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Serverless computing has become a new trending paradigm in cloud computing, allowing developers to focus on the development of core application logic and rapidly construct the prototype via the composition of independent functions. With the…

Software Engineering · Computer Science 2023-02-07 Jinfeng Wen , Yi Liu , Zhenpeng Chen , Junkai Chen , Yun Ma

A growing number of critical workflow applications leverage a streamlined edge-hub-cloud architecture, which diverges from the conventional edge computing paradigm. An edge device, in collaboration with a hub device and a cloud server,…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-23 Andreas Kouloumpris , Georgios L. Stavrinides , Maria K. Michael , Theocharis Theocharides

Cloud computing environments often have to deal with random-arrival computational workloads that vary in resource requirements and demand high Quality of Service (QoS) obligations. It is typical that a Service-Level-Agreement (SLA) is…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-04-21 Husam Suleiman , Otman Basir

This paper presents a multiagent approach as a paradigm for scheduling parallel jobs in a parallel system. Scheduling parallel jobs is performed as a means to balance the load of a system in order to improve the performance of a parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-29 Jaderick P. Pabico

Despite existing work in machine learning inference serving, ease-of-use and cost efficiency remain challenges at large scales. Developers must manually search through thousands of model-variants -- versions of already-trained models that…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-07 Francisco Romero , Qian Li , Neeraja J. Yadwadkar , Christos Kozyrakis

We propose a novel job scheduling approach for homogeneous cluster computing platforms. Its key feature is the use of virtual machine technology to share fractional node resources in a precise and controlled manner. Other VM-based…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-06-27 Henri Casanova , Mark Stillwell , Frédéric Vivien

We propose an approach to utilize idle computational resources of supercomputers. The idea is to maintain an additional queue of low-priority non-parallel jobs and execute them in containers, using container migration tools to break the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-04 Julia Dubenskaya , Stanislav Polyakov

In this paper, we study the market-oriented online bi-objective service scheduling problem for pleasingly parallel jobs with variable resources in cloud environments, from the perspective of SaaS (Software-as-as-Service) providers who…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-18 Bingbing Zheng , Li Pan , Shijun Liu

Serverless computing is a popular cloud deployment paradigm where developers implement applications as workflows of functions that invoke each other. Cloud providers automatically scale function instances on demand and forward workflow…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-09 Dmitrii Ustiugov , Shyam Jesalpura , Mert Bora Alper , Michal Baczun , Rustem Feyzkhanov , Edouard Bugnion , Boris Grot , Marios Kogias

Serverless functions are a cloud computing paradigm where the provider takes care of resource management tasks such as resource provisioning, deployment, and auto-scaling. The only resource management task that developers are still in…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-08 Simon Eismann , Long Bui , Johannes Grohmann , Cristina L. Abad , Nikolas Herbst , Samuel Kounev

Optimising the execution of Bag-of-Tasks (BoT) applications on the cloud is a hard problem due to the trade- offs between performance and monetary cost. The problem can be further complicated when multiple BoT applications need to be…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-15 Long Thai , Blesson Varghese , Adam Barker

Traditionally, on-demand, rigid, and malleable applications have been scheduled and executed on separate systems. The ever-growing workload demands and rapidly developing HPC infrastructure trigger the interest of converging these…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-14 Yuping Fan , Paul Rich , William Allcock , Michael Papka , Zhiling Lan

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…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-26 Larissa Schmid , Marcin Copik , Alexandru Calotoiu , Laurin Brandner , Anne Koziolek , Torsten Hoefler

Cloud computing has been developed as one of the prominent paradigm for providing on demand resources to the end user based on signed service level agreement and pay as use model. Cloud computing provides resources using multitenant…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-09 Rajinder Sandhu , Adel Nadjaran Toosi , Rajkumar Buyya

To support parallelizable serverless workflows in applications like media processing, we have prototyped a distributed scheduler called Raptor that reduces both the end-to-end delay time and failure rate of parallelizable serverless…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-16 Kevin Exton , Maria Read

Serverless query processing has become increasingly popular due to its auto-scaling, high elasticity, and pay-as-you-go pricing. It allows cloud data warehouse (or lakehouse) users to focus on data analysis without the burden of managing…

Databases · Computer Science 2024-12-24 Haoqiong Bian , Dongyang Geng , Yunpeng Chai , Anastasia Ailamaki

We consider robust resource allocation of services in Clouds. More specifically, we consider the case of a large public or private Cloud platform that runs a relatively small set of large and independent services. These services are…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-22 Olivier Beaumont , Lionel Eyraud-Dubois , Paul Renaud-Goud

Serverless computing platforms currently rely on basic pricing schemes that are static and do not reflect customer feedback. This leads to significant inefficiencies from a total utility perspective. As one of the fastest-growing cloud…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-26 Vipul Gupta , Soham Phade , Thomas Courtade , Kannan Ramchandran

The advent of serverless computing has revolutionized the landscape of cloud computing, offering a new paradigm that enables developers to focus solely on their applications rather than managing and provisioning the underlying…

Software Engineering · Computer Science 2023-11-23 Muhammad Hamza , Muhammad Azeem Akbar , Rafael Capilla

As more and more service providers choose Cloud platforms, which is provided by third party resource providers, resource providers needs to provision resources for heterogeneous workloads in different Cloud scenarios. Taking into account…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-07-22 Jianfeng Zhan , Lei Wang , Weisong Shi , Shimin Gong , Xiutao Zang