无线局域网的网络流量特性与建模研究
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摘要
当前无线局域网的发展趋势表明,迅速增加的笔记本电脑和PDA的用户迫切要求为他们提供灵活的宽带无线服务。要想满足这一需求,研究无线局域网的流量特性和流量模型就显得十分重要,这也是本文研究的目的。
受到有线网络流量具有自相似性的启发,本文针对Standford大学无线局域网的流量测试结果做了大量的分析,首次发现无线局域网的真实流量特性在不同的时间尺度下都呈现出显著的自相似性。
为考察无线链路的流量是否也具有自相似性,本文进行了无线链路流量特性若干项测试,首次验证了无线链路的流量具有自相似性。本文认为这是无线局域网的流量具有自相似性的首要原因。
不仅无线链路的流量具有自相似性,我们还知道无线局域网的流量就是由各条无线链路上的流量汇聚、叠加而形成的,而汇聚、叠加是产生自相似的重要原因,本文认为这是无线局域网的流量呈现出典型自相似特征的另外一个原因。
Hurst系数、信息维数和盒维数是反映分形特性的重要指标,本文总结了Hurst系数、信息维数和盒维数在不同时间尺度下的变化规律,并结合无线局域网的用户行为方式给出了部分解释。
本文计算并绘制出了无线局域网流量的多重分形谱,从而首次发现无线局域网的真实流量具有多重分形的典型特征。
作为建立基于自相似理论的无线链路特性的数学模型的初步尝试,本文给出并验证了丢包率PLR的一个近似的计算公式。该公式的参数是Hurst系数、Buffer容量大小和该无线链路服务率。
鉴于无线局域网流量自相似性的发现,本文使用了两种基于分形理论的预测算法用于预测无线局域网流量,并与非分形的预测算法在预测效果上进行了比对,证实了基于分形理论的预测算法在预测无线局域网流量时的优越性。实际体现了发现无线局域网流量自相似性的意义。本文还对分段变维分形插值预测法进行了改进,提高了预测精度,克服了原方法的缺陷。
本文讨论了无线局域网可采用的提高性能可靠性的各种措施。并且,为在蓝牙应用层提高可靠性,本文研究并部分实现了支持断点续传的高可靠的新型蓝牙文件传输协议。
Current trends in wireless local area networks (WLAN) indicate an exigent demand to provide broadband wireless services to growing users of mobile laptop and PDA. To meet this need, it is very important to study the traffic characteristics and traffic model of WLAN, which is the purpose of this thesis.
Illumined by the findings of self-similarity in wired networks, and after analysing the real WLAN traffic test results in Stanford University, this thesis discovers, for the first time, that the real traffic in WLAN also exhibits obvious self-similarity.
Why does the self-similarity exist in WLAN? One conjecture is that the bottom-level wireless links maybe have self-similarity. To verify whether a wireless link also has self-similar characteristic, some traffic tests are performed over wireless links. In consequence, the traffic between point-to-point wireless devices also has distinct self-similarity, and it is the first reason of the self-similar traffic in WLAN.
As we known, the traffics over all of the wireless links are coverged and superposed into the traffic of WLAN. And covergence and superposition is an important condition to form self-similar traffic. So, we think it is another reason of the self-similar traffic in WLAN.
Then, this thesis obtains the Hurst coefficients, Information-dimension and Box-dimension of the Standford WLAN traffic traces at different time scales and analyzes the trends and regular rules of the above coefficients results. Accoding to the behaviours of the WLAN users, this thesis elementaryly explains these trends and rules.
Moreover, this thesis calculates and plots the multifractal spectrums of the Standford WLAN traffic data. The multifractal spectrums show, for the first time, that the WLAN traffic also has typical multifractal spectrum characteristic.
According to the above results, using self-similar theory, this thesis establishes and verifies a close-form approximate formula for PLR (Packet Loss Rate) over a wireless link, whose input variables are Hurst parameter, buffer size, and service rate.
