A Hierarchical Optimized Resource Utilization based Content Placement (HORCP) model for cloud Content Delivery Networks (CDNs)

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
M. Sasikumar, P. Jesu Jayarin, F. Sangeetha Francelin Vinnarasi
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引用次数: 0

Abstract

Abstract Content Delivery Networks (CDNs) have grown in popularity as a result of the ongoing development of the Internet and its applications. The workload on streaming media service systems can be significantly decreased with the help of the cooperative edge-cloud computing architecture. In the traditional works, a different types of content placement and routing algorithms are developed for improving the content delivery of cloud systems with reduced delay and cost. But, the majority of existing algorithms facing complexities in terms of increased resource usage, ineffective delivery, and high system designing complexity. Therefore, the proposed work aims to develop a new framework, named as, Hierarchical Optimized Resource Utilization based Content Placement (HORCP) model for cloud CDNs. Here, the Chaotic Krill Herd Optimization (CKHO) method is used to optimize the resource usage for content placement. Then, a Hierarchical Probability Routing (HPR) model is employed to enable a dependable end-to-end data transmission with an optimized routing path. The performance of the proposed HORCP model is validated and compared by using several performance metrics. The obtained results are also compared with current state-of-the-art methodologies in order to show the superiority of the proposed HORCP model. By using the HORCP mechanism, the overall memory usage of the network is reduced to 80%, CPU usage is reduced to 20%, response is minimized to 2 s, and total congestion cost with respect to the network load level is reduced to 100.
基于分层优化资源利用的云内容分发网络(cdn)内容放置(HORCP)模型
摘要随着互联网及其应用的不断发展,内容分发网络(cdn)越来越受欢迎。协同边缘云计算架构可以显著降低流媒体服务系统的工作量。在传统工作中,开发了不同类型的内容放置和路由算法,以提高云系统的内容交付,降低延迟和成本。但是,现有的大多数算法都面临着资源占用增加、传输效率低下和系统设计复杂性高的问题。因此,提出的工作旨在为云cdn开发一个新的框架,称为基于分层优化资源利用的内容放置(HORCP)模型。在这里,使用混沌磷虾群优化(CKHO)方法来优化内容放置的资源使用。然后,采用层次概率路由(HPR)模型,优化路由路径,实现可靠的端到端数据传输。通过使用几个性能指标对所提出的HORCP模型的性能进行了验证和比较。所得结果也与目前最先进的方法进行了比较,以显示所提出的HORCP模型的优越性。通过使用HORCP机制,网络的总体内存使用减少到80%,CPU使用减少到20%,响应减少到2秒,相对于网络负载水平的总拥塞成本减少到100。
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来源期刊
Journal of Cloud Computing-Advances Systems and Applications
Journal of Cloud Computing-Advances Systems and Applications Computer Science-Computer Networks and Communications
CiteScore
6.80
自引率
7.50%
发文量
76
审稿时长
75 days
期刊介绍: The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA) will publish research articles on all aspects of Cloud Computing. Principally, articles will address topics that are core to Cloud Computing, focusing on the Cloud applications, the Cloud systems, and the advances that will lead to the Clouds of the future. Comprehensive review and survey articles that offer up new insights, and lay the foundations for further exploratory and experimental work, are also relevant.
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