BASE STATION POWER BACKUP SCHEDULING FOR NETWORK PROVIDERS BY A THREE-PERSON DYADIC GAME
DOI:
https://doi.org/10.20535/2411-2976.22024.68-76Keywords:
power backup, network providers, QoS, three-person dyadic game, best symmetric situation, schedulingAbstract
Background. Recently reliable telecommunication has been challenged due to power grid instability and temporary blackouts. There is a strong need for optimizing the base station power backup for telecommunication network providers.
Objective. The purpose of the paper is to substantiate a game model of optimizing the base station power backup for three major telecommunication network providers and determine the best strategy. The optimization is based on payoff symmetry, rather than equilibrium.
Methods. There are only two pure strategies at the provider — to apply the power backup or ignore applying, whenever needed. The latter means avoiding additional expenses for the provider while applying the power backup requires additional expenses. The cost of applying the power backup is set to a conditional unit. It is further assumed that, if only one provider does not apply the power backup, it does not affect the quality of service (QoS). When there is no backup at all, QoS worsens significantly, users subsequently seek for alternative telecommunication services, and shortly every provider loses the 3 units.
Results. The provider’s expected payoff, being treated as a loss, is minimized over the set of symmetric mixed situations, where the provider’s mixed strategy is the no-backup probability. The base station power backup best strategy is realized by turning the power backup off with an irrational probability whose value lies between 0.05904144 and 0.05904145. It is more likely that the backup state switch is possible at definite time intervals usually counted in hours or days.
Conclusions. The best strategy allows saving the power backup for 5.904 % of the temporarily-off-the-grid period by saving 2.9 % of expenses for the backup, which does not worsen the QoS. Whenever the amounts of providers’ expenses, costs, and losses are changed, the best strategy is determined in the same way it has been found.
References
G. Diaz and M. Chahbar, “Towards a QoS-aware network virtual deployment for network-as-a-service,” Journal of Ambient Intelligence and Humanized Computing, vol. 15, pp. 623 — 639, 2024.
https://doi.org/10.1007/s12652-023-04719-1
R. Kundel, “Design of QoS-Aware Network Functions,” In: R. Kundel (Ed.), Accelerating Network Functions Using Reconfigurable Hardware. Springer Theses. Springer, Cham, 2024, pp. 37 — 91.
https://doi.org/10.1007/978-3-031-52872-9_3
Digital Transformation Ministry conducting survey on national roaming / The New Voice of Ukraine [Online].
Available: https://english.nv.ua/business/digital-transformation-ministry-conducting-survey-on-national-roaming-50301315.html. [Posted: February 1, 2023], [Accessed: September 10, 2024].
G. Tang, D. Guo, and K. Wu, “Optimal Backup Power Allocation for 5G Base Stations,” In: G. Tang, D. Guo, and K. Wu (Eds.), GreenEdge: New Perspectives to Energy Management and Supply in Mobile Edge Computing. SpringerBriefs in Computer Science. Springer, Singapore, 2022, pp. 51 — 65.
https://doi.org/10.1007/978-981-16-9690-9_4
M. A. Rahman, S. Asif, M. S. Hossain, T. Alam, A. W. Reza, and M. S. Arefin, “A Sustainable Approach to Reduce Power Consumption and Harmful Effects of Cellular Base Stations,” In: P. Vasant, G. W. Weber, J. A. Marmolejo-Saucedo, E. Munapo, J. J. Thomas (Eds.), Intelligent Computing & Optimization. ICO 2022. Lecture Notes in Networks and Systems, vol. 569. Springer, Cham, 2023, pp. 695 — 707.
https://doi.org/10.1007/978-3-031-19958-5_66
M. Hammoum, M. E. Khanouche, N. Khoulalene, and B. Benatallah, “Uncertainty QoS-aware services composition: a systematic literature review for services community,” Service Oriented Computing and Applications, vol. 18, pp. 121 — 143, 2024.
https://doi.org/10.1007/s11761-024-00389-9
W. Jiang and B. Han, “Evolution Toward Sixth-Generation (6G) Mobile Cellular Systems,” In: W. Jiang and B. Han (Eds.), Cellular Communication Networks and Standards. Textbooks in Telecommunication Engineering. Springer, Cham, 2024, pp. 195 — 210.