At last, this thesis uses 2 fractal-based methods to predict the traffic in WLAN. The accuracy of the methods is verified by comparing with the original data, and the comparing results show that the fractal prediction methods are better than others. Additionally, by overcoming the blemish of one of the old method, this thesis improves the old prediction method and enhances the precision.
受到有线网络流量具有自相似性的启发,本文针对Standford大学无线局域网的流量测试结果做了大量的分析,首次发现无线局域网的真实流量特性在不同的时间尺度下都呈现出显著的自相似性。
为考察无线链路的流量是否也具有自相似性,本文进行了无线链路流量特性若干项测试,首次验证了无线链路的流量具有自相似性。本文认为这是无线局域网的流量具有自相似性的首要原因。
不仅无线链路的流量具有自相似性,我们还知道无线局域网的流量就是由各条无线链路上的流量汇聚、叠加而形成的,而汇聚、叠加是产生自相似的重要原因,本文认为这是无线局域网的流量呈现出典型自相似特征的另外一个原因。
Hurst系数、信息维数和盒维数是反映分形特性的重要指标,本文总结了Hurst系数、信息维数和盒维数在不同时间尺度下的变化规律,并结合无线局域网的用户行为方式给出了部分解释。
本文计算并绘制出了无线局域网流量的多重分形谱,从而首次发现无线局域网的真实流量具有多重分形的典型特征。
作为建立基于自相似理论的无线链路特性的数学模型的初步尝试,本文给出并验证了丢包率PLR的一个近似的计算公式。该公式的参数是Hurst系数、Buffer容量大小和该无线链路服务率。
鉴于无线局域网流量自相似性的发现,本文使用了两种基于分形理论的预测算法用于预测无线局域网流量,并与非分形的预测算法在预测效果上进行了比对,证实了基于分形理论的预测算法在预测无线局域网流量时的优越性。实际体现了发现无线局域网流量自相似性的意义。本文还对分段变维分形插值预测法进行了改进,提高了预测精度,克服了原方法的缺陷。
本文讨论了无线局域网可采用的提高性能可靠性的各种措施。并且,为在蓝牙应用层提高可靠性,本文研究并部分实现了支持断点续传的高可靠的新型蓝牙文件传输协议。
Current trends in wireless local area networks (WLAN) indicate an exigent demand to provide broadband wireless services to growing users of mobile laptop and PDA. To meet this need, it is very important to study the traffic characteristics and traffic model of WLAN, which is the purpose of this thesis.
Illumined by the findings of self-similarity in wired networks, and after analysing the real WLAN traffic test results in Stanford University, this thesis discovers, for the first time, that the real traffic in WLAN also exhibits obvious self-similarity.
Why does the self-similarity exist in WLAN? One conjecture is that the bottom-level wireless links maybe have self-similarity. To verify whether a wireless link also has self-similar characteristic, some traffic tests are performed over wireless links. In consequence, the traffic between point-to-point wireless devices also has distinct self-similarity, and it is the first reason of the self-similar traffic in WLAN.
As we known, the traffics over all of the wireless links are coverged and superposed into the traffic of WLAN. And covergence and superposition is an important condition to form self-similar traffic. So, we think it is another reason of the self-similar traffic in WLAN.
Then, this thesis obtains the Hurst coefficients, Information-dimension and Box-dimension of the Standford WLAN traffic traces at different time scales and analyzes the trends and regular rules of the above coefficients results. Accoding to the behaviours of the WLAN users, this thesis elementaryly explains these trends and rules.
Moreover, this thesis calculates and plots the multifractal spectrums of the Standford WLAN traffic data. The multifractal spectrums show, for the first time, that the WLAN traffic also has typical multifractal spectrum characteristic.
According to the above results, using self-similar theory, this thesis establishes and verifies a close-form approximate formula for PLR (Packet Loss Rate) over a wireless link, whose input variables are Hurst parameter, buffer size, and service rate.
At last, this thesis uses 2 fractal-based methods to predict the traffic in WLAN. The accuracy of the methods is verified by comparing with the original data, and the comparing results show that the fractal prediction methods are better than others. Additionally, by overcoming the blemish of one of the old method, this thesis improves the old prediction method and enhances the precision.
引文
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