无线通信中LRD流量与可变服务容量的队列服务质量分析
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"该文是IEEE Transactions on Wireless Communications期刊第11卷第2期的一篇研究论文，主要探讨了在具有远距离依赖网络流量和可变服务容量的排队系统中的服务质量分析。文章由Xiaolong Jin、Geyong Min、Speros Velentzas和Jianmin Jiang撰写，发表于2012年2月。"
在无线通信领域，高质测量研究已经证实无线网络流量表现出显著的远距离依赖（Long-Range-Dependent, LRD）特性。LRD是指数据包到达的间隔时间序列具有长程相关性，这种特性在高带宽需求的应用中尤其突出，如视频流和在线游戏等。此外，无线信道的衰落特性导致服务容量可以是变化的，这增加了系统分析的复杂性。
现有的分析模型通常简化假设服务容量恒定，以此来处理LRD到达过程的排队系统。然而，考虑到现实世界中无线信道的时间变化特性，这并不完全准确。因此，该论文的创新之处在于，它提出了一种全面的分析模型，以考虑LRD流量和可变服务容量对系统性能的影响。
作者们对这种复杂情况下的系统进行了深入分析，旨在评估服务质量（Quality-of-Service, QoS）。QoS指标通常包括延迟、丢包率、吞吐量和抖动等，这些指标直接影响到用户体验。通过构建数学模型，他们能够量化这些因素如何受到LRD流量模式和无线信道波动的共同影响。
此外，论文可能还涉及了以下几点：
1. 提出了新的统计方法来描述和建模LRD网络流量，以更准确地反映实际流量行为。
2. 分析了可变服务容量对系统性能的动态影响，可能包括不同信道条件下的性能变化。
3. 可能提供了优化策略，以改善在LRD流量和可变服务条件下的系统效率和服务质量。
4. 可能还包括了仿真或实验结果，以验证提出的分析模型的有效性和准确性。
这篇论文对于理解并优化在复杂无线环境中的网络性能有重要的理论和实践价值，对于网络设计者和管理者来说，是理解如何在LRD流量下确保服务质量和系统稳定性的关键参考资料。
562 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 11, NO. 2, FEBRUARY 2012
Transactions Papers
Quality-of-Service Analysis of
Queuing Systems with Long-Range-Dependent
Network Traffic and Variable Service Capacity
Xiaolong Jin, Geyong Min, Speros Velentzas, and Jianmin Jiang
Abstract—Many high-quality measurement studies have
demonstrated that wireless network traffic exhibits the noticeable
Long-Range-Dependent (LRD) property. Moreover, the fading
nature of wireless channels can lead to variable service capacity.
Due to the inherent difficulty and high complexity of modelling
the fractal-like L RD traffic, existing analytical models of queuing
systems with LRD arrival processes have b een primarily limited
to the simplified scenarios where the service capacity is assumed
to be constant. Given the time-varying nature of wireless channels
in the real-world working environments, it is very important
and necessary to investigate system performance in the presence
of variable service capacity. To this end, this paper presents a
comprehensive analytical model for queuing systems subject to
LRD traffic and variable service capacity. We extend the appli-
cation of a Large Deviation Principle and derive the closed-form
expressions of Quality-of-Service (QoS) metrics. The accuracy
of the model validated through extensive simulation experiments
makes it a cost-effective evaluation tool for performance analysis
of communication networks. To illustrate its applications, the
model is adopted to investigate the effects of LRD trafficand
variable service capacity on the system performance and resource
configuration.
Index Terms—Quality-of-service, long-range-dependency, frac-
tional Brownian motion, variable service capacity, performance
modelling.
I. INTRODUCTION
A
Straffic scheduling plays a c rucial role in the design
and performance of communication networks, analytical
Manuscript received May 21, 2010; revised January 30 and June 19, 2011;
accepted August 22, 2011. The associate editor coordinating the review of
this paper and approving it for publication was M. L. Merani.
This work was supported by the UK EPSRC Research Grant No.
EP/C525027/1, the National Natural Science Foundation of China under
Grants No. 61100175 and No. 60933005, and the National High-Tech R&D
Program of China under Grant No. 2010AA012500.
X. Jin is with the Key Laboratory of Network Science and Technology,
Institute of Computing Technology, Chinese Academy of Sciences, Beijing,
China (e-mail: jinxiaolong@ict.ac.cn).
G. Min (corresponding author) and J. Jiang are with the School of
Informatics, University of Bradford, Bradford, BD7 1DP, UK (e-mail: {g.min,
j.jiang}@brad.ac.uk).
S. Velentzas is with the R&D Department, AdvTec Ltd., 83 Lansdown
Road, Swindon, SN1 3ND, UK (e-mail: ross@advtec.co.uk).
Digital Object Identifier 10.1109/TWC.2011.120511.100867
modelling and evaluation of queuing systems have been re-
ceiving tremendous research efforts from both academia and
industry (e.g., [1]–[4]). The innovative study reported in [5]
has revealed that the traffic in local-area networks exhibits
noticeable Long-Range-Dependent (LRD) nature and set the
groundwork for considering long-range-dependency as a key
characteristic in understanding of traffic properties, modelling
and analysis of network performance. Moreover, this study
has triggered an explosion of research on this topic [6].
Many subsequent studies have further demonstrated that long-
range-dependency is a ubiquitous phenomenon in a variety
of communicatio n networks and multimedia systems [7], [8],
including local-area n etworks, wide-area networks, metro-area
networks, world wide web, and variable-bit-rate video and
multimedia systems.
More recently, the traffic in wireless networks has also
been shown to reveal the noticeable LRD nature [7], [9]–
[12]. For instance, Liang [9] investigated the traffic in wireless
mobile ad hoc networks and revealed that such network traffic
has the noticeable characteristic of long-range-dependency.
Yin and Lin [12] further developed a mathematical model
and theoretically proved the LRD nature of mobile ad hoc
network traffic. Oliveira, Kim, and Suda [11] empirically
verified that the traffic in IEEE 802.11b wireless local-area
networks exhibits the LRD property. Ilyas and Radha [7]
studied the IEEE 802.15.4 wireless personal area networks
and again discovered the traffic long-range-dependency.
LRD network traffic manifests itself as scale-invariant
burstiness and large-lag correlation. This fractal-like traffic
behavior has significantly different theoretical properties from
those of the conventional Short-Range-Dependent (SRD) traf-
fic (e.g., Poisson or Markovian processes) and can seriously
deteriorate queuing performance and user-perceived Quality-
of-Service (QoS) [5], [13]. As a consequence, the existing
analytical models developed for queuing systems under the
assumption of SRD traffic are no longer valid in the presence
of LRD traffic. The investigation of the effects of LRD
traffic on the performance of communication networks has
emerged as an important research topic in the networking and
communication research community (e.g., [14]–[17]). Norros
1536-1276/12$31.00
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2012 IEEE
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