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This paper explores resource allocation in serverless cloud computing platforms and proposes an optimization approach for autoscaling systems. Serverless computing relieves users from resource management tasks, enabling focus on application…

分布式、并行与集群计算 · 计算机科学 2023-10-31 Harold Ship , Evgeny Shindin , Chen Wang , Diana Arroyo , Asser Tantawi

The cloud computing paradigm offers on-demand services over the Internet and supports a wide variety of applications. With the recent growth of Internet of Things (IoT) based applications the usage of cloud services is increasing…

分布式、并行与集群计算 · 计算机科学 2018-07-10 Sukhpal Singh Gill , Rajkumar Buyya

Serverless computing is increasingly popular because of its lower cost and easier deployment. Several cloud service providers (CSPs) offer serverless computing on their public clouds, but it may bring the vendor lock-in risk. To avoid this…

分布式、并行与集群计算 · 计算机科学 2021-06-08 Junfeng Li , Sameer G. Kulkarni , K. K. Ramakrishnan , Dan Li

Cloud infrastructure supports the efficient operation of data pipelines regarding requirements like cost, speed, and resource utilization. We present an integrated view of optimization opportunities for cloud-based data pipelines by…

分布式、并行与集群计算 · 计算机科学 2026-04-03 Johannes Jablonski , Georg-Daniel Schwarz , Philip Heltweg , Dirk Riehle

The pay-as-you-go model supported by existing cloud infrastructure providers is appealing to most application service providers to deliver their applications in the cloud. Within this context, elasticity of applications has become one of…

分布式、并行与集群计算 · 计算机科学 2015-11-17 Rui Han

The proliferation of sensors over the last years has generated large amounts of raw data, forming data streams that need to be processed. In many cases, cloud resources are used for such processing, exploiting their flexibility, but these…

分布式、并行与集群计算 · 计算机科学 2024-02-01 Rafael Tolosana-Calasanz , José Ángel Bañares , José-Manuel Colom

Serverless computing has attracted a broad range of applications due to its ease of use and resource elasticity. However, developing serverless applications often poses a dilemma -- relying on general-purpose serverless platforms can fall…

分布式、并行与集群计算 · 计算机科学 2025-07-17 Minchen Yu , Yinghao Ren , Jiamu Zhao , Jiaqi Li

Distributed communities of researchers rely increasingly on valuable, proprietary, or sensitive datasets. Given the growth of such data, especially in fields new to data-driven, computationally intensive research like the social sciences…

分布式、并行与集群计算 · 计算机科学 2016-10-19 Yadu N. Babuji , Kyle Chard , Aaron Gerow , Eamon Duede

Serverless computing has become a major trend among cloud providers. With serverless computing, developers fully delegate the task of managing the servers, dynamically allocating the required resources, as well as handling availability and…

分布式、并行与集群计算 · 计算机科学 2020-06-08 Pascal Maissen , Pascal Felber , Peter Kropf , Valerio Schiavoni

Serverless computing, also known as Functions-as-a-Service, is a recent paradigm aimed at simplifying the programming of cloud applications. The idea is that developers design applications in terms of functions, which are then deployed on a…

Serverless computing is an emerging cloud computing paradigm, being adopted to develop a wide range of software applications. It allows developers to focus on the application logic in the granularity of function, thereby freeing developers…

软件工程 · 计算机科学 2022-12-19 Jinfeng Wen , Zhenpeng Chen , Xin Jin , Xuanzhe Liu

As organizations increasingly rely on data-driven insights, the ability to run data intensive applications seamlessly across multiple cloud environments becomes critical for tapping into cloud innovations while complying with various…

分布式、并行与集群计算 · 计算机科学 2025-04-14 Vignesh Babu , Feng Lu , Haotian Wu , Cameron Moberg

Today cloud computing has become as a new concept for hosting and delivering different services over the Internet for big data solutions. Cloud computing is attractive to different business owners of both small and enterprise as it…

分布式、并行与集群计算 · 计算机科学 2013-08-06 Mehdi Bahrami

Autoscaling system can reconfigure cloud-based services and applications, through various configurations of cloud software and provisions of hardware resources, to adapt to the changing environment at runtime. Such a behavior offers the…

软件工程 · 计算机科学 2018-04-26 Tao Chen , Rami Bahsoon , Xin Yao

Serverless computing with cloud functions is quickly gaining adoption, but constrains programmers with its limited support for state management. We introduce a shared file system for cloud functions. It offers familiar POSIX semantics while…

分布式、并行与集群计算 · 计算机科学 2020-09-22 Johann Schleier-Smith , Leonhard Holz , Nathan Pemberton , Joseph M. Hellerstein

Web application providers have been migrating their applications to cloud data centers, attracted by the emerging cloud computing paradigm. One of the appealing features of the cloud is elasticity. It allows cloud users to acquire or…

分布式、并行与集群计算 · 计算机科学 2017-09-15 Chenhao Qu , Rodrigo N. Calheiros , Rajkumar Buyya

Cloud-enabled large-scale distributed systems orchestrate resources and services from various providers in order to deliver high-quality software solutions to the end users. The space and structure created by such technological advancements…

软件工程 · 计算机科学 2018-08-14 Andreea Buga , Sorana Tania Nemes , Atif Mashkoor

Recently, serverless computing has gained recognition as a leading cloud computing method. Providing a solution that does not require direct server and infrastructure management, this technology has addressed many traditional model problems…

分布式、并行与集群计算 · 计算机科学 2025-01-20 Mohsen Ghorbian , Mostafa Ghobaei-Arani

We consider how underused computing resources within an enterprise may be harnessed to improve utilization and create an elastic computing infrastructure. Most current cloud provision involves a data center model, in which clusters of…

分布式、并行与集群计算 · 计算机科学 2016-09-08 Graham Kirby , Alan Dearle , Angus Macdonald , Alvaro Fernandes

Transactional cloud applications such as payment, booking, reservation systems, and complex business workflows are currently being rewritten for deployment in the cloud. This migration to the cloud is happening mainly for reasons of cost…