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Caching over-the-top services, the Netflix case

机译:缓存Netflix案例中的顶级服务

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摘要

Over-the-top (OTT) traffic represents around 67% of the downstream Internet data volume during peak periods in the US. OTT content providers have been following the strategy of deploying caching servers within the ISPs' own networks. This work presents a method for deciding where these caches for OTT services can be conveniently deployed to provide significant traffic offload to ISPs' back-haul links. The procedure followed is to find suitable caching locations that minimize the maximum link traffic load. The problem is defined and solved as a Link Load Balanced Capacitated Facility Location Problem (LLB-CFL). The solution search processes are implemented based on Genetic Algorithms (GA), designing genetic operators highly targeted towards this specific problem. The proposed methods are applied to a case study focusing on the demand and cache specifications of Netflix, and framed into a real geographical area, the island of Bornholm, Denmark. The results cover a thorough analysis of the cost-fitness trade-off of the search method and an evaluation of both cache and gateway traffic flowing in the network in relation to the solutions found using different network topologies.
机译:在美国的高峰时段,空中(OTT)流量约占下游互联网数据量的67%。 OTT内容提供商一直在遵循在ISP自己的网络中部署缓存服务器的策略。这项工作提出了一种方法,用于确定可以方便地部署OTT服务的这些缓存的位置,以为ISP的回程链路提供可观的流量分流。遵循的过程是找到合适的缓存位置,以最大程度地减少最大链接流量负载。该问题被定义并解决为链路负载平衡的容量设施位置问题(LLB-CFL)。解决方案搜索过程是基于遗传算法(GA)实施的,设计了针对此特定问题的遗传算子。拟议的方法被应用于关注Netflix的需求和缓存规范的案例研究中,并以真实的地理区域(丹麦的Bornholm岛)为框架。结果涵盖了对搜索方法的成本适合性折衷的全面分析,以及对与使用不同网络拓扑找到的解决方案相关的网络中缓存和网关流量的评估。

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