• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Teletraffic Congress >Application-Aware Infrastructure Clustering for Cloud Service Placement to Enhance User QoE
【24h】

Application-Aware Infrastructure Clustering for Cloud Service Placement to Enhance User QoE

机译：面向云服务放置的应用感知基础架构集群可增强用户QoE

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Cloud service placement can be suboptimal in certain cases due to inefficient network design, which in turn impacts user Quality of Experience (QoE). Consequently, Application Service Providers (ASPs) need to manage cloud network infrastructures with efficient designs that fully satisfy Service Level Objectives (SLOs) of their data/videointensive applications of users. To proactively avoid this problem, a straightforward solution used by ASPs is to have many replicas of their services by renting more resources from Infrastructure Providers (InPs) which can lead to an expensive service delivery proposition. In this paper, we present a novel possibilistic C-Means (PCM) approach to enhance user QoE in cloud service placement by clustering network infrastructure with awareness of user SLO satisfaction amidst network path constraints. Our evaluation results obtained using numerical simulations as well as in a real-world cloud testbed with actual users prove that our multi-constrained path aware PCM approach outperforms existing solutions. Specifically, we show how our proposed infrastructure clustering with the PCM approach allows ASPs to rent less resources from InPs that reduces user cost, while still delivering satisfactory user QoE.
机译：由于网络设计效率低下，在某些情况下云服务放置可能不是最佳选择，这反过来又会影响用户的体验质量（QoE）。因此，应用程序服务提供商（ASP）需要使用高效的设计来管理云网络基础架构，这些设计完全满足用户数据/视频密集型应用程序的服务水平目标（SLO）。为了主动避免此问题，ASP使用的直接解决方案是通过从基础架构提供商（InP）租用更多资源来拥有其服务的许多副本，这可能导致昂贵的服务交付主张。在本文中，我们提出了一种新颖的可能的C均值（PCM）方法，它通过将网络基础架构聚类，并在网络路径约束下提高了用户对SLO的满意度，从而提高了云服务放置中的用户QoE。我们使用数值模拟以及在具有实际用户的真实云测试平台中获得的评估结果证明，我们的多约束路径感知PCM方法优于现有解决方案。具体而言，我们展示了我们提出的基于PCM方法的基础架构集群如何使ASP从InP租用更少的资源，从而降低用户成本，同时仍然提供令人满意的用户QoE。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号