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
Risk-aware resilient cloud orchestration under correlated faults using adaptive dual-regime search with self-healing control
Cloud resource allocation under simultaneous hardware faults and unpredictable demand spikes
Reducing Tail Latency in Storage-Disaggregated Database Systems
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
AI-Driven Hybrid Architecture for Secure, Reconstruction-Resistant Multi-Cloud Storage
Dynamic fragmentation and encryption across multiple cloud providers with local backup protection
A proposed enhanced dynamic grey wolf optimization algorithm for 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
Middleware-enforced Timed Causal Consistency for Apache Cassandra: An energy–performance–consistency evaluation against static consistency levels using YCSB
Adaptive consistency tuning for Cassandra clusters with energy and performance analysis
Performance and energy consumption optimization of ternary optical computers based on the M/G/1 queuing model
Energy-efficient scheduling for optical computers using queuing theory
A proactive virtual machine consolidation framework based on multi-dimensional workload awareness and deep reinforcement learning
Predicting server resource needs to cut energy costs while maintaining service quality
