一种新的面向普适计算的互联网实时流量模式检测技术

Wilfred W. K. Lin, Richard S. L. Wu, Allan K. Y. Wong, T. Dillon
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引用次数: 3

摘要

互联网遵循幂律。由于这个原因,它的交通模式有多种形式,这些形式毫无征兆地变化着。例如,它可能突然从LRD(远程依赖)改变,如重尾或自相似的SRD(短程依赖),如泊松或多重分形。这使得在Internet上成功运行时间要求苛刻的普及应用程序变得困难,因为很难控制逻辑TCP(传输控制协议)通道的响应时效性。提出的实时流量模式检测器(RTPD)技术具有通用性,能够在线检测和识别LRD和SRD的流量模式。如果将其实现为逻辑对象,则实时和普及应用程序可以使用其检测到的结果在运行时进行自我重新配置,以获得更好的性能,包括更短的服务往返时间(RTT)和容错性。RTPD在概念上是“M3RT + R/S +过滤”的组合。m3rt(微平均消息响应时间)工具是收敛算法(CA)的微实现,它是一个带反馈的IEPM (Internet端到端性能测量)模型。该工具也被称为微型CA (MCA),可以在线或以预先收集的痕迹进行事后分析,快速准确地预测任何波形的平均值。微型IEPM工具作为独立对象运行,可以通过消息传递随时随地为服务调用。如果M3RT被抑制,则RTPD与传统的R/S(重新调整的统计量)估计器一起工作,但仍然在线检测LRD和SRD模式。如果激活了M3RT支持,则RTPD与增强的R/S或E-R/S一起工作。所提出的RTPD技术不同于其他事后分析方法(例如Hill estimator),因为它可以实时检测和识别流量模式。它对基于internet的普及应用程序的贡献是显著的,因为它的输出使这些应用程序能够动态地重新配置并快速适应新的操作标准。结果是系统性能更好,服务往返时间(RTT)更短,令客户满意
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Internet Real-Time Traffic Pattern Detection Technique for Better Pervasive Computing
The Internet follows the power law. For this reason its traffic pattern takes many forms, which change without warning. For example it may change suddenly from LRD (long-range dependence) such as heavy-tailed or self-similar to SRD (short-range dependence) such as Poisson or multifractal. This makes it difficult to run time-critical pervasive applications over the Internet successfully because it is hard to control the response timeliness of the logical TCP (transmission control protocol) channels. The proposed real-time traffic pattern detector (RTPD) technique is generic and detects and identifies LRD and SRD traffic pattern online. If it is implemented as a logical object, then realtime and pervasive applications can use its detected results to self-reconfigure at runtime for better performance that includes shorter service roundtrip time (RTT) and fault tolerance. The RTPD is conceptually the "M3RT + R/S + filtration" combination. The M 3RT (micro mean message response time) tool is the micro implementation of the convergence algorithm (CA), which is an IEPM (Internet end-to-end performance measurement) model with feedback. Alternatively known as the micro CA (MCA), this tool predicts the mean of any waveform quickly and accurately, either on-line or in a postmortem manner with pre-collected traces. A micro IEPM tool operates as an independent object, to be invoked for service anytime and anywhere by message passing. If M3RT is inhibited, then RTPD works with the traditional R/S (rescaled adjusted statistics) estimator, but still detects the LRD and SRD patterns on-line. If M3RT support is activated, then RTPD works with the enhanced R/S or E-R/S. The proposed RTPD technique differs from other post-mortem approaches (e.g. Hill estimator) because it detects and identifies traffic patterns on the fly. Its contribution to Internet-based pervasive applications is significant because its output enables these applications to reconfigure on the fly and adapt quickly to new operational criteria. The result is better system performance in light of a shorter service roundtrip time (RTT) that makes the client happy
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