<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>AWaRe-SAC: Proactive slice admission control under weather-induced capacity uncertainty</dc:title><dc:creator>Jacoby, D; Li, Y; Yu, S; DiCicco, N; Messer, H; Zussman, G</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Millimeter-wave (mmWave) links are increasingly
utilized in wireless x-haul transport to meet growing service
demands. However, the inherent susceptibility of mmWave links
to weather-related attenuation creates uncertainty about future
network capacity which can significantly affect Quality of Service
(QoS). This creates a critical challenge: how to make admission
control decisions for slices with QoS requirements, balancing
acceptance rewards against the risk of future QoS-violation
penalties due to capacity uncertainty? To address this, we develop
a proactive slice admission control framework that tightly integrates: (i) a predictor that leverages historical link measurements
to forecast short-term attenuation and quantify uncertainty; and
(ii) an admission control algorithm that incorporates both the
predictions and uncertainties to maximize rewards and minimize
QoS-violation penalties. We compare our framework against
baseline, state-of-the-art, and idealized oracle algorithms using
real-world mmWave x-haul data and residential traffic traces.
Simulations suggest that our framework can achieve revenues
that are 250% larger than baseline algorithms and 75% larger
than state-of-the-art algorithms.</dc:description><dc:publisher>arXiv and  in Proc. WiOpt’26 (to appear), 2026.</dc:publisher><dc:date>2026-03-02</dc:date><dc:nsf_par_id>10678855</dc:nsf_par_id><dc:journal_name/><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn/><dc:isbn/><dc:doi>https://doi.org/</dc:doi><dcq:identifierAwardId>2148128</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>