Edge AI workloads demand low-latency, privacy-compliant storage. CATER delivers, using policy-driven placement to optimize energy, latency, and compliance. Tested on real edge clusters, it cuts data movement by 61%. 🌟 Follow us on LinkedIn! Check the updates from the…
Edge storage systems must minimize active nodes while respecting collocation, hardware, and privacy constraints. Our CATER framework achieves this with a hybrid optimization-heuristic approach, reducing energy consumption and data movement by up to 61%. 🌟 Follow us on LinkedIn! …
Edge computing demands dynamic, constraint-aware data placement. CATER, our policy-driven framework, integrates with Apache Ozone to optimize storage while respecting GDPR, hardware compatibility, and collocation restrictions. The result? 23% fewer active nodes and 100% constraint compliance. 🌟 Follow us on…
🚀 Launching September with CLEVER innovations! CATER, our policy-based data placement framework, is transforming how data flows across the edge-cloud continuum. With GDPR compliance, privacy safeguards, and energy efficiency at its core, CATER is paving the way for sustainable edge…
CATER — a policy-based, constraint-aware data placement framework tailored for the edge-cloud continuum. Traditional storage solutions fail to handle the complex demands of edge computing: heterogeneous nodes, GDPR compliance, privacy isolation, and energy-efficient storage. CATER addresses these challenges head-on: ✅…
