Adel N. Toosi , Bahman Javadi , Alexandru Iosup , Evgenia Smirni , Schahram Dustdar
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Serverless Computing for Next-generation Application Development
Serverless computing is a cloud computing model that abstracts server management, allowing developers to focus solely on writing code without concerns about the underlying infrastructure. This paradigm shift is transforming application development by reducing time to market, lowering costs, and enhancing scalability. In serverless computing, functions are event-driven and automatically scale in response to events such as data changes or user requests. Despite its advantages, serverless computing presents several research challenges, including managing state for ephemeral functions, mitigating cold start delays, optimizing function composition, debugging, efficient auto-scaling, resource management, and ensuring security and compliance. This special issue focused on addressing these challenges by promoting research on innovative solutions and exploring the potential of serverless computing in new application domains.
期刊介绍:
Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications.
Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration.
Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.