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首页> 外文期刊>IEEE systems journal >Content Routing and Lookup Schemes Using Global Bloom Filter for Content-Delivery-as-a-Service
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Content Routing and Lookup Schemes Using Global Bloom Filter for Content-Delivery-as-a-Service

机译:使用全局布隆过滤器进行内容交付即服务的内容路由和查找方案

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摘要

The dramatic growth of user-generated contents (UGCs) transforms the digital media value chain, and stresses current content distribution network (CDN). In order to deliver UGCs in an efficient and economical fashion, we have proposed content-delivery-as-a-service (CoDaaS) by leveraging cloud computing technology. However, due to the exponential increase of Internet traffic (especially the UGCs), traditional hashing-based content routing and lookup scheme in CDNs suffers from high delay and consequent inefficient delivery. This paper introduces a global compressed counting BF (CCBF) into CoDaaS to address this issue. By equipping it with the global CCBF, our system is able to check early on for the existence of any specific content among all the peering surrogates, before any local checking on each cache node. Based on this global CCBF, we propose two content routing and lookup mechanisms (i.e., parallel and cut-through schemes) to reduce the delay for better user experience. The comparative performance of those approaches is verified via both mathematical modeling and experimental simulation. The results show that for light traffic load, the average response time can be saved by up to 65.2% compared with traditional methods. In addition, the impacts and overheads of different synchronization schemes are also quantified to provide valuable insight for further optimizations.
机译:用户生成的内容(UGC)的急剧增长改变了数字媒体价值链,并给当前的内容分发网络(CDN)带来了压力。为了以高效,经济的方式交付UGC,我们提出了利用云计算技术的内容交付即服务(CoDaaS)。但是,由于Internet流量(尤其是UGC)呈指数级增长,CDN中传统的基于哈希的内容路由和查找方案遭受了高延迟和随之而来的低效率传递。本文将全局压缩计数BF(CCBF)引入CoDaaS,以解决此问题。通过为它配备全局CCBF,我们的系统能够在对每个缓存节点进行任何本地检查之前,尽早检查所有对等代理中是否存在任何特定内容。基于此全局CCBF,我们提出了两种内容路由和查找机制(即并行和直通方案),以减少延迟,以获得更好的用户体验。这些方法的比较性能已通过数学建模和实验仿真验证。结果表明,与传统方法相比,在轻载情况下,平均响应时间可节省高达65.2%。此外,还对不同同步方案的影响和开销进行了量化,以为进一步优化提供有价值的见解。

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