GreenGNN: Energy-Aware Windowed Communication Optimization for Distributed GNN Training
arXiv 2606.02916•b24f95dbd6feac1d3d45a5bb8286a1df05ce79703c9d6a3d24d241f253a2e63d
Byzantine-consensusGNNHNSWKafka-StreamsLLM-servingRPC-amortizationapproximate-nearest-neighborbitmap-representationblockchaincachingcloud-cost-optimizationdata-deduplicationdata-integrity risks','attack-surface','DoS-resource-exhaustion'distributed-systemsedge-computingenergy-efficiencyfuzzy-deduplicationgraph-neural-networksgraph-partitioningmodel-parallelismobject-storageprivacyshufflestream-processingunauthenticated-BFT
Paper metadata
- arXiv ID
- 2606.02916
- Version
- Not specified by this published record
- Category
- Computer Science — Distributed, Parallel, and Cluster Computing (cs.DC)
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Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- b24f95dbd6feac1d3d45a5bb8286a1df05ce79703c9d6a3d24d241f253a2e63d
- Enrichment time
- 2026-06-03T08:52:24Z
- AI-assisted enrichment
- Yes
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