The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena

The Internet is the most complex system ever created in human history. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, large-scale effects of worm traffic, and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex System

Modeling the interdependency of low-priority congestion control and active queue management

Recently, a negative interplay has been shown to arise when scheduling/AQM techniques and low-priority congestion control protocols are used together: namely, AQM resets the relative level of priority among congestion control protocols. This work explores this issue by (i) studying a fluid model that describes system dynamics of heterogeneous congestion control protocols competing on a bottleneck link governed by AQM and (ii) proposing a system level solution able to reinstate priorities among protocols.Comment: 9 page

Analysis of a Reputation System for Mobile Ad-Hoc Networks with Liars

The application of decentralized reputation systems is a promising approach to ensure cooperation and fairness, as well as to address random failures and malicious attacks in Mobile Ad-Hoc Networks. However, they are potentially vulnerable to liars. With our work, we provide a first step to analyzing robustness of a reputation system based on a deviation test. Using a mean-field approach to our stochastic process model, we show that liars have no impact unless their number exceeds a certain threshold (phase transition). We give precise formulae for the critical values and thus provide guidelines for an optimal choice of parameters.Comment: 17 pages, 6 figure

TCP performance enhancement in wireless networks via adaptive congestion control and active queue management

The transmission control protocol (TCP) exhibits poor performance when used in error-prone wireless networks. Remedy to this problem has been an active research area. However, a widely accepted and adopted solution is yet to emerge. Difficulties of an acceptable solution lie in the areas of compatibility, scalability, computational complexity and the involvement of intermediate routers and switches. This dissertation rexriews the current start-of-the-art solutions to TCP performance enhancement, and pursues an end-to-end solution framework to the problem. The most noticeable cause of the performance degradation of TCP in wireless networks is the higher packet loss rate as compared to that in traditional wired networks. Packet loss type differentiation has been the focus of many proposed TCP performance enhancement schemes. Studies conduced by this dissertation research suggest that besides the standard TCP\u27s inability of discriminating congestion packet losses from losses related to wireless link errors, the standard TCP\u27s additive increase and multiplicative decrease (AIMD) congestion control algorithm itself needs to be redesigned to achieve better performance in wireless, and particularly, high-speed wireless networks. This dissertation proposes a simple, efficient, and effective end-to-end solution framework that enhances TCP\u27s performance through techniques of adaptive congestion control and active queue management. By end-to-end, it means a solution with no requirement of routers being wireless-aware or wireless-specific . TCP-Jersey has been introduced as an implementation of the proposed solution framework, and its performance metrics have been evaluated through extensive simulations. TCP-Jersey consists of an adaptive congestion control algorithm at the source by means of the source\u27s achievable rate estimation (ARE) —an adaptive filter of packet inter-arrival times, a congestion indication algorithm at the links (i.e., AQM) by means of packet marking, and a effective loss differentiation algorithm at the source by careful examination of the congestion marks carried by the duplicate acknowledgment packets (DUPACK). Several improvements to the proposed TCP-Jersey have been investigated, including a more robust ARE algorithm, a less computationally intensive threshold marking algorithm as the AQM link algorithm, a more stable congestion indication function based on virtual capacity at the link, and performance results have been presented and analyzed via extensive simulations of various network configurations. Stability analysis of the proposed ARE-based additive increase and adaptive decrease (AJAD) congestion control algorithm has been conducted and the analytical results have been verified by simulations. Performance of TCP-Jersey has been compared to that of a perfect , but not practical, TCP scheme, and encouraging results have been observed. Finally the framework of the TCP-Jersey\u27s source algorithm has been extended and generalized for rate-based congestion control, as opposed to TCP\u27s window-based congestion control, to provide a design platform for applications, such as real-time multimedia, that do not use TCP as transport protocol yet do need to control network congestion as well as combat packet losses in wireless networks. In conclusion, the framework architecture presented in this dissertation that combines the adaptive congestion control and active queue management in solving the TCP performance degradation problem in wireless networks has been shown as a promising answer to the problem due to its simplistic design philosophy complete compatibility with the current TCP/IP and AQM practice, end-to-end architecture for scalability, and the high effectiveness and low computational overhead. The proposed implementation of the solution framework, namely TCP-Jersey is a modification of the standard TCP protocol rather than a completely new design of the transport protocol. It is an end-to-end approach to address the performance degradation problem since it does not require split mode connection establishment and maintenance using special wireless-aware software agents at the routers. The proposed solution also differs from other solutions that rely on the link layer error notifications for packet loss differentiation. The proposed solution is also unique among other proposed end-to-end solutions in that it differentiates packet losses attributed to wireless link errors from congestion induced packet losses directly from the explicit congestion indication marks in the DUPACK packets, rather than inferring the loss type based on packet delay or delay jitter as in many other proposed solutions; nor by undergoing a computationally expensive off-line training of a classification model (e.g., HMM), or a Bayesian estimation/detection process that requires estimations of a priori loss probability distributions of different loss types. The proposed solution is also scalable and fully compatible to the current practice in Internet congestion control and queue management, but with an additional function of loss type differentiation that effectively enhances TCP\u27s performance over error-prone wireless networks. Limitations of the proposed solution architecture and areas for future researches are also addressed

