Serverless edge computing decreases unnecessary resource usage on end devices with
limited processing power and storage capacity. Despite its benefits, serverless edge …

Edge computing is one of the technological areas currently considered among the most
promising for the implementation of many types of applications. In particular, IoT-type …

Serverless computing platforms currently provide application developers with two ways to
control their services' resource usage cost: resource usage-based and resource quota …

The container resource autoscaling techniques offer scalability and continuity for
microservices operating in cloud-native computing environments. However, they manage …

The rapid expansion of cloud data centers, driven by the increasing demand for diverse user
services, has escalated energy consumption and greenhouse gas emissions, posed severe …

The advent of artificial intelligence (AI) has driven an emergence in applications demanding
online responses to immense amounts of data. Typically, the cloud-based deployment of …

Edge serverless computing represents a rapidly advancing technological paradigm with
various applications across multiple computing domains. However, resource constraints and …

To efficiently manage serverless computing platforms, a key aspect is the auto-scaling of
services, ie, the set of computational resources allocated to a service adapts over time as a …

Serverless computing is a new cloud computing model suitable for providing services in
both large cloud and edge clusters. In edge clusters, the autoscaling functions play a key …

Abstract Cloud Function-as-a-Service (FaaS) systems offer statistical guarantees and cannot
meet the deadlines of bursty, real-time applications. To address this limitation, we propose …