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Stefan cel Mare
University of Suceava
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ROMANIA

Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  4/2021 - 11

A Security-Driven Approach for Energy-Aware Cloud Resource Pricing and Allocation

MIKAVICA, B. See more information about MIKAVICA, B. on SCOPUS See more information about MIKAVICA, B. on IEEExplore See more information about MIKAVICA, B. on Web of Science, KOSTIC-LJUBISAVLJEVIC, A. See more information about KOSTIC-LJUBISAVLJEVIC, A. on SCOPUS See more information about KOSTIC-LJUBISAVLJEVIC, A. on SCOPUS See more information about KOSTIC-LJUBISAVLJEVIC, A. on Web of Science
 
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Download PDF pdficon (2,003 KB) | Citation | Downloads: 616 | Views: 1,085

Author keywords
decision making, energy consumption, security, simulation, virtual machining

References keywords
cloud(29), comput(13), energy(12), computing(10), security(9), resource(9), data(8), auction(8), virtual(6), centers(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-11-30
Volume 21, Issue 4, Year 2021, On page(s): 99 - 106
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.04011
Web of Science Accession Number: 000725107100011
SCOPUS ID: 85122259459

Abstract
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Auctions are often recommended as effective cloud resource pricing and allocation mechanism. If adequately set, auctions provide incentives for cloud users truthful bidding and support cloud providers revenue maximization. In such a cloud system, resources are offered via an auction mechanism as Virtual Machines (VMs). Due to the virtualization of the cloud system, VMs security becomes a critical factor. However, security requirements are often in contrast with performance requirements since the operation of security mechanism inevitably consumes a certain amount of Central Processing Time (CPU) and memory. Thus, delays and energy consumption increase. In this paper, we propose a novel simulation model based on a truthful auction mechanism to address revenues, security, and energy consumption in a cloud system. The VMs security modeling is introduced to assess the security level of VMs. A Vickrey-Clarke-Groves (VCG) driven algorithm is established for winner determination. The proposed simulation model is used to observe cloud providers revenues, lost revenues, cloud users' task rejection rate and energy consumption depending on the offered security level. This model supports decision making in terms of investments in security and selection of security scenario that maximizes revenues and minimizes task rejection rate and energy consumption.


References | Cited By  «-- Click to see who has cited this paper

[1] Y. S. Patel, Z. Malwi, A. Nighojkar, "Truthful online double auction based dynamic resource provisioning for multi-objective trade-offs in IaaS clouds," Cluster Comput., 2021.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 13]


[2] R. Yadav, W. Zhang, K. Li, C. Liu, A. A. Laghari, "Managing overloaded hosts for energy-efficiency in cloud data centers," Cluster Comput., 2021.
[CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 42]


[3] D. Gonzales, J. Kaplan, E. Saltzman, Z. Winkelman, D. Woods, "Cloud-trust - a security assessment model for infrastructure as a service (IaaS) clouds," IEEE Trans. Cloud Comput., vol. 5, no. 3, pp. 523-536, 2017.
[CrossRef] [Web of Science Times Cited 67] [SCOPUS Times Cited 101]


[4] H. Xu, X. Qiu, Y. Sheng, L. Luo, Y. Xiang, "A QoS-driven approach to the cloud service addressing attributes of security," IEEE Access., vol. 6, pp. 34477-34487, 2018.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 12]


[5] B. Mikavica, A. Kostic-Ljubisavljevic, "Auction-based pricing in cloud environment," In M. Khosrow-Pour (eds), Encyclopedia of Organizational Knowledge, Administration, and Technologies. IGI Global, pp. 86-97, 2021.
[CrossRef] [SCOPUS Times Cited 5]


[6] M. Amoon, T. E. El-Tobely, "A green energy-efficient scheduler for cloud data centers," Cluster Comput., vol. 22, pp. 3247-3259, 2019.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]


[7] R. Yadav, W. Zhang, O. Kaiwartya, P. R. Singh, I. A. Elgendy, Y. Tian, "Adaptive energy-aware algorithms for minimizing energy consumption and SLA violation in cloud computing," IEEE Access, vol. 6, pp. 55923-55936, 2018.
[CrossRef] [Web of Science Times Cited 103] [SCOPUS Times Cited 130]


[8] Z. Tong, X. Deng, H. Chen, J. Mei, "DDMTS: A novel dynamic load balancing scheduling scheme under SLA constraints in cloud computing," J. Parallel Distrib. Comput, vol. 149, pp. 138-148, 2021.
[CrossRef] [Web of Science Times Cited 21] [SCOPUS Times Cited 28]


[9] Y. Saadi, S. El Kafhali, "Energy-efficient strategy for virtual machine consolidation in cloud environment," Soft Comput., vol. 24, pp. 14845-14859, 2020.
[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 49]


[10] S. Azizi, M. Zandsalimi, D. Li, "An energy-efficient algorithm for virtual machine placement optimization in cloud data centers," Cluster Comput., vol. 23, pp. 3421-3434, 2020.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 52]


[11] A. Tarafdar, M. Debnath, S. Khatua, R. K. Das, "Energy and quality of service-aware virtual machine consolidation in a cloud data center," J. Supercomput., vol. 76, pp. 9095-9126, 2020.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 34]


[12] B. Alouffi, M. Hasnain, A. Alharbi, W. Alosaimi, H. Alyami, M. Ayaz, "A systematic literature review on cloud computing security: threats and mitigation strategies," IEEE Access., vol. 9, pp. 57792-57807, 2021.
[CrossRef] [Web of Science Times Cited 64] [SCOPUS Times Cited 118]


