{"title":"调整网络缓冲区:HTTP自适应流的视角","authors":"Darijo Raca, A. Zahran, C. Sreenan","doi":"10.1109/W-FiCloud.2016.80","DOIUrl":null,"url":null,"abstract":"HTTP Adaptive video Streaming (HAS) is the dominant traffic type on the Internet. When multiple video clients share a bottleneck link many problems arise, notably bandwidth underutilisation, unfairness and instability. Key findings from previous papers show that the \"ON-OFF\" behaviour of adaptive video clients is the main culprit. In this paper we focus on the network, and specifically the effects of network queue size when multiple video clients share network resources. We conducted experiments using the Mininet virtual network environment streaming real video content to open-source GPAC video clients. We explored how different network buffer sizes, ranging from 1xBDP to 30xBDP (bandwidth-delay-product), affect clients sharing a bottleneck link. Within GPAC, we implemented the published state-of-the-art adaptive video algorithms FESTIVE and BBA-2. We also evaluated impact of web cross-traffic. Our main findings indicate that the \"rule-of-thumb\" 1xBDP for network buffer sizing causes bandwidth underutilisation, limiting available bandwidth to 70% for all video clients across different round-trip-times (RTT). Interaction between web and HAS clients depends on multiple factors, including adaptation algorithm, bitrate distribution and offered web traffic load. Additionally, operating in an environment with heterogeneous RTTs causes unfairness among ompeting HAS clients. Based on our experimental results, we propose 2xBDP as a default network queue size in environments when multiple users share network resources with homogeneous RTTs. With heterogeneous RTTs, a BDP value based on the average RTTs for all clients improves fairness among competing clients by 60%.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Sizing Network Buffers: An HTTP Adaptive Streaming Perspective\",\"authors\":\"Darijo Raca, A. Zahran, C. Sreenan\",\"doi\":\"10.1109/W-FiCloud.2016.80\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"HTTP Adaptive video Streaming (HAS) is the dominant traffic type on the Internet. When multiple video clients share a bottleneck link many problems arise, notably bandwidth underutilisation, unfairness and instability. Key findings from previous papers show that the \\\"ON-OFF\\\" behaviour of adaptive video clients is the main culprit. In this paper we focus on the network, and specifically the effects of network queue size when multiple video clients share network resources. We conducted experiments using the Mininet virtual network environment streaming real video content to open-source GPAC video clients. We explored how different network buffer sizes, ranging from 1xBDP to 30xBDP (bandwidth-delay-product), affect clients sharing a bottleneck link. Within GPAC, we implemented the published state-of-the-art adaptive video algorithms FESTIVE and BBA-2. We also evaluated impact of web cross-traffic. Our main findings indicate that the \\\"rule-of-thumb\\\" 1xBDP for network buffer sizing causes bandwidth underutilisation, limiting available bandwidth to 70% for all video clients across different round-trip-times (RTT). Interaction between web and HAS clients depends on multiple factors, including adaptation algorithm, bitrate distribution and offered web traffic load. Additionally, operating in an environment with heterogeneous RTTs causes unfairness among ompeting HAS clients. Based on our experimental results, we propose 2xBDP as a default network queue size in environments when multiple users share network resources with homogeneous RTTs. 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引用次数: 3
摘要
HTTP自适应视频流(HAS, Adaptive video Streaming)是目前Internet上占主导地位的流量类型。当多个视频客户端共享一个瓶颈链路时,会出现许多问题,特别是带宽利用率不足、不公平和不稳定。先前论文的主要发现表明,自适应视频客户端的“开-关”行为是罪魁祸首。在本文中,我们关注的是网络,特别是当多个视频客户端共享网络资源时,网络队列大小的影响。我们使用Mininet虚拟网络环境进行实验,将真实视频内容流式传输到开源GPAC视频客户端。我们探讨了不同的网络缓冲区大小(从1xBDP到30xBDP(带宽延迟产品))如何影响共享瓶颈链路的客户机。在GPAC中,我们实现了已发布的最先进的自适应视频算法节日和BBA-2。我们还评估了网络交叉流量的影响。我们的主要研究结果表明,网络缓冲区大小的“经验法则”1xBDP导致带宽利用率不足,将不同往返时间(RTT)的所有视频客户端的可用带宽限制为70%。web和HAS客户端之间的交互取决于多种因素,包括自适应算法、比特率分布和提供的web流量负载。此外,在具有异构rtt的环境中操作会导致竞争的HAS客户机之间的不公平。基于我们的实验结果,我们建议将2xBDP作为多用户与同质rtt共享网络资源的环境中的默认网络队列大小。对于异构rtt,基于所有客户机的平均rtt的BDP值可以将竞争客户机之间的公平性提高60%。
Sizing Network Buffers: An HTTP Adaptive Streaming Perspective
HTTP Adaptive video Streaming (HAS) is the dominant traffic type on the Internet. When multiple video clients share a bottleneck link many problems arise, notably bandwidth underutilisation, unfairness and instability. Key findings from previous papers show that the "ON-OFF" behaviour of adaptive video clients is the main culprit. In this paper we focus on the network, and specifically the effects of network queue size when multiple video clients share network resources. We conducted experiments using the Mininet virtual network environment streaming real video content to open-source GPAC video clients. We explored how different network buffer sizes, ranging from 1xBDP to 30xBDP (bandwidth-delay-product), affect clients sharing a bottleneck link. Within GPAC, we implemented the published state-of-the-art adaptive video algorithms FESTIVE and BBA-2. We also evaluated impact of web cross-traffic. Our main findings indicate that the "rule-of-thumb" 1xBDP for network buffer sizing causes bandwidth underutilisation, limiting available bandwidth to 70% for all video clients across different round-trip-times (RTT). Interaction between web and HAS clients depends on multiple factors, including adaptation algorithm, bitrate distribution and offered web traffic load. Additionally, operating in an environment with heterogeneous RTTs causes unfairness among ompeting HAS clients. Based on our experimental results, we propose 2xBDP as a default network queue size in environments when multiple users share network resources with homogeneous RTTs. With heterogeneous RTTs, a BDP value based on the average RTTs for all clients improves fairness among competing clients by 60%.