Passively cooled base stations (PCBSs) offer low deployment cost and energy consumption for the next generation networks. By its nature, however, dealing with the thermal issue becomes crucial. For an outdoor PCBS, a major challenge is that the heat dissipation is uncertain over time. We address this online temperature scheduling problem with uncertain parameters via adjustable robust optimization (ARO) embedded into a re-optimization framework. In each optimization instance, temperature pre-scheduling is done to achieve solution robustness, looking ahead into forthcoming time slots. The solution is adaptive with respect to the gradually realized heat dissipation. Interestingly, we prove that the robust temperature pre-scheduling problem can be addressed via solving a compact linear program (LP), even though the number of possible realizations of heat dissipation is infinite. Simulation results show that our algorithm achieves robustness as well as very good average performance.
Robust Online Temperature Management for Passively Cooled Base Stations
24.06.2024
1118643 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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