[13] B. G. Batista, C. H. G. Ferreira, D. C. M. Segura, D. M. L. Filho, M. L. M. Peixoto, "A QoS-driven approach for cloud computing addressing attributes of performance and security," Future Gener. Comput. Syst., vol. 68, pp. 260-274, 2017.
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 38]


[14] J. Chen, Q. Zhu, "Security as a service for cloud-enabled internet of controlled things under advanced persistent threats: a contract design approach," IEEE Trans. Inf. Forensics Security, vol. 12, no. 11, pp. 2736-2750, 2017.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 73]


[15] F. Sheikholeslami, N. J. Navimipour, "Auction-based resource allocation mechanisms in the cloud environments: a review of the literature and reflection on future challenges," Concurr. Comput. Pract. Exp., vol. 30, no. 16, pp. 1-15, 2018.
[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 43]


[16] G. Baranwal, D. Kumar, Z. Raza, D. P. Vidyarthi. Auction based resource provisioning in cloud computing, pp. 38-43, Spinger. 2018

[17] X. Wang, X. Chen, W. Wu, "Towards truthful auction mechanisms for task assignment in mobile device clouds," in Proc. IEEE Conf. Computer Communications (INFOCOM), Atlanta, 2017, pp. 1-9.
[CrossRef] [SCOPUS Times Cited 62]


[18] T. Halabi, M. Bellaiche, A. Abusitta, "Cloud security up for auction: a dsic online mechanism for secure IaaS resource allocation," in Proc. 2nd Cyber Security in Networking Conference (CSNet), Paris, 2018, pp. 1-8.
[CrossRef] [SCOPUS Times Cited 6]


[19] B. Mikavica, A. Kostic-Ljubisavljevic, D. Popovic, "A security-driven approach to the auction-based cloud service pricing," Int. J. Transport and Traffic Engineering, vol. 11. no. 2, pp. 213-228, 2020.
[CrossRef]


[20] W. Song, Z. Xiao, Q. Chen, H. Luo, "Adaptive resource provisioning for the cloud using online bin packing," IEEE Trans. Comput., vol. 63, no. 11, pp. 2647-2660, 2014.
[CrossRef] [Web of Science Times Cited 157] [SCOPUS Times Cited 193]


[21] H. Cambazard, D. Mehta, B. O'Sullivan, H. Simonis, "Bin packing with linear usage costs - an application to energy management in data centres," In Schulte C. (eds), Principles and Practice of Constraint Programming. CP 2013. Lecture Notes in Computer Science, vol. 8124. Springer, 2013.
[CrossRef] [SCOPUS Times Cited 13]


[22] C. Mastroianni, M. Meo, G. Papuzzo, "Probabilistic consolidation of virtual machines in self-organizing cloud data centers," IEEE Trans. Cloud Comput., vol. 1, no. 2, pp. 215-228, 2013.
[CrossRef] [Web of Science Times Cited 125] [SCOPUS Times Cited 149]


[23] Z. Xiao, W. Song, Q. Chen, "Dynamic resource allocation using virtual machines for cloud computing environment," IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 6, pp. 1107-1117, 2013.
[CrossRef] [Web of Science Times Cited 495] [SCOPUS Times Cited 705]


[24] A. Beloglazov, J. Abawajy, R. Buyya, "Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing," Future Gener. Comput. Syst., vol. 28, no. 5, pp. 755-768, 2020.
[CrossRef] [Web of Science Times Cited 1698] [SCOPUS Times Cited 2235]


[25] A. Beloglazov, R. Buyya, "Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers," Concurr. Comput. Pract. Exp., vol. 24, no. 13, pp. 1397-1420, 2012.
[CrossRef] [Web of Science Times Cited 1127] [SCOPUS Times Cited 1454]


[26] J. Cao, K. Hwang, K. Li, A. Y. Zomaya, "Optimal multiserver configuration for profit maximization in cloud computing," IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 6, pp. 1087-1096, 2013.
[CrossRef] [Web of Science Times Cited 134] [SCOPUS Times Cited 162]


[27] T. T. Huu, C.-K. Tham, "An auction-based resource allocation model for green cloud computing," in Proc. IEEE Int. Conf. Cloud Eng. (IC2E), San Francisco, 2013, pp. 269-278.
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 38]


[28] W. Wang, Y. Jiang and W. Wu, "Multiagent-based resource allocation for energy minimization in cloud computing systems," IEEE Trans. Syst. Man, Cybern. Syst., vol. 47, no. 2, pp. 205-220, 2017.
[CrossRef] [Web of Science Times Cited 64] [SCOPUS Times Cited 94]


[29] B. Mikavica, A. Kostic-Ljubisavljevic, "Pricing and bidding strategies for cloud spot block instances," in Proc. 41st Int. Conv. Inf. Comm. Tech. Electr. Microelectr. (MIPRO), Opatija, 2018, pp. 419-424.
[CrossRef] [SCOPUS Times Cited 7]


[30] H. S. Choi, J. B. Lim, H. Yu, E. Y. Lee, "Task classification based energy-aware consolidation in clouds," Scientific Programming, vol. 2016, 6208358, 13p.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 20]




References Weight

Web of Science® Citations for all references: 4,368 TCR
SCOPUS® Citations for all references: 5,884 TCR

Web of Science® Average Citations per reference: 141 ACR
SCOPUS® Average Citations per reference: 190 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-03-28 03:28 in 168 seconds.




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