Tpram-kelly.7z -

The file refers to the research paper titled " Transformer-based performance prediction and proactive resource allocation for cloud-native microservices ," published in Cluster Computing in August 2025.

: Experimental results using the DeathStarBench benchmark showed that TPRAM can save at least 40.58% of CPU and 15.84% of memory resources while maintaining end-to-end Quality of Service (QoS). Accessing the Paper TpRam-Kelly.7z

: A preprint or abstract of the work is hosted on ResearchGate . The file refers to the research paper titled

: It employs Deep Deterministic Policy Gradient (DDPG) , a reinforcement learning technique, to dynamically adjust CPU, memory, and I/O disk allocation based on real-time requirements. a reinforcement learning technique

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