Abstract
This chapter illustrates the resource allocation in cloud IaaS. We detail how to optimize the VM instances allocation strategy using the novel ANN model. This chapter narrates the functionality and workflow of the system using the NFRLP and EARA algorithms. Further, several issues in implementing the resource allocation are also detailed. This chapter illustrates how the artificial neural network and genetic algorithm techniques are used in IaaS frame work to efficiently allocate the resources for VMs.
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References
K. Saravanan, M. Rajaram, An exploratory study of cloud service level agreements - state of the art review. KSII Trans. Internet Inform. Syst. 9(3), 843–871 (2015). https://doi.org/10.3837/tiis.2015.03.001. ISSN 1976-7277.IF0.561
H. Kuo-Chan, L. Kuan-Po, Processor allocation policies for reducing resource fragmentation in multi cluster grid and cloud environments (IEEE, 2010), pp. 971–976
D. Shin, H. Akkan, Domain-based virtualized resource management in cloud computing, in 2010 6th International Conference on Collaborative Computing: Networking, Applications and Work-sharing (CollaborateCom) (IEEE, 2010), pp. 1–6
J. Li, M. Qiu, J.W. Niu, Y. Chen, Z. Ming, Adaptive resource allocation for preemptable jobs in cloud systems, in 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA) (IEEE, 2010), pp. 31–36
J.O. Melendez, S. Majumdar, Matchmaking with limited knowledge of resources on clouds and grids, in 2010 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS) Ottawa, ON (2010), pp. 102–110
K. Kumar, J. Feng, Y. Nimmagadda, Y.H. Lu, Resource allocation for real-time tasks using cloud computing, in 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN) (IEEE, 2011), pp. 1–7
K. Zhen, Z.X. Cheng, G. Minyi, Mechanism design for stochastic virtual resource allocation in non cooperative cloud systems, in IEEE 4th International Conference on Cloud Computing (2011), pp. 614–621
F. Wuhib, R. Stadler, Distributed monitoring and resource management for large cloud environments, in 2011 IFIP/IEEE International Symposium on Integrated Network Management (IM) (IEEE, 2011), pp. 970–975
D. Niyato, K. Zhu, P. Wang, Cooperative virtual machine management for multi-organization cloud computing environment, in Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools (ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 2011), pp. 528–537
H. Nguyen Van, F. Dang Tran, J.M. Menaud, Autonomic virtual resource management for service hosting platforms, in Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing (IEEE Computer Society, 2009), pp. 1–8
H. Weisong, T. Chao, L. Xiaowei, Q. Hongwei, Z. Li, L. Huaming, Multiple job optimization in MapReduce for heterogeneous workloads, in IEEE 6th International Conference on Semantics, Knowledge and Grids (2010), pp. 35–140
L. Xiaoyi, L. Jian, Z. Li, X. Zhiwei, Vega ling cloud: a resource single leasing point system to support heterogeneous application modes on shared infrastructure (IEEE, 2011), pp. 99–106
L. Wei-Yu, L. GuanYu, L. Hung-Yu, Dynamic auction mechanism for cloud resource allocation, in IEEE/ACM 10th International Conference on Cluster, Cloud and Grid Computing (2010), pp. 591–592
Y. Xindong, X. Xianghua, W. Jian, Y. Dongjin, RAS-M: Resource allocation strategy based on market mechanism in cloud computing (IEEE, 2009), pp. 256–263
M. Uthayabanu, K. Saravanan, Optimizing the cost for resource subscription policy in IaaS cloud. Int. J. Eng. Trends Technol. (IJETT), Seventh Sense Res. Group 6(5), 296 (2014)
T.H. Tram, M. John, Virtual resource allocations distribution on a cloud infrastructure (IEEE, 2010), pp. 612–617
P. Xiong, Y. Chi, S. Zhu, H.J. Moon, C. Pu, H. Hacigm, Intelligent management of virtualized resources for database systems in cloud environment, in 2011 IEEE 27th International Conference on Data Engineering (ICDE) (IEEE, 2011), pp. 87–98
W. Linlin, K.G. Saurabh, R. Buyya, SLA–based resource allocation for SaaS provides in cloud computing environments. IEEE. 195–204 (2011)
R.T. Ma, D.M. Chiu, J.C. Lui, V. Misra, D. Rubenstein, On resource management for cloud users: a generalized kelly mechanism approach. Electr. Eng. Tech. Rep. (2010)
A. Radhakrishnan, V. Kavitha, Energy conservation in cloud data centers by minimizing virtual machines migration through artificial neural network. Comput. Springer–Verlag Wien, 98, 1185–1202 (2016)
A. Radhakrishnan, V. Kavitha, Proficient decision making on virtual machine allocation in cloud environment. Int. Arab. J. Inf. Technol. 14 (2017)
S. Vinothina, R. Sridaran, G. Padmavathi, A survey on resource allocation strategies in cloud. Int. J. Adv. Comput. Sci. Appl. 3, 98–104 (2012)
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Radhakrishnan, A., Saravanan, K. (2018). Energy Aware Resource Allocation Model for IaaS Optimization. In: Mishra, B., Das, H., Dehuri, S., Jagadev, A. (eds) Cloud Computing for Optimization: Foundations, Applications, and Challenges. Studies in Big Data, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-319-73676-1_3
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DOI: https://doi.org/10.1007/978-3-319-73676-1_3
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