A robust adaptive congestion control strategy for large scale networks with differentiated services traffic

Abstract

Abstract-In this paper, a robust decentralized congestion control strategy is developed for a large scale network with Differentiated Services (Diff-Serv) traffic. The network is modeled by a nonlinear fluid flow model corresponding to two classes of traffic, namely the premium traffic and the ordinary traffic. The proposed congestion controller does take into account the associated physical network resource limitations and is shown to be robust to the unknown and time-varying delays. Our proposed decentralized congestion control strategy is developed on the basis of Diff-Serv architecture by utilizing a robust adaptive technique. A Linear Matrix Inequality (LMI) condition is obtained to guarantee the ultimate boundedness of the closed-loop system. Numerical simulation implementations are presented by utilizing the QualNet and Matlab software tools to illustrate the effectiveness and capabilities of our proposed decentralized congestion control strategy.

Average consensus in multi-agent systems with uncertain topologies and multiple time-varying delays

“…Consider the switching system (5). We assume that the digraphs G (k) (t) with Laplacian matrices L (k) m,t := L (k) + ΔL (k) m (t) are balanced for t ≥ 0, m = 1, · · · , M and k = 1, · · · , Ξ.…”

“…Multi-agent systems have been widely used in the areas of formation control [10], flocking or swarming behaviors [24,32], path planning [8] and congestion control in communication networks [3,5], etc. In coordinated control of multiagent systems, a critical problem is to design appropriate protocols and algorithms such that multiple agents can achieve a common consensus value on the shared information in the presence of limited and unreliable information exchange as well as communication delays [1,9,23,26,28,29].…”

Profile-Based Adaptive DiffServ Policing with Learning Techniques

“…It is also our belief that our approach has advantages on acting only in the network elements with significant contribution, in exchange for a small amount of signaling, and presents better scalability. [9] refines the model using a closed-loop system and traffic data compression. An extensive analytical approach is used to show the stability of the closed-loop system.…”

“…However, it bears the risk of undesirable oscillations in the feedback closed-loop to appear, reducing the effectiveness of the mechanism. The use of decentralized control strategies with feedback to the sources have been proposed [8], [9], [10] to prevent or deal with congestion situations. [8] reports the development of a generic traffic control mechanism that uses queue status information and non-linear control theory to tightly control the output queues of each router, and sends information on the allowed traffic to upstream traffic sources in order to guarantee an overall network performance.…”

A new adaptive sliding-based congestion control strategy for a large scale TCP/IP network with differentiated services

“…However a number of congestion control schemes for the Diff-Serv networks were presented in [9]- [16], but these works have serious problems. In [9]- [13] based on the fluid flow model, various congestion control strategy were proposed for one node without considering the interaction of other dynamic nodes.…”