Modeling and estimation techniques for understanding heterogeneous traffic behavior

The majority of current internet traffic is based on TCP. With the emergence of new applications, especially new multimedia applications, however, UDP-based traffic is expected to increase. Furthermore, multimedia applications have sparkled the development of protocols responding to congestion while behaving differently from TCP. As a result, network traffc is expected to become more and more diverse. The increasing link capacity further stimulates new applications utilizing higher bandwidths of future. Besides the traffic diversity, the network is also evolving around new technologies. These trends in the Internet motivate our research work. In this dissertation, modeling and estimation techniques of heterogeneous traffic at a router are presented. The idea of the presented techniques is that if the observed queue length and packet drop probability do not match the predictions from a model of responsive (TCP) traffic, then the error must come from non-responsive traffic; it can then be used for estimating the proportion of non-responsive traffic. The proposed scheme is based on the queue length history, packet drop history, expected TCP and queue dynamics. The effectiveness of the proposed techniques over a wide range of traffic scenarios is corroborated using NS-2 based simulations. Possible applications based on the estimation technique are discussed. The implementation of the estimation technique in the Linux kernel is presented in order to validate our estimation technique in a realistic network environment

Flow Control in Wireless Ad-hoc Networks

We are interested in maximizing the Transmission Control Protocol (TCP) throughput between two nodes in a single cell wireless ad-hoc network. For this, we follow a cross-layer approach by first developing an analytical model that captures the effect of the wireless channel and the MAC layer to TCP. The analytical model gives the time evolution of the TCP window size which is described by a stochastic differential equation driven by a point process. The point process represents the arrival of acknowledgments sent by the TCP receiver to the sender as part of the self-regulating mechanism of the flow control protocol. Through this point process we achieve a cross-layer integration between the physical layer, the MAC layer and TCP. The intervals between successive points describe how the packet drops at the wireless channel and the delays because of retransmission at the MAC layer affect the window size at the TCP layer. We fully describe the statistical behavior of the point process by computing first the p.d.f. for the inter-arrival intervals and then the compensator and the intensity of the process parametrized by the quantities that describe the MAC layer and the wireless channel. To achieve analytical tractability we concentrate on the pure (unslotted) Aloha for the MAC layer and the Gilbert-Elliott model for the channel. Although the Aloha protocol is simpler than the more popular IEEE 802.11 protocol, it still exhibits the same exponential backoff mechanism which is a key factor for the performance of TCP in a wireless network. Moreover, another reason to study the Aloha protocol is that the protocol and its variants gain popularity as they are used in many of today's wireless networks. Using the analytical model for the TCP window size evolution, we try to increase the TCP throughput between two nodes in a single cell network. We want to achieve this by implicitly informing the TCP sender of the network conditions. We impose this additional constraint so we can achieve compatibility between the standard TCP and the optimized version. This allows the operation of both protocol stacks in the same network. We pose the optimization problem as an optimal stopping problem. For each packet transmitted by the TCP sender to the network, an optimal time instance has to be computed in the absence of an acknowledgment for this packet. This time instance indicates when a timeout has to be declared for the packet. In the absence of an acknowledgment, if the sender waits long for declaring a timeout, the network is underutilized. If the sender declares a timeout soon, it minimizes the transmission rate. Because of the analytical intractability of the optimal stopping time problem, we follow a Markov chain approximation method to solve the problem numerically

