, J.O., Perry, P., Stokes, N., Thorburn, J., Murphy, L.: A cost-capacity analysis for assessing the efficiency of heterogeneous computing assets in an enterprise cloud. In: IEEE/ACM 6th International Conference on Utility and Cloud Computing, UCC 2013, Dresden, Germany, 9–12 December 2013, pp. 107–114. IEEE Computer Society (2013). https://doi.org/10.1109/UCC.2013.32

  25. Inc., D.: Dell EMC (2019). https://www.dellemc.com/en-us/solutions/cloud/vmware-cloud-on-dellemc.htm#scroll=off. Accessed 15 Oct 2019

  26. Jawad, M., et al.: A robust optimization technique for energy cost minimization of cloud data centers. IEEE Trans. Cloud Comput. 1 (2018). https://doi.org/10.1109/TCC.2018.2879948

  27. Klems, M., Nimis, J., Tai, S.: Do clouds compute? a framework for estimating the value of cloud computing. In: WEB (2008)

    Google Scholar 

  28. Kondo, D., Javadi, B., Malecot, P., Cappello, F., Anderson, D.P.: Cost-benefit analysis of cloud computing versus desktop grids. In: 2009 IEEE International Symposium on Parallel Distributed Processing, pp. 1–12, May 2009. https://doi.org/10.1109/IPDPS.2009.5160911

  29. Konecný, J., McMahan, H.B., Yu, F.X., Richtárik, P., Suresh, A.T., Bacon, D.: Federated learning: strategies for improving communication efficiency. CoRR abs/1610.05492 (2016). http://arxiv.org/abs/1610.05492

  30. Laatikainen, G., Tyrväinen, P.: Cost efficiency of hybrid cloud storage cost efficiency of hybrid cloud storage: shortening acquisition cycle to mitigate volume variation, 12 2015

    Google Scholar 

  31. Larsen, M.H., Holck, J., Pedersen, M.K.: The challenges of open source software in it adoption: enterprise architecture versus total cost of ownership (2004)

    Google Scholar 

  32. Li, A., Yang, X., Kandula, S., Zhang, M.: CloudCmp: comparing public cloud providers. In: Internet Measurement Conference (2010)

    Google Scholar 

  33. Li, X., Li, Y., Liu, T., Qiu, J., Wang, F.: The method and tool of cost analysis for cloud computing. In: 2009 IEEE International Conference on Cloud Computing, pp. 93–100, September 2009. https://doi.org/10.1109/CLOUD.2009.84

  34. Liew, S., Su, Y.Y.: CloudGuide: helping users estimate cloud deployment cost and performance for legacy web applications, pp. 90–98, 12 2012. https://doi.org/10.1109/CloudCom.2012.6427577

  35. Liu, Q., Cheng, L., Ozcelebi, T., Murphy, J., Lukkien, J.: Deep reinforcement learning for IoT network dynamic clustering in edge computing. In: 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), pp. 600–603, May 2019. https://doi.org/10.1109/CCGRID.2019.00077

  36. Mao, M., Li, J., Humphrey, M.: Cloud auto-scaling with deadline and budget constraints. In: 2010 11th IEEE/ACM International Conference on Grid Computing, pp. 41–48, October 2010. https://doi.org/10.1109/GRID.2010.5697966

  37. Skilton, M., Director, C., Cloud Business Artifacts Project, et al.: Building return on investment from cloud computing. White Paper (2009)

    Google Scholar 

  38. Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., Ghalsasi, A.: Cloudcomputing - the business perspective. Decis. Support Syst. 51(1), 176–189 (2011). https://doi.org/10.1016/j.dss.2010.12.006

  39. Martens, B., Walterbusch, M., Teuteberg, F.: Costing of cloud computing services: a total cost of ownership approach. In: 2012 45th Hawaii International Conference on System Sciences, pp. 1563–1572 (2012)

    Google Scholar 

  40. Mell, P., Grance, T.: The NIST definition of cloud computing. Natl. Inst. Stand. Technol. 53(6), 50 (2009)

    Google Scholar 

  41. Mencer, O., Vynckier, E., Spooner, J., Girdlestone, S., Charlesworth, O.: Finding the right level of abstraction for minimizing operational expenditure. In: WHPCF@SC (2011)

