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C–SLO: Carbon–and SLO–Aware Global Load Balancing for Online Services

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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1017/cbo9780511804441openalex-snapshot
Convex Optimization
inferredcites →https://doi.org/10.1109/cloud62652.2024.00062openalex-snapshot
Carbon-Aware and Fault-Tolerant Migration of Deep Learning Workloads in the Geo-Distributed Cloud
inferredcites →https://doi.org/10.1109/tsusc.2021.3086087openalex-snapshot
Energy and Network Aware Workload Management for Geographically Distributed Data Centers
inferredcites →https://doi.org/10.1109/tsusc.2024.3391791openalex-snapshot
CFWS: DRL-Based Framework for Energy Cost and Carbon Footprint Optimization in Cloud Data Centers
inferredcites →https://doi.org/10.1145/2408776.2408794openalex-snapshot
The tail at scale
inferredcites →https://doi.org/10.1145/3604930.3605711openalex-snapshot
Bringing Carbon Awareness to Multi-cloud Application Delivery
inferredcites →https://doi.org/10.1561/2200000018openalex-snapshot
Online Learning and Online Convex Optimization
inferredcites →https://doi.org/10.3390/computers14070280openalex-snapshot
Carbon-Aware, Energy-Efficient, and SLA-Compliant Virtual Machine Placement in Cloud Data Centers Using Deep Q-Networks and Agglomerative Clustering
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