Elephant flow (original) (raw)
在计算机网络中，大象流（英語：Elephant Flow）是由通过网络链路测量的傳輸控制協定（或其他协议）流建立的一个非常大的连续流（总字节数）。虽然大象流不常出现，但是在一段时间内会占据了总带宽的不成比例的份额。目前不清楚是谁创造了「大象流」"一词，但这一术语始于2001年发表的因特网网络研究中，当时观察到：少数流携带了大部分因特网流量，其余流量由大量携带的因特网流量很少（老鼠流）的流组成。例如，研究人员Mori等人研究了几所日本大学和研究网络的流量：在宽带网络中，他们发现大象流量仅占所有流量的4.7%，但占据了这段时间内所有传输数据的41.3%。 大象流对互联网流量的实际影响仍然是一个研究和争论的领域。一些研究表明，大象流可能与交通峰值和其他大象流（Lan & Heidemann and Mori）高度相关。研究人员提出了不同的定义，包括在一段时间内占总流量1%以上的流量、测量流量持续时间，以及观察流量大于这段时间内流量平均值加上三个标准差的流量。现阶段研究大象流的主要目标之一是为互联网开发更有效的带宽管理工具和预测模型。例如，研究人员通过降低大象流的优先级，将重点放在为小型流（老鼠流）提供更高服务质量（QoS）的服务上。
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| dbo:abstract | In computer networking, an elephant flow is an extremely large (in total bytes) continuous flow set up by a TCP (or other protocol) flow measured over a network link. Elephant flows, though not numerous, can occupy a disproportionate share of the total bandwidth over a period of time. It is not clear who coined "elephant flow", but the term began occurring in published Internet network research in 2001 when the observations were made that a small number of flows carry the majority of Internet traffic and the remainder consists of a large number of flows that carry very little Internet traffic (mice flows). For example, researchers Mori et al. studied the traffic flows on several Japanese universities and research networks. At the WIDE network they found elephant flows were only 4.7% of all flows but occupied 41.3% of all data transmitted during the time period. The actual impact of elephant flows on Internet traffic is still an area of research and debate. Some research shows that elephant flows may be highly correlated with traffic spikes and other elephant flows (Lan & Heidemann and Mori et al.). Elephant flows have varying definitions proposed by researchers including flows that occupy greater than 1% of total traffic in a time period, measuring the duration of the flow, and looking at flows whose size is greater than the mean plus three standard deviations of traffic during the time period. One of the main goals of research into elephant flows is to develop more efficient bandwidth management tools and predictive models for the Internet. For example, researchers have focused on providing better quality of service to flows of small sizes (mice flows) by de-prioritizing elephant flows. Elephant flows can also be viewed from the perspective of a network appliance such as an Intrusion Prevention System (IPS). In this context the number of bytes on the flow is less significant than the instantaneous processing load required to service the flow, where the processing load depends on the IPS configuration (how much work it is supposed to do) and the byte rate (flow throughput). An elephant flow could thus be defined as a flow that exceeds a given total service time within a particular time interval For example, if just a single CPU core is used to process a flow, an elephant flow could be considered any flow for which the processing load exceeds the capacity of the CPU core. This in turn could be defined by dropped packets or an excess latency for any packet to transit the device. Obviously, lower thresholds can be applied and more cores could be used but the basic concept of required processing load relative to processing capacity holds. To see how this differs from simply looking at the total bytes on a flow, consider two flows F1 and F2 with N1 and N2 total bytes respectively and where N2 = 1000*N1. It is possible that N1 is an elephant flow while N2 is not, if for example the required inspection of F1 is more complex than that of F2 and/or if the rate of F1 is much greater than the rate of F2. (en) 在计算机网络中，大象流（英語：Elephant Flow）是由通过网络链路测量的傳輸控制協定（或其他协议）流建立的一个非常大的连续流（总字节数）。虽然大象流不常出现，但是在一段时间内会占据了总带宽的不成比例的份额。目前不清楚是谁创造了「大象流」"一词，但这一术语始于2001年发表的因特网网络研究中，当时观察到：少数流携带了大部分因特网流量，其余流量由大量携带的因特网流量很少（老鼠流）的流组成。例如，研究人员Mori等人研究了几所日本大学和研究网络的流量：在宽带网络中，他们发现大象流量仅占所有流量的4.7%，但占据了这段时间内所有传输数据的41.3%。 大象流对互联网流量的实际影响仍然是一个研究和争论的领域。一些研究表明，大象流可能与交通峰值和其他大象流（Lan & Heidemann and Mori）高度相关。研究人员提出了不同的定义，包括在一段时间内占总流量1%以上的流量、测量流量持续时间，以及观察流量大于这段时间内流量平均值加上三个标准差的流量。现阶段研究大象流的主要目标之一是为互联网开发更有效的带宽管理工具和预测模型。例如，研究人员通过降低大象流的优先级，将重点放在为小型流（老鼠流）提供更高服务质量（QoS）的服务上。 (zh) |
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| rdfs:comment | 在计算机网络中，大象流（英語：Elephant Flow）是由通过网络链路测量的傳輸控制協定（或其他协议）流建立的一个非常大的连续流（总字节数）。虽然大象流不常出现，但是在一段时间内会占据了总带宽的不成比例的份额。目前不清楚是谁创造了「大象流」"一词，但这一术语始于2001年发表的因特网网络研究中，当时观察到：少数流携带了大部分因特网流量，其余流量由大量携带的因特网流量很少（老鼠流）的流组成。例如，研究人员Mori等人研究了几所日本大学和研究网络的流量：在宽带网络中，他们发现大象流量仅占所有流量的4.7%，但占据了这段时间内所有传输数据的41.3%。 大象流对互联网流量的实际影响仍然是一个研究和争论的领域。一些研究表明，大象流可能与交通峰值和其他大象流（Lan & Heidemann and Mori）高度相关。研究人员提出了不同的定义，包括在一段时间内占总流量1%以上的流量、测量流量持续时间，以及观察流量大于这段时间内流量平均值加上三个标准差的流量。现阶段研究大象流的主要目标之一是为互联网开发更有效的带宽管理工具和预测模型。例如，研究人员通过降低大象流的优先级，将重点放在为小型流（老鼠流）提供更高服务质量（QoS）的服务上。 (zh) In computer networking, an elephant flow is an extremely large (in total bytes) continuous flow set up by a TCP (or other protocol) flow measured over a network link. Elephant flows, though not numerous, can occupy a disproportionate share of the total bandwidth over a period of time. It is not clear who coined "elephant flow", but the term began occurring in published Internet network research in 2001 when the observations were made that a small number of flows carry the majority of Internet traffic and the remainder consists of a large number of flows that carry very little Internet traffic (mice flows). For example, researchers Mori et al. studied the traffic flows on several Japanese universities and research networks. At the WIDE network they found elephant flows were only 4.7% of all (en) |
| rdfs:label | Elephant flow (en) 大象流 (zh) |
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