实现云存储提供商利润最大化的在线定价和资源调度

IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Kyungtae Lee;Yeongjin Kim
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引用次数: 0

摘要

随着云对象存储服务(COSS)需求的增长,云对象存储服务提供商之间的竞争日益激烈。然而,商业COSS提供商提供的现有定价模式无法有效适应不断变化的客户需求和资源供应。因此,许多COSS提供商仍在努力应对利润最大化方面的运营挑战,例如定价策略、负载平衡、服务器调度和能源管理。本文提出了一种基于lyapunov -drift- -profit技术的时间依赖定价与调度方法(td - pn)。为了使COSS提供商的利润最大化,TD-PnS能够跨几个关键因素进行联合和动态决策,这些因素到目前为止已经单独处理:(i)服务定价,(ii) CPU时钟缩放和编码调度,(iii)网络调度,以及(iv)储能管理。我们提出了一个增强版本的TD-PnS,称为TD-PnS- adv,进一步改善其他方面,如系统稳定性。最后,通过利用真实数据集的跟踪驱动模拟,我们证明了与现有算法和定价模型相比,所提出的算法在利润最大化方面具有优越的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Pricing and Resource Scheduling for Profit Maximization of Cloud Storage Providers
There is increasing competition among cloud object storage service (COSS) providers as the demand for COSSs grows. However, existing pricing models offered by commercial COSS providers fail to effectively adapt to changing client demand and resource supply. Consequently, many COSS providers are still grappling with operational challenges in maximizing their profits, such as pricing policy, load balancing, server scheduling, and energy management. In this paper, we propose a novel approach called time-dependent pricing and scheduling ( TD-PnS ), which is based on the Lyapunov-drift-minus-profit technique. To maximize the profits of COSS providers, TD-PnS enables joint and dynamic decision-making across several key factors that have been dealt with separately so far: (i) service pricing, (ii) CPU clock scaling and encoding scheduling, (iii) network scheduling, and (iv) energy storage management. We propose an enhanced version of TD-PnS , called TD-PnS-Adv , further to improve other aspects, such as system stabilization. Finally, through trace-driven simulations utilizing a real dataset, we demonstrate the superior performance of the proposed algorithms compared to existing algorithms and pricing models in terms of profit maximization.
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来源期刊
IEEE Transactions on Cloud Computing
IEEE Transactions on Cloud Computing Computer Science-Software
CiteScore
9.40
自引率
6.20%
发文量
167
期刊介绍: The IEEE Transactions on Cloud Computing (TCC) is dedicated to the multidisciplinary field of cloud computing. It is committed to the publication of articles that present innovative research ideas, application results, and case studies in cloud computing, focusing on key technical issues related to theory, algorithms, systems, applications, and performance.
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