    Google Scholar 

  42. Microsoft: Azure Stack (2009). https://docs.microsoft.com/en-us/azure-stack/operator/azure-stack-overview?view=azs-1908. Accessed 15 Oct 2019

  43. Milligan, B.: Tracking total cost of ownership proves elusive. Purchasing 127, 22–23 (1999)

    Google Scholar 

  44. Molka, K., Byrne, J.: Towards predictive cost models for cloud ecosystems: poster paper. In: IEEE 7th International Conference on Research Challenges in Information Science (RCIS), pp. 1–2, May 2013. https://doi.org/10.1109/RCIS.2013.6577736

  45. Moyle, K.: Total cost of ownership and open source software (2004)

    Google Scholar 

  46. Mvelase, P., Sibiya, G., Dlodlo, N., Oladosu, J., Adigun, M.: A comparative analysis of pricing models for enterprise cloud platforms. In: 2013 Africon, pp. 1–7, September 2013. https://doi.org/10.1109/AFRCON.2013.6757870

  47. Orbegozo, I.S.A., Moreno-Vozmediano, R., Montero, R.S., Llorente, I.M.: Cloud capacity reservation for optimal service deployment. In: CLOUD 2011 (2011)

    Google Scholar 

  48. Pal, R., Hui, P.: Economic models for cloud service markets: pricing and capacity planning. Theoret. Comput. Sci. 496, 113–124 (2013)

    Article  MathSciNet  Google Scholar 

  49. Pandey, S., Wu, L., Guru, S.M., Buyya, R.: A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments. In: 2010 24th IEEE International Conference on Advanced Information Networking and Applications, pp. 400–407, April 2010. https://doi.org/10.1109/AINA.2010.31

  50. Patel, C.D., Shah, A.: Cost model for planning, development and operation of a data center (2005)

    Google Scholar 

  51. BONE Project: WP 21 tropical project green optical networks: report on year 1 and unpdate plan for activities. No. FP7-ICT-2007- 1216863 BONE project (2009)

    Google Scholar 

  52. Qing, L., Boyu, Z., Jinhua, W., Qinqian, L.: Research on key technology of network security situation awareness of private cloud in enterprises. In: 2018 IEEE 3rd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), pp. 462–466, April 2018. https://doi.org/10.1109/ICCCBDA.2018.8386560

  53. Ren, K., Wang, C., Wang, Q.: Security challenges for the public cloud. IEEE Internet Comput. 16(1), 69–73 (2012). https://doi.org/10.1109/MIC.2012.14

    Article  Google Scholar 

  54. da Rosa Righi, R., et al.: A survey on global management view: toward combining system monitoring, resource management, and load prediction. J. Grid Comput. 17(3), 473–502 (2019). https://doi.org/10.1007/s10723-018-09471-x

    Article  Google Scholar 

  55. Sharma, U., Shenoy, P., Sahu, S., Shaikh, A.: A cost-aware elasticity provisioning system for the cloud. In: 2011 31st International Conference on Distributed Computing Systems, pp. 559–570, June 2011. https://doi.org/10.1109/ICDCS.2011.59

  56. Simonet, A., Lebre, A., Orgerie, A.: Deploying distributed cloud infrastructures: who and at what cost? In: 2016 IEEE International Conference on Cloud Engineering Workshop (IC2EW), pp. 178–183, April 2016. https://doi.org/10.1109/IC2EW.2016.48

  57. Singh, S., Aazam, M., St-Hilaire, M.: RACE: relinquishment-aware cloud economics model. In: 2017 24th International Conference on Telecommunications (ICT), pp. 1–6, May 2017. https://doi.org/10.1109/ICT.2017.7998279

  58. Sousa, E., Lins, F., Tavares, E., Cunha, P., Maciel, P.: A modeling approach for cloud infrastructure planning considering dependability and cost requirements. IEEE Trans. Syst. Man Cybern. Syst. 45(4), 549–558 (2015). https://doi.org/10.1109/TSMC.2014.2358642

