Concept: Cloud Computing and Resource Management
Adaptive CPU frequency scaling for energy-efficient and sustainable edge computing under renewable energy uncertainty
Optimizing CPU performance on renewable-powered edge servers using machine learning
Replay-as-a-Service reduces tail latency in storage-disaggregated databases
Reducing latency delays in cloud database systems through distributed log replay
CXL-SpecKV: A Disaggregated FPGA Speculative KV-Cache for Datacenter LLM Serving
Offloading memory to remote accelerators improves LLM inference speed and reduces costs
Telemetry-guided multi-cloud storage resists reconstruction
Dynamic fragmentation and encryption across multiple cloud providers with local backup protection
Enhanced grey wolf optimization improved cloud load balancing
Algorithm improves cloud computing resource distribution and workload balancing
PAT: Accelerating LLM Decoding via P refix- A ware A t tention with Resource Efficient Multi-Tile Kernel
Accelerating language model inference by reusing shared prompt cache across concurrent requests
STCC middleware evaluated for Cassandra consistency trade-offs
Adaptive consistency tuning for Cassandra clusters with energy and performance analysis
Queueing model reduces energy use in ternary optical computers
Energy-efficient scheduling for optical computers using queuing theory
Proactive VM consolidation cuts energy use and SLA violations
Predicting server resource needs to cut energy costs while maintaining service quality
Hybrid deep learning improved edge-cloud task scheduling in simulation
Smart task scheduling for edge-cloud systems using deep learning
