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Related papers: Location, Location, Location: Exploring Amazon EC2…

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In Amazon EC2, cloud resources are sold through a combination of an on-demand market, in which customers buy resources at a fixed price, and a spot market, in which customers bid for an uncertain supply of excess resources. Standard market…

Computer Science and Game Theory · Computer Science 2016-12-20 Darrell Hoy , Nicole Immorlica , Brendan Lucier

This paper addresses the challenge of deadline-aware online scheduling for jobs in hybrid cloud environments, where jobs may run on either cost-effective but unreliable spot instances or more expensive on-demand instances, under hard…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-22 Neelkamal Bhuyan , Randeep Bhatia , Murali Kodialam , TV Lakshman

AI batch jobs such as model training, inference pipelines, and data analytics require substantial GPU resources and often need to finish before a deadline. Spot instances offer 3-10x lower cost than on-demand instances, but their…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-13 Zhifei Li , Tian Xia , Ziming Mao , Zihan Zhou , Ethan J. Jackson , Jamison Kerney , Zhanghao Wu , Pratik Mishra , Yi Xu , Yifan Qiao , Scott Shenker , Ion Stoica

Spot instances offer significant cost savings of up to 90% over on-demand prices, making them an attractive resource for large-scale computing workloads. However, understanding their availability dynamics is essential for building systems…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-28 Kyumin Kim , Moohyun Song , Taeyoon Kim , Kyungyong Lee

Microservices architecture, known for its agility and efficiency, is an ideal framework for cloud-based software development and deployment. When integrated with containerization and orchestration systems, resource management becomes more…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-10 Dasith Edirisinghe , Kavinda Rajapakse , Pasindu Abeysinghe , Sunimal Rathnayake

This case study illustrates the potential benefits and risks associated with the migration of an IT system in the oil & gas industry from an in-house data center to Amazon EC2 from a broad variety of stakeholder perspectives across the…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-18 Ali Khajeh-Hosseini , David Greenwood , Ian Sommerville

The spot pricing scheme has been considered to be resource-efficient for providers and cost-effective for consumers in the Cloud market. Nevertheless, unlike the static and straightforward strategies of trading on-demand and reserved Cloud…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-08-07 Zheng Li , William Tarneberg , Maria Kihl , Anders Robertsson

This paper aims to answer the question: Can deep learning models be cost-efficiently trained on a global market of spot VMs spanning different data centers and cloud providers? To provide guidance, we extensively evaluate the cost and…

Machine Learning · Computer Science 2024-06-04 Alexander Erben , Ruben Mayer , Hans-Arno Jacobsen

We study the problem of scheduling delay-sensitive jobs over spot and on-demand cloud instances to minimize average cost while meeting an average delay constraint. Jobs arrive as a general stochastic process, and incur different costs based…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-21 Neelkamal Bhuyan , Randeep Bhatia , Murali Kodialam , TV Lakshman

The increasing reliance on dynamic pricing models, such as spot instances, in public cloud environments presents new challenges for workload scheduling and reliability. While these models offer cost advantages, they introduce volatility and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-25 Christoph Goldgruber , Benedikt Pittl , Erich Schikuta

The proliferation of commercial cloud computing providers has generated significant interest in the scientific computing community. Much recent research has attempted to determine the benefits and drawbacks of cloud computing for scientific…

Instrumentation and Methods for Astrophysics · Physics 2016-11-15 Gideon Juve , Ewa Deelman , Karan Vahi , Gaurang Mehta , Bruce Berriman , Benjamin P. Berman , Phil Maechling

As foundation models grow in size, fine-tuning them becomes increasingly expensive. While GPU spot instances offer a low-cost alternative to on-demand resources, their volatile prices and availability make deadline-aware scheduling…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-25 Linggao Kong , Yuedong Xu , Lei Jiao , Chuan Xu

Deploying applications across the computing continuum requires selecting infrastructure nodes from geographically distributed and heterogeneous environments while satisfying constraints (e.g., performance, location). This decision problem…

Cloud computing is a powerful new technology that is widely used in the business world. Recently, we have been investigating the benefits it offers to scientific computing. We have used three workflow applications to compare the performance…

Instrumentation and Methods for Astrophysics · Physics 2015-03-17 G. Bruce Berriman , Ewa Deelman , Gideon Juve , Moira Regelson , Peter Plavchan

Today, static cloud markets where consumers purchase services directly from providers are dominating. Thus, consumers neither negotiate the price nor the characteristics of the service. In recent years, providers have adopted more dynamic…

Computer Science and Game Theory · Computer Science 2025-07-15 Benedikt Pittl , Werner Mach , Erich Schikuta

Cloud storage is fast securing its role as a major repository for both consumers and business customers. Many companies now offer storage solutions, sometimes for free for limited amounts of capacity. We have surveyed the pricing plans of a…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-07-26 Loretta Mastroeni , Maurizio Naldi

Cloud users aim to minimize cost while maximizing performance by selecting the most suitable instance types for their workloads. To reduce expenses, spot instances have been widely adopted due to their steep discounts compared to on-demand…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-28 Taeyoon Kim , Kyumin Kim , Enrique Molina-Giménez , Pedro García-López , Kyungyong Lee

When orchestrating highly distributed and data-intensive Web service workflows the geographical placement of the orchestration engine can greatly affect the overall performance of a workflow. We present CloudForecast: a Web service…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-23 Michael Luckeneder , Adam Barker

Cloud computing has become the cornerstone of modern IT infrastructure, offering a wide range of general-purpose instances optimized for diverse workloads. This paper provides a comparative analysis of cost and performance for…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-05 Jay Tharwani , Arnab A Purkayastha

By acquiring cloud-like capacities at the edge of a network, edge computing is expected to significantly improve user experience. In this paper, we formulate a hybrid edge-cloud computing system where an edge device with limited local…

Information Theory · Computer Science 2020-01-27 Thinh Quang Dinh , Ben Liang , Tony Q. S. Quek , Hyundong Shin