    Article  Google Scholar 

  59. Sousa, E., Maciel, P., Medeiros, L., Lins, F., Tavares, E., Medeiros, E.: Stochastic model generation for cloud infrastructure planning. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics, pp. 4098–4103, October 2013. https://doi.org/10.1109/SMC.2013.699

  60. Subashini, S., Kavitha, V.: A survey on security issues in service delivery models of cloud computing. J. Netw. Comput. Appl. 34, 1–11 (2011)

    Article  Google Scholar 

  61. Sun, K., Li, Y.: Effort estimation in cloud migration process. In: 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering, pp. 84–91, March 2013. https://doi.org/10.1109/SOSE.2013.29

  62. Thanakornworakij, T., Nassar, R., Leangsuksun, C., Paun, M.: An economic model for maximizing profit of a cloud service provider. In: 2012 Seventh International Conference on Availability, Reliability and Security, pp. 274–279 (2012)

    Google Scholar 

  63. Trummer, I., Leymann, F., Mietzner, R., Binder, W.: Cost-optimal outsourcing of applications into the clouds. In: 2010 IEEE Second International Conference on Cloud Computing Technology and Science, pp. 135–142, November 2010. https://doi.org/10.1109/CloudCom.2010.64

  64. Tsalis, N., Theoharidou, M., Gritzalis, D.: Return on security investment for cloud platforms. In: 2013 IEEE 5th International Conference on Cloud Computing Technology and Science, vol. 2, pp. 132–137 (2013)

    Google Scholar 

  65. Uchechukwu, A., Li, K., Shen, Y.: Improving cloud computing energy efficiency. In: 2012 IEEE Asia Pacific Cloud Computing Congress (APCloudCC), pp. 53–58 (2012)

    Google Scholar 

  66. Vrek, N., Brumec, S.: Role of utilization rate on cloud computing cost effectiveness analysis. In: International Conference on Information Society (i-Society 2013), pp. 177–181, June 2013

    Google Scholar 

  67. Walterbusch, M., Martens, B., Teuteberg, F.: Evaluating cloud computing services from a total cost of ownership perspective. Manage. Res. Rev. 36, 613–638 (2013)

    Article  Google Scholar 

  68. Wan, Z.: Cloud computing infrastructure for latency sensitive applications. In: 2010 IEEE 12th International Conference on Communication Technology, pp. 1399–1402, November 2010. https://doi.org/10.1109/ICCT.2010.5689022

  69. Weinhardt, C., et al.: Cloud computing - a classification, business models, and research directions. Bus. Inf. Syst. Eng. 1, 391–399 (2009)

    Article  Google Scholar 

  70. Wu, L., Garg, S.K., Buyya, R.: SLA-based resource allocation for software as a service provider (SaaS) in cloud computing environments. In: 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 195–204, May 2011. https://doi.org/10.1109/CCGrid.2011.51

  71. Yu, Y., Bhatti, S.N.: Energy measurement for the cloud. In: International Symposium on Parallel and Distributed Processing with Applications, pp. 619–624 (2010)

    Google Scholar 

  72. Z Degraeve, F.R.: Improving the efficiency of the purchasing process using total cost of ownership information: the case of heating electrodes at Cockerill Sambre SA (1999)

    Google Scholar 

  73. Zhang, P., Han, Y., Zhao, Z., Wang, G.: Cost optimization of cloud-based data integration system. In: 2012 Ninth Web Information Systems and Applications Conference, pp. 183–188, November 2012. https://doi.org/10.1109/WISA.2012.13

  74. Zheng, L., Hu, Y., Yang, C.: Design and research on private cloud computing architecture to support smart grid. In: 2011 Third International Conference on Intelligent Human-Machine Systems and Cybernetics, vol. 2, pp. 159–161, August 2011. https://doi.org/10.1109/IHMSC.2011.109

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Chi, Y., Dai, W., Fan, Y., Ruan, J., Hwang, K., Cai, W. (2020). Private Cloud in 6G Networks: A Study from the Total Cost of Ownership Perspective. In: Wang, X., Leung, V.C.M., Li, K., Zhang, H., Hu, X., Liu, Q. (eds) 6GN for Future Wireless Networks. 6GN 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-63941-9_30

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