# A Survey on Video Big Data Analytics: Architecture, Technologies, and Open Research Challenges
## 4 ViMindXAI: A Scalable and Cognitive AI Platform for VBDA
### Layered Architecture and Functional Components
#### 4.2.2 Data Infrastructure Layer (DIL)  
The DILconstitutes a central component of the ViMindXAI architecture, offering a scalable and intelligent foundation for storing, organizing, and retrieving large-scale video data. Tailored to the unique requirements of VBDA, this layer combines cloud and on-premises storage with real-time metadata indexing and AI-enhanced retrieval pipelines, thereby enabling high-throughput, low-latency, and semantically aware search capabilities. The hardware foundation supporting this layer includes cloud-native storage services such as AWS EC2/S3, GCP Cloud Storage, on-premises clusters with NVMe SSD arrays for high-speed access, and GPU-accelerated nodes such as NVIDIA A100, T4 for semantic indexing and batch analytics. RAID configurations and hardware-assisted encryption modules are used to ensure data redundancy, fault tolerance, and security at rest. The DIL is composed of three main modules: AI-Driven Storage Orchestration, Data Lakehouse, and Semantic Indexing. **(1) AI-Driven Storage Orchestration**  
This module is a core component of the ViMindXAI platform, designed to manage large-scale video data intelligently, efficiently, and in compliance with privacy regulations. It orchestrates data storage across edge, cloud, and on-premise systems, ensuring high availability, scalability, and regulatory alignment in dynamic VBDA environments. This module comprises three tightly integrated layers: Big Data Storage, AI-driven Storage Optimization, and Privacy-Aware Synchronization. * **Big Data Storage**: establishes a hybrid, fault-tolerant infrastructure for ingesting and managing video data across diverse environments. Cloud services like Amazon S3 offer elastic scalability, while on-premise platforms such as MinIO, and Hadoop HDFS ensure secure, policy-compliant storage. At the edge, Ceph supports low-latency buffering and ingestion. Efficient video encoding formats such as MPEG-4, H.264, and H.265 are integrated into the pipeline to reduce transmission load and long-term storage costs, especially in surveillance and healthcare contexts [150]. Adaptive compression is employed to align bitrate with network and storage constraints [151]. This multi-layered storage backbone supports lifecycle management, distributed retention, and efficient data provisioning for downstream analytics within Lakehouse architectures. * **AI-Based Storage Optimization**: leverages reinforcement learning to automate storage tiering decisions, guided by observed usage patterns and anticipated access frequency. This enables dynamic tiering across hot, warm, and cold layers, balancing performance and cost-efficiency. High-speed caching with Redis accelerates access to frequently queried data, while observability tools like Grafana, MLFlow, and Prometheus monitor system performance and guide optimization. To enable intelligent storage tiering, we integrate a Deep Q-Network (DQN)-based reinforcement learning agent [152]. The agent interacts with the environment to learn optimal retention policies, adapting dynamically to changes in data access frequency, latency requirements, and cost performance trade-offs. This allows ViMindXAI to proactively allocate resources across hot, warm, and cold tiers under varying workload conditions. * **Privacy-Aware Synchronization:** facilitates secure and regulation-compliant data transfers across distributed environments, maintaining confidentiality and integrity in multi-tenant deployments. It employs federated synchronization to preserve data locality and prevent unnecessary exposure of sensitive content. Containerized deployment via Docker and Kubernetes ensures portability and scalability, while Apache Zookeeper and secure API gateways manage access control and coordination in multi-tenant setups. This layer is instrumental in ensuring compliance with data protection regulations, including GDPR and HIPAA.