Soft Actor-Critic Request Redirection for Quality Control in Green Multimedia Content Distribution

IF 2.5 4区 计算机科学 Q3 TELECOMMUNICATIONS
Pejman Goudarzi, Jaime Lloret
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引用次数: 0

Abstract

Nowadays, network resource limitations which are resulted from the increasing interest of greedy users for streaming video services, lead the network operators to use multimedia content distribution/delivery network (CDN) for distribution of user requests to the network edges and hence optimally use their resources. Due to the stochastic and uncertain nature of user request distributions and green energy suppliers (wind, solar, etc.), developing an optimal request redirection methodology that takes into account both maximizing total users' quality of experience (QoE) and energy cost minimization is a challenging issue. In this paper, a model-free soft actor-critic reinforcement learning algorithm has been developed for QoE enhancement of smart grid-enabled (green) content distribution networks. Contrary to the traditional CDNs, the achieved optimal request redirection policy, while maximizing the total QoE of the system, may redirect the users of a regional CDN point of presence to other (non-regional) PoPs due to real-time energy management mechanism associated with energy cost optimization constraints. We have performed extensive simulations on real electricity pricing data for validating the effectiveness of the proposed method and have compared it with similar approaches. The experimental results show that the proposed intelligent request routing method while preserving the same order of computational complexity, can achieve the energy cost savings up to 65% and improve the average total QoE of CDN users in comparison with similar methods.

Abstract Image

用于绿色多媒体内容分发质量控制的软代理-批评请求重定向
如今,由于贪婪的用户对流媒体视频服务的兴趣与日俱增,导致网络资源有限,网络运营商不得不使用多媒体内容分发/交付网络(CDN)将用户请求分发到网络边缘,从而优化资源利用。由于用户请求分布和绿色能源供应商(风能、太阳能等)的随机性和不确定性,开发一种既能最大限度提高用户体验质量(QoE)又能最小化能源成本的最佳请求重定向方法是一个具有挑战性的问题。本文为智能电网(绿色)内容分发网络的 QoE 增强开发了一种无模型软行为批判强化学习算法。与传统的 CDN 不同,在最大化系统总 QoE 的同时,由于与能源成本优化约束相关的实时能源管理机制,所实现的最优请求重定向策略可能会将区域 CDN 存在点的用户重定向到其他(非区域)PoP。我们对真实电价数据进行了大量模拟,以验证所提方法的有效性,并将其与类似方法进行了比较。实验结果表明,与同类方法相比,所提出的智能请求路由方法在保持相同计算复杂度的前提下,可实现高达 65% 的能源成本节约,并改善 CDN 用户的平均总 QoE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.90
自引率
13.90%
发文量
249
期刊介绍: ransactions on Emerging Telecommunications Technologies (ETT), formerly known as European Transactions on Telecommunications (ETT), has the following aims: - to attract cutting-edge publications from leading researchers and research groups around the world - to become a highly cited source of timely research findings in emerging fields of telecommunications - to limit revision and publication cycles to a few months and thus significantly increase attractiveness to publish - to become the leading journal for publishing the latest developments in telecommunications
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