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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 2/2019

26.09.2018

Toward maximization of profit and quality of cloud federation: solution to cloud federation formation problem

verfasst von: Benay Kumar Ray, Avirup Saha, Sunirmal Khatua, Sarbani Roy

Erschienen in: The Journal of Supercomputing | Ausgabe 2/2019

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Abstract

The emergence of cloud computing has led to an astronomical growth in the computing services provided by vendors over the cloud interface. This has led to the paradigm of cloud federations where a group of CSPs collaborate to form a federation for seamless provisioning of resource requests. In this paper, cloud federation formation framework is modeled as a multi-objective optimization problem with the trade-off between profit and QoS. Federation formation algorithms try to maximize the federation profit while maintaining a balance between the QoS and the profit of the members of the federation. We have applied Linear Scalarization as well as \(\varepsilon \)-constraint method to find the pareto-optimal solution to this multi-objective optimization problem. A heuristic-based algorithm for cloud federation formation following the integer linear program is proposed. We perform extensive experiments to investigate the performance of our proposed mechanism and show that our proposed mechanism yields optimized solution to the general problem of profit/QoS trade-off.
Vorheriger Artikel Transfer learning-based default prediction model for consumer credit in China
Nächster Artikel On the modelling of optimal coordinated checkpoint period in supercomputers

