MIDDLEWARE

Analytical performance models have been shown very efficient in analyzing, predicting, and improving the performance of distributed computing systems. However, there is a lack of rigorous analytical models for analyzing the transient behaviour of ...

We are witnessing an increasing trend towards using Machine Learning (ML) based prediction systems, spanning across different application domains, including product recommendation systems, personal assistant devices, facial recognition, etc. These ...

Application software provisioning evolved from monolithic designs towards differently designed abstractions including serverless applications. The promise of that abstraction is that developers are free from infrastructural concerns such as instance ...

Serverless computing is a promising cloud execution model that significantly simplifies cloud users' operational concerns by offering features such as auto-scaling and a pay-as-you-go cost model. Consequently, serverless systems promise to provide an ...

Fully-managed cloud and Function-as-a-Service (FaaS) services allow the wide adoption of serverless computing for various cloud-native applications. Despite the many advantages that serverless computing provides, no direct connection support exists ...

Serverless computing is becoming more and more attractive for cloud solution architects and developers. This new computing paradigm relies on Function-as-a-Service (FaaS) platforms that enable deploying functions without being concerned with the ...

While much of the software running on today's serverless platforms is written in easily-analyzed high-level interpreted languages, many performance-conscious users choose to deploy their applications as container-encapsulated compiled binaries on ...

Serverless computing in the cloud, or functions as a service (FaaS), poses new and unique systems design challenges. Serverless offers improved programmability for customers, yet at the cost of increased design complexity for cloud providers. One such ...

Federated learning (FL) enables resource-constrained edge devices to learn a shared Machine Learning (ML) or Deep Neural Network (DNN) model, while keeping the training data local and providing privacy, security, and economic benefits. However, building ...

Scaling transparency means that applications can expand in scale without changes to the system structure or the application algorithms. Serverless Computing's inherent auto-scaling support and fast function launching is ideally suited to support scaling ...

This paper introduces a new primitive to serverless language runtimes called freshen. With freshen, developers or providers specify functionality to perform before a given function executes. This proactive technique allows for overheads associated with ...

To help better understand factors that impact performance on Function-as-a-Service (FaaS) platforms we have developed the Serverless Application Analytics Framework (SAAF). SAAF provides a reusable framework supporting multiple programming languages ...