Related papers: Konflux: Optimized Function Fusion for Serverless …
Function-as-a-Service (FaaS) has recently emerged to reduce the deployment cost of running cloud applications compared to Infrastructure-as-a-Service (IaaS). FaaS follows a serverless 'pay-as-you-go' computing model; it comes at a higher…
The serverless computing model has evolved as one of the key solutions in the cloud for fast autoscaling and capacity planning. In edge computing environments, however, the serverless model is challenged by the system heterogeneity and…
Since the appearance of Amazon Lambda in 2014, all major cloud providers have embraced the Function as a Service (FaaS) model, because of its enormous potential for a wide variety of applications. As expected (and also desired), the…
Serverless computing, in particular the Function-as-a-Service (FaaS) execution model, has recently shown to be effective for running large-scale computations. However, little attention has been paid to highly-parallel applications with…
Quantum computing has the potential to solve complex problems beyond the capabilities of classical computers. However, its practical use is currently limited due to early-stage quantum software engineering and the constraints of Noisy…
Following the increasing interest and adoption of FaaS systems, benchmarking frameworks for determining non-functional properties have also emerged. While existing (microbenchmark) frameworks only evaluate single aspects of FaaS platforms,…
Developers increasingly use function-as-a-service (FaaS) platforms for data-centric applications that perform low-latency and transactional operations on data, such as for microservices or web serving. Unfortunately, existing FaaS platforms…
Federated Learning (FL) is emerging as a promising technology to build machine learning models in a decentralized, privacy-preserving fashion. Indeed, FL enables local training on user devices, avoiding user data to be transferred to…
In FaaS, users invoke remote functions, which encapsulate service(s). These functions typically need to remotely access a persistent state via external services: this makes the paradigm less attractive in edge systems, especially for IoT…
Automatic network management strategies have become paramount for meeting the needs of innovative real-time and data-intensive applications, such as in the Internet of Things. However, meeting the ever-growing and fluctuating demands for…
Modern scientific applications are increasingly decomposable into individual functions that may be deployed across distributed and diverse cyberinfrastructure such as supercomputers, clouds, and accelerators. Such applications call for new…
The function-as-a-service (FaaS) paradigm is envisioned as the next generation of cloud computing systems that mitigate the burden for cloud-native application developers by abstracting them from cloud resource management. However, it does…
Serverless computing has made it easier than ever to deploy applications over scalable cloud resources, all the while driving higher utilization for cloud providers. While this technique has worked well for easily divisible resources like…
Current serverless offerings give users a limited degree of flexibility for configuring the resources allocated to their function invocations by either coupling memory and CPU resources together or providing no knobs at all. These…
We present a framework for scheduling multifunction serverless applications over a hybrid public-private cloud. A set of serverless jobs is input as a batch, and the objective is to schedule function executions over the hybrid platform to…
Due to the popularity of the FaaS programming model, there is now a wide variety of commercial and open-source FaaS systems. Hence, for comparison of different FaaS systems and their configuration options, FaaS application developers rely…
Serverless computing, commonly offered as Function-as-a-Service, was initially designed for small, lean applications. However, there has been an increasing desire to run larger, more complex applications (what we call bulky applications) in…
Along with the wide-adoption of Serverless Computing, more and more applications are developed and deployed on cloud platforms. Major cloud providers present their serverless workflow services to orchestrate serverless functions, making it…
Existing serverless workflow orchestration systems are predominantly designed for a single-cloud FaaS system, leading to vendor lock-in. This restricts performance optimization, cost reduction, and availability of applications. However,…
Serverless computing has emerged as a prominent paradigm, with a significant adoption rate among cloud customers. While this model offers advantages such as abstraction from the deployment and resource scheduling, it also poses limitations…