Abstract:

Today, Function-as-a-Service is the most promising concept of serverless cloud computing. It makes possible for developers to focus on application development without any system management effort: FaaS ensures resource allocation, fast response time, schedulability, scalability, resiliency, and upgrad- ability. Applications of 5G, IoT, and Industry 4.0 raise the idea to open cloud-edge computing infrastructures for time-critical applications too, i.e., there is a strong desire to pose real-time requirements for computing systems like FaaS. However, multi- node systems make real-time scheduling significantly complex since guaranteeing real-time task execution is challenging even on one computing node with multi-core processors. In this paper, we present an analytical model and a heuristic partitioning scheduling algorithm for a partitioned scheduling system suitable for real-time FaaS platforms of multi-node clusters. We present the architecture of the envisioned real-time FaaS platform, emphasize its benefits and the requirements for the underlying network and nodes, and survey the related work that could meet these demands.

Index Terms:

real-time scheduling, real-time cloud, real-time FaaS, partitioned scheduling, partitioned-EDF, heterogeneous multiprocessor, multi-node and multiprocessor system.