Networking Mechanisms for Delay-Sensitive Applications

The diversity of applications served by the explosively growing Internet is increasing. In particular, applications that are sensitive to end-to-end packet delays become more common and include telephony, video conferencing, and networked games. While the single best-effort service of the current Internet favors throughput-greedy traffic by equipping congested links with large buffers, long queuing at the congested links hurts the delay-sensitive applications. Furthermore, while numerous alternative architectures have been proposed to offer diverse network services, the innovative alternatives failed to gain widespread end-to-end deployment. This dissertation explores different networking mechanisms for supporting low queueing delay required by delay-sensitive applications. In particular, it considers two different approaches. The first one assumes employing congestion control protocols for the traffic generated by the considered class of applications. The second approach relies on the router operation only and does not require support from end hosts

Delay-oriented active queue management in TCP/IP networks

PhDInternet-based applications and services are pervading everyday life. Moreover, the growing popularity of real-time, time-critical and mission-critical applications set new challenges to the Internet community. The requirement for reducing response time, and therefore latency control is increasingly emphasized. This thesis seeks to reduce queueing delay through active queue management. While mathematical studies and research simulations reveal that complex trade-off relationships exist among performance indices such as throughput, packet loss ratio and delay, etc., this thesis intends to find an improved active queue management algorithm which emphasizes delay control without trading much on other performance indices such as throughput and packet loss ratio. The thesis observes that in TCP/IP network, packet loss ratio is a major reflection of congestion severity or load. With a properly functioning active queue management algorithm, traffic load will in general push the feedback system to an equilibrium point in terms of packet loss ratio and throughput. On the other hand, queue length is a determinant factor on system delay performance while has only a slight influence on the equilibrium. This observation suggests the possibility of reducing delay while maintaining throughput and packet loss ratio relatively unchanged. The thesis also observes that queue length fluctuation is a reflection of both load changes and natural fluctuation in arriving bit rate. Monitoring queue length fluctuation alone cannot distinguish the difference and identify congestion status; and yet identifying this difference is crucial in finding out situations where average queue size and hence queueing delay can be properly controlled and reasonably reduced. However, many existing active queue management algorithms only monitor queue length, and their control policies are solely based on this measurement. In our studies, our novel finding is that the arriving bit rate distribution of all sources contains information which can be a better indication of congestion status and has a correlation with traffic burstiness. And this thesis develops a simple and scalable way to measure its two most important characteristics, namely the mean ii and the variance of the arriving rate distribution. The measuring mechanism is based on a Zombie List mechanism originally proposed and deployed in Stabilized RED to estimate the number of flows and identify misbehaving flows. This thesis modifies the original zombie list measuring mechanism, makes it capable of measuring additional variables. Based on these additional measurements, this thesis proposes a novel modification to the RED algorithm. It utilizes a robust adaptive mechanism to ensure that the system reaches proper equilibrium operating points in terms of packet loss ratio and queueing delay under various loads. Furthermore, it identifies different congestion status where traffic is less bursty and adapts RED parameters in order to reduce average queue size and hence queueing delay accordingly. Using ns-2 simulation platform, this thesis runs simulations of a single bottleneck link scenario which represents an important and popular application scenario such as home access network or SoHo. Simulation results indicate that there are complex trade-off relationships among throughput, packet loss ratio and delay; and in these relationships delay can be substantially reduced whereas trade-offs on throughput and packet loss ratio are negligible. Simulation results show that our proposed active queue management algorithm can identify circumstances where traffic is less bursty and actively reduce queueing delay with hardly noticeable sacrifice on throughput and packet loss ratio performances. In conclusion, our novel approach enables the application of adaptive techniques to more RED parameters including those affecting queue occupancy and hence queueing delay. The new modification to RED algorithm is a scalable approach and does not introduce additional protocol overhead. In general it brings the benefit of substantially reduced delay at the cost of limited processing overhead and negligible degradation in throughput and packet loss ratio. However, our new algorithm is only tested on responsive flows and a single bottleneck scenario. Its effectiveness on a combination of responsive and non-responsive flows as well as in more complicated network topology scenarios is left for future work