RUSH: Rule-Based Scheduling for Low-Latency Serverless Computing

Serverless computing abstracts server management, enabling developers to focus on application logic while benefiting from automatic scaling and pay-per-use pricing. However, dynamic workloads pose challenges in resource allocation and response time optimization. Response time is a critical performance metric in serverless environments, especially for latency-sensitive applications, where inefficient scheduling can degrade user experience and system efficiency. This paper proposes RUSH (Rule-based Scheduling for Low-Latency Serverless Computing), a lightweight and adaptive scheduling framework designed to reduce cold starts and execution delays. RUSH employs a set of predefined rules that consider system state, resource availability, and timeout thresholds to make proactive, latency-aware scheduling decisions. We implement and evaluate RUSH on a real-world serverless application that generates emoji meanings. Experimental results demonstrate that RUSH consistently outperforms First-Come-First-Served (FCFS), Random Scheduling, and Profaastinate, achieving ≈ 33% reduction in average execution time.