Function-as-a-Service (FaaS) allows developers to define, orchestrate and run modular event-based pieces of code on virtualised resources, without the burden of managing the underlying infrastructure nor the life-cycle of such pieces of code. Indeed, FaaS providers offer resource auto-provisioning, auto-scaling and pay-per-use billing at no costs for idle time. This makes it easy to scale running code and it represents an effective and increasingly adopted way to deliver software. This article aims at offering an overview of the existing literature in the field of next-gen FaaS from three different perspectives: (i) the definition of FaaS orchestrations, (ii) the execution of FaaS orchestrations in Fog computing environments, and (iii) the security of FaaS orchestrations. Our analysis identify trends and gaps in the literature, paving the way to further research on securing FaaS orchestrations in Fog computing landscapes.

The decision-making related to the placement of applications made from orchestrated serverless functions onto Cloud-Edge infrastructures is a challenging problem as it must consider functional and non-functional requirements. In this article, we propose a novel declarative methodology to determine the placement of FaaS orchestration onto Cloud-Edge resources while satisfying all the requirements of the FaaS orchestrations and relying on information-flow analyses and padding techniques to prevent information leaks through side channels. A motivating example from Augmented Reality is used to showcase the open-source declarative prototype implementing our proposal. Besides, the prototype is assessed via simulation to evaluate execution times, placement success rates and energy consumption.

Deploying Function-as-a-Service (FaaS) applications to resources in the Cloud-Edge continuum calls for suitable simulation environments to assess new proposals for managing those applications while accounting for their specificity, i.e. ephemeral deployment and orchestrated execution. Indeed, exploiting real infrastructures for extensive experiments, while considering heterogeneous nodes and different applications, is costly and time-consuming. In this article, we propose a novel open-source discrete-time simulator for the management (i.e. deployment and migration) of orchestrated FaaS in the Cloud-Edge continuum. It enables assessing customised management policies against varying infrastructure conditions. It collects data about execution time, energy consumption, and successes/failures of management operations. We illustrate the prototype at work over a lifelike case study.

Quantum computing is rapidly progressing from theoretical promise to practical implementation, offering significant computational advantages for tasks in optimization, simulation, cryptography, and machine learning. However, its integration into real-world software systems remains constrained by hardware fragility, platform heterogeneity, and the absence of robust software engineering practices. This paper introduces Service-Oriented Quantum (SOQ), a novel paradigm that reimagines quantum software systems through the lens of classical service-oriented computing. Unlike prior approaches such as Quantum Service-Oriented Computing (QSOC), which treat quantum capabilities as auxiliary components within classical systems, SOQ positions quantum services as autonomous, composable, and interoperable entities. We define the foundational principles of SOQ, propose a layered technology stack to support its realization, a reference architecture for defining quantum services based on the good implementation of a classical service, and identify the key research and engineering challenges that must be addressed, including interoperability, hybridity, pricing models, service abstractions, and workforce development. This approach is of vital importance for the advancement of quantum technology because it enables the scalable, modular, and interoperable integration of quantum computing into real-world software systems independently and without relying on a dedicated classical environment to manage quantum processing.

Placing applications composed as orchestrated serverless functions onto Cloud-loT infrastructures is a chal-lenging problem as it must consider hardware, software, network Quality of Service, and service interactions constraints. In this paper, we propose a novel declarative methodology that handles all of the above, also relying on information-flow analyses and padding techniques to prevent information leaks through side channels. A motivating use case from augmented reality is used to showcase the open-source prototype implementing our proposal.

Utility computing paradigms (e.g, Fog, Edge, Mist computing) allow application operators to deploy applications onto heterogeneous resources along the infrastructure continuum spanning from virtually unbounded datacenters to resource-constrained Edge and IoT devices. Application operators must suitably select infrastructure resources where to deploy at best the services that compose their applications, and then manage the application life-cycle across the infrastructure. We propose a new view of the Cloud-Edge continuum, where infrastructure providers lease tailored portions of the infrastructure, determined by taking into account the hardware and QoS requirements as well as the sustainability goals expressed by application operators. Most importantly, infrastructure providers offer the selected Cloud-Edge infrastructure portion as a single virtual infrastructure node that customers can exploit to deploy and manage their applications in a seamless way.