AI-Optimized Cost-Aware Design Strategies for Resource-Efficient Applications
DOI:
https://doi.org/10.55662/JST.2023.4101Downloads
Keywords:
Artificial Intelligence, Cloud computing, Cloud-based ServicesAbstract
In the context of modern computing landscapes marked by escalating resource demands and cost considerations, this paper introduces a novel framework that integrates artificial intelligence (AI) for the creation of resource-efficient applications while maintaining a keen awareness of costs. The imperative to strike a harmonious equilibrium between application performance and expenses has never been more pressing, especially with the proliferation of cloud-based services. In response, our approach capitalizes on AI methodologies to dynamically analyze real-time application requisites, workload trends, and the availability of resources. Central to our methodology is the elevation of cost to a principal design determinant. We devise strategies that dynamically apportion resources, opt for suitable service tiers, and make necessary adjustments to application configurations. This duality of optimizing performance while curtailing expenditure underscores the essence of our approach. Rigorous simulations and empirical evaluations underscore the efficacy of our strategies across diverse scenarios, underscoring substantial cost reductions without compromising the quality of applications.
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References
R. S. S. Dittakavi, "IAAS CLOUD ARCHITECTURE DISTRIBUTED CLOUD INFRA STRUCTURES AND VIRTUALIZED DATA CENTERS."
G. Erion et al., "A cost-aware framework for the development of AI models for healthcare applications," Nature Biomedical Engineering, vol. 6, no. 12, pp. 1384-1398, 2022.
https://doi.org/10.1038/s41551-022-00872-8
PMid:35393566 PMCid:PMC9537352
X. Bao, N. J. Jorgensen, and B. Namatherdhala, "System and method for matching specialists and potential clients," ed: Google Patents, 2023.
A. Verma, P. Ahuja, and A. Neogi, "pMapper: power and migration cost aware application placement in virtualized systems," in ACM/IFIP/USENIX international conference on distributed systems platforms and open distributed processing, 2008: Springer, pp. 243-264.
https://doi.org/10.1007/978-3-540-89856-6_13
T. Ouyang, X. Chen, L. Zeng, and Z. Zhou, "Cost-aware edge resource probing for infrastructure-free edge computing: From optimal stopping to layered learning," in 2019 IEEE Real-Time Systems Symposium (RTSS), 2019: IEEE, pp. 380-391.
https://doi.org/10.1109/RTSS46320.2019.00041
PMid:30248458
G. Erion et al., "CoAI: Cost-aware artificial intelligence for health care," Nature biomedical engineering, vol. 6, no. 12, p. 1384, 2022.
https://doi.org/10.1101/2021.01.19.21249356
G.-H. Lee, U. E. Akpudo, and J.-W. Hur, "FMECA and MFCC-based early wear detection in gear pumps in cost-aware monitoring systems," Electronics, vol. 10, no. 23, p. 2939, 2021.
https://doi.org/10.3390/electronics10232939
A. B. Kareem, U. Ejike Akpudo, and J.-W. Hur, "An Integrated Cost-Aware Dual Monitoring Framework for SMPS Switching Device Diagnosis," Electronics, vol. 10, no. 20, p. 2487, 2021.
https://doi.org/10.3390/electronics10202487
B. Boroumand, E. Yaghoubi, and B. Barekatain, "An enhanced cost-aware mapping algorithm based on improved shuffled frog leaping in network on chips," The Journal of Supercomputing, vol. 77, pp. 498-522, 2021.
https://doi.org/10.1007/s11227-020-03271-5
J. Chen, C.-H. Chang, J. Ding, R. Qiao, and M. Faust, "Tap delay-and-accumulate cost aware coefficient synthesis algorithm for the design of area-power efficient FIR filters," IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 2, pp. 712-722, 2017.
https://doi.org/10.1109/TCSI.2017.2725916
J.-w. Park, M.-W. Lee, J. Kim, S.-w. Hwang, and S. Kim, "Costriage: A cost-aware triage algorithm for bug reporting systems," in Proceedings of the AAAI Conference on Artificial Intelligence, 2011, vol. 25, no. 1, pp. 139-144.
https://doi.org/10.1609/aaai.v25i1.7839
R. Han, M. M. Ghanem, L. Guo, Y. Guo, and M. Osmond, "Enabling cost-aware and adaptive elasticity of multi-tier cloud applications," Future Generation Computer Systems, vol. 32, pp. 82-98, 2014.
https://doi.org/10.1016/j.future.2012.05.018
V. Eramo, F. G. Lavacca, T. Catena, and F. Di Giorgio, "Reconfiguration of optical-NFV network architectures based on cloud resource allocation and QoS degradation cost-aware prediction techniques," IEEE Access, vol. 8, pp. 200834-200850, 2020.
https://doi.org/10.1109/ACCESS.2020.3035749
G. Fursin, A. Memon, C. Guillon, and A. Lokhmotov, "Collective Mind, Part II: Towards performance-and cost-aware software engineering as a natural science," arXiv preprint arXiv:1506.06256, 2015.
P. Luong, D. Nguyen, S. Gupta, S. Rana, and S. Venkatesh, "Adaptive cost-aware Bayesian optimization," Knowledge-Based Systems, vol. 232, p. 107481, 2021.
https://doi.org/10.1016/j.knosys.2021.107481
Y. Zhou, D. Sokolov, and A. Yakovlev, "Cost-aware synthesis of asynchronous circuits based on partial acknowledgement," in Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design, 2006, pp. 158-163.
https://doi.org/10.1109/ICCAD.2006.320080
S. Long, W. Long, Z. Li, K. Li, Y. Xia, and Z. Tang, "A game-based approach for cost-aware task assignment with QoS constraint in collaborative edge and cloud environments," IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 7, pp. 1629-1640, 2020.
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Copyright (c) 2023 Raghava Satya SaiKrishna Dittakavi (Author)
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Authors of this research paper submitted to the Journal of Science & Technology retain the copyright of their work while granting the journal certain rights. Authors maintain ownership of the copyright and have granted the journal a right of first publication. Simultaneously, authors agreed to license their research papers under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License.
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Under the CC BY-NC-SA 4.0 License, others are permitted to share and adapt the work, as long as proper attribution is given to the authors and acknowledgement is made of the initial publication in the Journal of Science & Technology. This license allows for the broad dissemination and utilization of research papers.
Additional Distribution Arrangements:
Authors are free to enter into separate contractual arrangements for the non-exclusive distribution of the journal's published version of the work. This may include posting the work to institutional repositories, publishing it in journals or books, or other forms of dissemination. In such cases, authors are requested to acknowledge the initial publication of the work in the Journal of Science & Technology.
Online Posting:
Authors are encouraged to share their work online, including in institutional repositories, disciplinary repositories, or on their personal websites. This permission applies both prior to and during the submission process to the Journal of Science & Technology. Online sharing enhances the visibility and accessibility of the research papers.
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Authors are responsible for ensuring that their research papers do not infringe upon the copyright, privacy, or other rights of any third party. The Journal of Science & Technology and The Science Brigade Publishers disclaim any liability or responsibility for any copyright infringement or violation of third-party rights in the research papers.