Routing Games with Progressive Filling

Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived

Design of Congestion Controller for TCP Networks Based on LMI Formulation

In this paper, a state feedback H221E; controller has been proposed in order to design an active queue management (AQM) system based on congestion control algorithm for networks supporting TCP protocols. In this approach, the available link bandwidth is modeled as a time-variant disturbance. The objective of this paper is to design controller which capable of achieving the queue size and guarantee asymptotic stability in the present of disturbance. An important feature of the proposed approach is that the performance of system, including the disturbance rejection and stability of closed-loop system, are guaranteed for all round-trip times that are less than a known value. The controller design is formulated in the form of some linear matrix inequalities, which can efficiently solved numerically. The simulation results demonstrate the effectiveness of proposed methods in comparison with other conventional methods

Layering as Optimization Decomposition: Questions and Answers

Network protocols in layered architectures have historically been obtained on an ad-hoc basis, and much of the recent cross-layer designs are conducted through piecemeal approaches. Network protocols may instead be holistically analyzed and systematically designed as distributed solutions to some global optimization problems in the form of generalized Network Utility Maximization (NUM), providing insight on what they optimize and on the structures of network protocol stacks. In the form of 10 Questions and Answers, this paper presents a short survey of the recent efforts towards a systematic understanding of "layering" as "optimization decomposition". The overall communication network is modeled by a generalized NUM problem, each layer corresponds to a decomposed subproblem, and the interfaces among layers are quantified as functions of the optimization variables coordinating the subproblems. Furthermore, there are many alternative decompositions, each leading to a different layering architecture. Industry adoption of this unifying framework has also started. Here we summarize the current status of horizontal decomposition into distributed computation and vertical decomposition into functional modules such as congestion control, routing, scheduling, random access, power control, and coding. We also discuss under-explored future research directions in this area. More importantly than proposing any particular crosslayer design, this framework is working towards a mathematical foundation of network architectures and the design process of modularization

On the multiresolution structure of Internet traffic traces

Internet traffic on a network link can be modeled as a stochastic process. After detecting and quantifying the properties of this process, using statistical tools, a series of mathematical models is developed, culminating in one that is able to generate ``traffic'' that exhibits --as a key feature-- the same difference in behavior for different time scales, as observed in real traffic, and is moreover indistinguishable from real traffic by other statistical tests as well. Tools inspired from the models are then used to determine and calibrate the type of activity taking place in each of the time scales. Surprisingly, the above procedure does not require any detailed information originating from either the network dynamics, or the decomposition of the total traffic into its constituent user connections, but rather only the compliance of these connections to very weak conditions.Comment: 57 pages, color figures. Figures are of low quality due to space consideration

Modeling and control of network traffic for performance and secure communications

The objective of this research is to develop innovative techniques for modeling and control of network congestion. Most existing network controls have discontinuous actions, but such discontinuity in control actions is commonly omitted in analytical models, and instead continuous models were widely adopted in the literature. This approximation works well under certain conditions, but it does cause significant discrepancy in creating robust, responsive control solutions for congestion management. In this dissertation, I investigated three major topics. I proposed a generic discontinuous congestion control model and its design methodology to guarantee asymptotic stability and eliminate traffic oscillation, based on the sliding mode control (SMC) theory. My scheme shows that discontinuity plays a crucial role in optimization of the I-D based congestion control algorithms. When properly modeled, the simple I-D control laws can be made highly robust to parameter and model uncertainties. I discussed applicability of this model to some existing flow or congestion control schemes, e.g. XON/XOFF, rate and window based AIMD, RED, etc. It can also be effectively applied to design of detection and defense of distributed denial of service (DDoS) attacks. DDoS management can be considered a special case of the flow control problem. Based on my generic discontinuous congestion control model, I developed a backward-propagation feedback control strategy for DDoS detection and defense. It not only prevents DDoS attacks but also provides smooth traffic and bounded queue size. Another application of the congestion control algorithms is design of private group communication networks. I proposed a new technique for protection of group communications by concealment of sender-recipient pairs. The basic approach is to fragment and disperse encrypted messages into packets to be transported along different paths, so that the adversary cannot efficiently determine the source/recipient of a message without correct ordering of all packets. Packet flows among nodes are made balanced, to eliminate traffic patterns related to group activities. I proposed a sliding window-based flow control scheme to control transmission of payload and dummy packets. My algorithms allow flexible tradeoff between traffic concealment and performance requirement