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In this report we demonstrate the potential utility of resource allocation management systems that use virtual machine technology for sharing parallel computing resources among competing jobs. We formalize the resource allocation problem…

分布式、并行与集群计算 · 计算机科学 2010-06-29 Mark Stillwell , David Schanzenbach , Frédéric Vivien , Henri Casanova

In this paper, we study a data caching problem in the cloud environment, where multiple frequently co-utilised data items could be packed as a single item being transferred to serve a sequence of data requests dynamically with reduced cost.…

数据结构与算法 · 计算机科学 2022-08-08 Jiashu Wu , Hao Dai , Yang Wang , Yong Zhang , Dong Huang , Chengzhong Xu

Cloud elasticity - the ability to use as much resources as needed at any given time - and low cost - a user pays only for the resources it consumes - represent solid incentives for many organizations to migrate some of their computational…

分布式、并行与集群计算 · 计算机科学 2013-07-15 Ashkan Paya , Dan C. Marinescu

Cloud computing, offering on-demand access to computing resources through the Internet and the pay-as-you-go model, has marked the last decade with its three main service models; Infrastructure as a Service (IaaS), Platform as a Service…

网络与互联网体系结构 · 计算机科学 2023-12-29 Berat Can Senel , Maxime Mouchet , Justin Cappos , Olivier Fourmaux , Timur Friedman , Rick McGeer

Elasticity is one of key features of cloud computing. Elasticity allows Software as a Service (SaaS) applications' provider to reduce cost of running applications. In large SaaS applications that are developed using service-oriented…

分布式、并行与集群计算 · 计算机科学 2017-02-07 Ashraf A. Shahin

Design and architecture of cloud storage system plays a vital role in cloud computing infrastructure in order to improve the storage capacity as well as cost effectiveness. Usually cloud storage system provides users to efficient storage…

分布式、并行与集群计算 · 计算机科学 2011-12-12 Tin Tin Yee , Thinn Thu Naing

Linux containers have gained high popularity in recent times. This popularity is significantly due to various advantages of containers over Virtual Machines (VM). The containers are lightweight, occupy lesser storage, have fast boot-up…

分布式、并行与集群计算 · 计算机科学 2020-09-21 Akshay Dhumal , Dharanipragada Janakiram

Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of…

网络与互联网体系结构 · 计算机科学 2024-08-15 Peiyuan Guan , Chen Chen , Ziru Chen , Lin X. Cai , Xing Hao , Amir Taherkordi

Scalability is an important characteristic of cloud computing. With scalability, cost is minimized by provisioning and releasing resources according to demand. Most of current Infrastructure as a Service (IaaS) providers deliver…

分布式、并行与集群计算 · 计算机科学 2017-01-13 Ashraf A. Shahin

Scheduling Bag-of-Tasks (BoT) applications on the cloud can be more challenging than grid and cluster environ- ments. This is because a user may have a budgetary constraint or a deadline for executing the BoT application in order to keep…

分布式、并行与集群计算 · 计算机科学 2016-11-15 Long Thai , Blesson Varghese , Adam Barker

The modern datacenter's computing capabilities have far outstripped the applications running within and have become a hidden cost of doing business due to how software is architected and deployed. Resources are over-allocated to monolithic…

分布式、并行与集群计算 · 计算机科学 2022-08-31 Aos Mulahuwaish , Shane Korbel , Basheer Qolomany

Cloud Computing is the latest blooming technology in the era of Computer Science and Information Technology domain. There is an enormous pool of data centres, which are termed as Clouds where the services and associated data are being…

分布式、并行与集群计算 · 计算机科学 2014-09-30 Nallakumar R. , Sruthi Priya K. S

Cloud computing is an emerging technology in distributed computing which facilitates pay per model as per user demand and requirement.Cloud consist of a collection of virtual machine which includes both computational and storage facility.…

分布式、并行与集群计算 · 计算机科学 2014-04-09 Dr. Amit Agarwal , Saloni Jain

Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on edge AI for…

This paper explores the role of energy-awareness strategies into the deployment of applications across heterogeneous Edge-Cloud infrastructures. It proposes methods to inject into existing scheduling approaches energy metrics at a…

网络与互联网体系结构 · 计算机科学 2025-11-13 Dalal Ali , Rute C. Sofia

Service-oriented workflows are typically executed using a centralised orchestration approach that presents significant scalability challenges. These challenges include the consumption of network bandwidth, degradation of performance, and…

分布式、并行与集群计算 · 计算机科学 2013-11-11 Ward Jaradat , Alan Dearle , Adam Barker

In the conventional cloud service model, computing resources are allocated for tenants on a pay-per-use basis. However, the performance of applications that communicate inside this network is unpredictable because network resources are not…

网络与互联网体系结构 · 计算机科学 2018-10-09 Feras Fattohi

Companies are rushing to deliver their services and solutions through the cloud. The scheduling process is very critical in reducing delays. Scheduling also has a role in accessing resources without excessive waiting time. All this in…

分布式、并行与集群计算 · 计算机科学 2022-01-28 M A El-Dosuky , Gamal H Eladl

Aiming at analyzing performance in cloud computing, some unpredictable perturbations which may lead to performance downgrade are essential factors that should not be neglected. To avoid performance downgrade in cloud computing system, it is…

分布式、并行与集群计算 · 计算机科学 2023-11-30 Jiaxin Zhou , Siyi Chen , Haiyang Kuang

Edge computing seeks to enable applications with strict latency requirements by utilizing compute resources deployed closer to the users. The diverse, dynamic, and constrained nature of edge infrastructures necessitates a flexible…

分布式、并行与集群计算 · 计算机科学 2022-07-05 Giovanni Bartolomeo , Mehdi Yosofie , Simon Bäurle , Oliver Haluszczynski , Nitinder Mohan , Jörg Ott