Serverless Cloud

Serverless cloud computing aims to provide on-demand, scalable computing resources without the need for users to manage underlying infrastructure. Current research focuses on optimizing performance and cost-efficiency, particularly addressing challenges like cold starts (delays in function execution) and stragglers (slow-performing clients in distributed tasks) using techniques such as temporal convolutional networks and asynchronous training strategies tailored to serverless environments. This approach is significantly impacting various fields, including data analytics (via natural language interfaces and flexible service levels), machine learning (through efficient federated learning frameworks), and cybersecurity (with applications in email forensics and threat detection).