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Continuing growth in cloud-based services and global Internet protocol traffic necessitates performance improvements in energy consumption, network delay, and service availability. Data centers providing cloud services and transport networks have often multiple stakeholders, which makes it difficult to implement centralized traffic management. This paper adopts a game-theoretic approach to data traffic management to obtain a distributed and energy-efficient solution, where each edge router is acting as a strategic player. A multiobjective optimization problem with a priori user-specific preferences is formulated for each player, and a distributed iterative algorithm is proposed to solve the game. The existence of Nash equilibrium of the proposed game is shown, followed by the theoretical convergence analysis of the iterative algorithm. The efficiency loss between the strategic game and the corresponding global optimization method is analyzed to quantify the impact of selfish behavior on the overall system performance. Simulation results show notable challenges for operators to plan, design, and operate a multimedia content network to optimize energy consumption, network delay, and load balance over a diurnal cycle. [ABSTRACT FROM PUBLISHER]

Abstract: We present a non-equilibrium analysis and control approach for the Active Queue Management (AQM) problem in communication networks. Using simplified fluid models, we carry out a bifurcation study of the complex dynamic queue behavior to show that non-equilibrium methods are essential for analysis and optimization in the AQM problem. We investigate an ergodic theoretic framework for stochastic modeling of the non-equilibrium behavior in deterministic models and use it to identify parameters of a fluid model from packet level simulations. For computational tractability, we use set-oriented numerical methods to construct finite-dimensional Markov models, including control Markov chains and hidden Markov models. Subsequently, we develop and analyze an example AQM algorithm using a Markov Decision Process (MDP) based control framework. The control scheme developed is optimal with respect to a reward function, defined over the queue size and aggregate flow rate. We implement and simulate our illustrative AQM algorithm in the ns-2 network simulator. The results obtained confirm the theoretical analysis and exhibit promising performance when compared with well-known alternative schemes under persistent non-equilibrium queue behavior. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate stability, bifurcation and oscillations arising in a single-link communication network model with a large number of heterogeneous users adopting a Transmission Control Protocol (TCP)-like rate control scheme with an Active Queue Management (AQM) router. In the system considered, different user delays are known and fixed but taken from a given distribution. It is shown that for any given distribution of delays, there exists a critical amount of feedback (due to AQM) at which the equilibrium loses stability and a limit cycling solution develops via a Hopf bifurcation. The nature (criticality) of the bifurcation is investigated with the aid of Lyapunov–Schmidt perturbation method. The results of the analysis are numerically verified and provide valuable insights into dynamics of the AQM control system. [Copyright &y& Elsevier]