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Literatur
1.
Mashayekhy L, Nejad MM, Grosu D (2015) Cloud federations in the sky: formation game and mechanism. IEEE Trans Cloud Comput 3(1):14–27CrossRef
2.
Niyato D, Vasilakos AV, Kun Z (2011) Resource and revenue sharing with coalition formation of cloud providers: game theoretic approach. In: 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Newport Beach, CA, pp 215–224
3.
Wahab OA, Bentahar J, Otrok H, Mourad A (2016) Towards trustworthy multi-cloud services communities: a trust-based hedonic coalitional game. IEEE Trans Serv Comput PP(99):1
4.
Hung JC, Gangman Y (2017) Advances in next era cloud-empowered computing and techniques. J Supercomput 73(7):2843–2850CrossRef
5.
Rochwerger B, Breitgand D, Levy E, Galis A (2009) The reservoir model and architecture for open federated cloud computing. IBM J Res Dev 53(4):4:1–4:11CrossRef
6.
Rochwerger B, Breitgand D, Epstein A (2011) Reservoir when one cloud is not enough. IEEE Comput 44(3):44–51CrossRef
7.
Celesti A, Tusa F, Villari M, Puliafito A (2010) How to enhance cloud architectures to enable cross-federation. In: 2010 IEEE 3rd International Conference on Cloud Computing, Miami, FL, pp 337–345
8.
Nordal A, Kvalnes A, Hurley J, Johansen D (2011) Balava: federating private and public clouds. In: Proceedings of IEEE World Congress on Services, pp 569–577
9.
Yang X, Nasser B, Surridge M, Middleton S (2012) A business-oriented cloud federation model for real-time applications. Future Gener Comput Syst 28(8):1158–1167CrossRef
10.
Altmann J, Kashef MM (2014) Cost model based service placement in federated hybrid clouds. Future Gener Comput Syst 41:79–90CrossRef
11.
Van den Bossche R, Vanmechelen K, Broeckhove J (2010) Costoptimal scheduling in hybrid IaaS clouds for deadline constrained workloads. In: Proceedings of 3rd IEEE International Conference on Cloud Computing, pp 228–235
12.
Goiri I, Guitart J, Torres J (2010) Characterizing cloud federation for enhancing providers’ profit. In: IEEE 3rd International Conference on Cloud Computing, Miami, FL, pp 123–130
13.
Hassan MM, Song B, Huh EN (2011) Distributed resource allocation games in horizontal dynamic cloud federation platform. In: IEEE 13th International Conference on High Performance Computing and Communications, Banff, AB, pp 822–827
14.
Toosi A, Calheiros R, Thulasiram R, Buyya R (2011) Resource provisioning policies to increase IaaS providers profit in a federated cloud environment. In: Proceedings of 13th IEEE International Conference on High Performance Computing and Communications, pp 279–287
15.
Chaisiri S, Lee BS, Niyato D (2012) Optimization of resource provisioning cost in cloud computing. IEEE Trans Serv Comput 5(2):164–177CrossRef
16.
Messina F, Pappalardo G, Rosaci D, Santoro C, Sarn GML (2015) A trust-aware, self-organizing system for large-scale federations of utility computing infrastructures. Future Gener Comput Syst 56:77–94CrossRef
17.
Lee YH, Huang KC, Shieh MR (2017) Distributed resource allocation in federated clouds. J Supercomput 73(7):3196–3211CrossRef
18.
Abdi S, PourKarimi L, Ahmadi M (2018) Cost minimization for bag-of-tasks workflows in a federation of clouds. J Supercomput 74(6):2801–2822CrossRef
19.
Li H, Wu C, Li Z, Lau FCM (2013) Profit-maximizing virtual machine trading in a federation of selfish clouds. In: Proceedings of IEEE on INFOCOM, Turin, pp 25–29
20.
Zant BE, Amigo I, Gagnaire M (2014) Federation and revenue sharing in cloud computing environment. In: IEEE International Conference on Cloud Engineering, Boston, MA, pp 446–451
21.
Rebai S, Hadji M, Zeghlache D (2015) Improving profit through cloud federation. In: 12th Annual IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, pp 732–739
22.
Wang WJ, Chang YS, Lo WT (2013) Adaptive scheduling for parallel tasks with QoS satisfaction for hybrid cloud environments. J Supercomput 66(2):783–811CrossRef
23.
Ye S, Liu H, Leung Y, Chu X (2017) Reinsurance-emulated collaboration mechanism in cloud federation. In: 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). IEEE
24.
Bellaiche M, Adel A, Talal H (2018) A cooperative game for online cloud federation formation based on security risk assessment. In: 2018 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom). IEEE
25.
26.
27.
Ray BK, Sunirmal K, Sarbani R (2018) A game theoretic model for cloud federation, cloud computing for optimization: foundations, applications, and challenges. Springer, Cham, pp 73–97CrossRef
28.
Johnson P, Beverlin M (1970) Beta distribution, continuous univariate distributions-2. Wiley, New York, pp 37–56
29.
Bouguessa M (2012) Modeling outlier score distributions, advanced data mining and applications. Springer, Berlin, pp 713–725CrossRef
30.
Figueiredo MAT, Jain AK (2002) Unsupervised learning of finite mixture models. IEEE Trans Pattern Anal Mach Intell 24(3):381–396CrossRef
31.
Ji Y, Wu C, Liu P, Wang J, Coombes KR (2005) Applications of beta-mixture models in bioinformatics. Bioinformatics 21(9):2118–2122CrossRef
32.
33.
Holbrook MB (1992) Product quality, attributes, and brand name as determinants of price: the case of consumer electronics. Mark Lett 3(1):71–83CrossRef
34.
Firth M (1993) Price setting and the value of a strong brand name. Int J Res Mark 10(4):381–386CrossRef
35.
Shehzad U, Ahmad S, Iqbal K, Nawaz M, Usman S (2014) Influence of brand name on consumer choice and decision. IOSR J Bus Manag (IOSR-JBM) 16(6):72–76CrossRef
36.
37.
Miettinen K (1999) Nonlinear multiobjective optimization. Springer international series in operations research and management science, vol 12. Springer US, New York
38.
39.
Klee V, Minty GJ (1969) How good is the simplex algorithm? In: Shisha O (ed) Inequalities III (Proceedings of the Third Symposium on Inequalities held at the University of California, Los Angeles, California, 1–9 Sept 1969, Dedicated to the Memory of Theodore S. Motzkin). Academic Press, New York, pp 159–175 (1972)
40.
Schrijver A (1998) Theory of linear and integer programming. Wiley. ISBN 0-471-98232-6 (mathematical)
41.
Borgwardt KH (1987) The simplex method: a probabilistic analysis. Algorithms and combinatorics (study and research texts), vol 1. Springer, Berlin, p xii+268
42.
43.
44.
45.
Buyya R, Yeo C, Venugopal S, Broberg J, Brandic I (2009) Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener Comput Syst 25(6):599–616CrossRef
46.
Ray BK, Khatua S, Roy S (2014) Negotiation based service brokering using game theory. In: IEEE International Conference on Applications and Innovations in Mobile Computing (AIMoC)
47.
Grozev N, Buyya R (2014) Inter-cloud architectures and application brokering: taxonomy and survey. Softw Pract Exp 44(3):369–390CrossRef
Metadaten
Titel
Toward maximization of profit and quality of cloud federation: solution to cloud federation formation problem
verfasst von
Benay Kumar Ray
Avirup Saha
Sunirmal Khatua
Sarbani Roy
Publikationsdatum
26.09.2018
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 2/2019
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2620-2

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