Shashikant Ilager

Collaborative edge-cloud LLM inference can achieve 275% higher throughput by dynamically synchronizing heterogeneous requests to batch their common cloud-side suffix.

Cloud computing's carbon footprint could be significantly reduced without sacrificing latency, but existing strategies fall short of this goal.

Achieving an 80% reduction in low-latency VM offloading while managing only an 11.97% worst-case latency increase could revolutionize how we integrate low-latency applications into renewable energy systems.

Lightweight LLMs like Gemini 2.0 and GPT-3.5 can extract key metadata from cloud incident reports with surprisingly high accuracy (75-95%), offering a cost-effective alternative to larger models.