https://doi.org/10.1007/978-3-031-57820-5_11
M. Ayaz, A. Hussain, T. Hussain, and I. Ali, “Optimization of Quality of Service in 5G Cellular Network by Focusing on Interference Management,” Wireless Personal Communications, vol. 135, pp. 2229 — 2254, 2024. https://doi.org/10.1007/s11277-024-11139-7
D. Srinivasa Rao, C. Rajasekhar, and G. Naidu, “Performance Comparison of QoS Aware Power Allocation and Optimization Techniques for the Small-Cell 5G Networks,” In: A. Verma, P. Verma, K. K. Pattanaik, S. K. Dhurandher, and I. Woungang (Eds.), Advanced Network Technologies and Intelligent Computing. ANTIC 2023. Communications in Computer and Information Science, vol. 2091. Springer, Cham, 2024, pp. 17 — 28.
https://doi.org/10.1007/978-3-031-64064-3_2
D. Ye and J. Chen, “Non-cooperative games on multidimensional resource allocation,” Future Generation Computer Systems, vol. 29, iss. 6, pp. 1345 — 1352, 2013. https://doi.org/10.1016/j.future.2013.02.004
D. Fudenberg and J. Tirole, Game Theory. MIT Press, Cambridge, MA, 1991.
A. A. Elbaset and S. Ata, “Regenerative Fuel Cells as a Backup Power Supply,” In: A. A. Elbaset and S. Ata (Eds.), Hybrid Renewable Energy Systems for Remote Telecommunication Stations. Springer, Cham, 2021, pp. 19 — 33. https://doi.org/10.1007/978-3-030-66344-5_3
V. V. Romanuke, “Environment guard model as dyadic three-person game with the generalized fine for the reservoir pollution,” Ecological Safety and Nature Management, iss. 6, pp. 77 — 94, 2010.
V. V. Romanuke, “Ecological-economic balance in fining environmental pollution subjects by a dyadic 3-person game model,” Applied Ecology and Environmental Research, vol. 17, no. 2, pp. 1451 — 1474, 2019.
https://doi.org/10.15666/aeer/1702_14511474
V. V. Romanuke, “Recommendations on using the nonequilibrium symmetric situation in a dyadic game as a model of the environment preservation with the three subjects of pollution,” Ecological Safety and Nature Management, iss. 5, pp. 144 — 159, 2010.
J. Sostrin, The Manager’s Dilemma: Balancing the Inverse Equation of Increasing Demands and Shrinking Resources. Palgrave Macmillan New York, 2015.
C. Süring and H. P. Weikard, “Coalition stability in international environmental matching agreements,” Group Decision and Negotiation, vol. 33, pp. 587 — 615, 2024. https://doi.org/10.1007/s10726-024-09878-w
P. Bao, Q. Xu, and Y. Yang, “Modeling and aggregated control of large-scale 5G base stations and backup energy storage systems towards secondary frequency support,” Applied Energy, vol. 357, Article no. 122498, 2024. https://doi.org/10.1016/j.apenergy.2023.122498
M. Haddad, G. Da Costa, J.-M. Nicod, M.-C. Péra,
J.-M. Pierson, V. Rehn-Sonigo, P. Stolf, and C. Varnier, “Combined IT and power supply infrastructure sizing for standalone green data centers,” Sustainable Computing: Informatics and Systems, vol. 30, Article no. 100505, 2021. https://doi.org/10.1016/j.suscom.2020.100505
A. Israr and Q. Yang, “Chapter 9 — Resilient and sustainable microgeneration power supply for 5G mobile networks,” In: Q. Yang, T. Yang, and W. Li (Eds.), Renewable Energy Microgeneration Systems. Academic Press, 2021, pp. 213 — 228.
https://doi.org/10.1016/B978-0-12-821726-9.00009-6
G. J. Mailath and L. Samuelson, Repeated Games and Reputations: Long-Run Relationships. Oxford University Press, 2006.
