Rate Based Flow Control Algorithms Research Articles

Fair resource allocation and stability for communication networks with multipath routing

Multipath networks allow that each source-destination pair can have several different paths for data transmission, thus they improve the performance of increasingly bandwidth-hungry applications and well cater for traffic load balancing and bandwidth usage efficiency. This paper investigates fair resource allocation for users in multipath networks and formulates it as a multipath network utility maximisation problem with several fairness concepts. By applying the Lagrangian method, sub-problems for users and paths are derived from the resource allocation model and interpreted from an economic point of view. In order to solve the model, a novel rate-based flow control algorithm is proposed for achieving optimal resource allocation, which depends only on local information. In the presence of round-trip delays, sufficient conditions are obtained for local stability of the delayed algorithm. As for the end-to-end implementation in Internet, a window-based flow control mechanism is presented since it is more convenient to implement than rate-based flow control.

Efficiency of Oblivious versus Nonoblivious Schedulers for Optimistic, Rate-based Flow Control

Two important performance parameters of distributed, rate-based flow control algorithms are their locality and convergence complexity. The former is characterized by the amount of global knowledge that is available to their scheduling mechanisms, while the latter is defined as the number of update operations performed on rates of individual sessions until max-min fairness is reached. Optimistic algorithms allow any session to intermediately receive a rate larger than its max-min fair rate; bottleneck algorithms finalize the rate of a session only if it is restricted by a certain, highly congested link of the network. In this work, we present a comprehensive collection of lower and upper bounds on convergence complexity, under varying degrees of locality, for optimistic, bottleneck, rate-based flow control algorithms. Say that an algorithm is oblivious if its scheduling mechanism uses no information of either the session rates or the network topology. We present a novel, combinatorial construction of a capacitated network, which we use to establish a fundamental lower bound of $\frac{dn}{4} + \frac{n}{2}$ on the convergence complexity of any oblivious algorithm, where n is the number of sessions laid out on a network, and d, the session dependency, is a measure of topological dependencies among sessions. Moreover, we devise a novel simulation proof to establish that, perhaps surprisingly, the lower bound of $\frac{dn}{4} + \frac{n}{2}$ on convergence complexity still holds for any partially oblivious algorithm, in which the scheduling mechanism is allowed to use information about session rates, but is otherwise unaware of network topology. On the positive side, we prove that the lower bounds for oblivious and partially oblivious algorithms are both tight. We do so by presenting optimal oblivious algorithms, which converge after $\frac{dn}{2} + \frac{n}{2}$ update operations are performed in the worst case. To complete the picture, we show that linear convergence complexity can indeed be achieved if information about both session rates and network topology is available to schedulers. We present a counterexample, nonoblivious algorithm, which converges within an optimal number of n update operations. Our results imply a surprising convergence complexity collapse of oblivious and partially oblivious algorithms, and a convergence complexity separation between (partially) oblivious and nonoblivious algorithms for optimistic, bottleneck rate-based flow control.

Convergence Complexity of Optimistic Rate-Based Flow-Control Algorithms

This paper studies basic properties of rate-based flow-control algorithms and of the max-min fairness criteria. For the algorithms we suggest a new approach for their modeling and analysis, which may be considered more “optimistic” and realistic than traditional approaches. Three variations of the approach are presented, and their rate of convergence to the optimal max-min fairness solution is analyzed. In addition, we introduce and analyze approximate rate-based flow-control algorithms. We show that under certain conditions the approximate algorithms may converge faster. However, we show that the resulting flows may be substantially different from the flows dictated by the max-min fairness. We further demonstrate that the max-min fairness solution can be very sensitive to small changes, i.e., there are configurations in which an addition or deletion of a session with rate δ may change the allocation of another session by Ω(δ·2n/2), but by no more thanO(δ·2n). This implies that the max-min fairness criteria may provide a bad estimate of how far a set of flow allocations is from the optimal allocation.

NBBS traffic management overview

In this paper, we describe an integrated set of procedures used for bandwidth management and congestion control in high-speed packet-switched networks such as asynchronous transfer mode (ATM), which are part of IBM's Networking BroadBand Services (NBBS) architecture. These controls are designed to support a wide variety of services with different characteristics in the network and operate at different time scales: connection-level controls such as path selection, admission control and bandwidth allocation, and packet-level controls that discriminate between packets from different connections to support multiple levels of service guarantees. Connection-level controls are applied at connection setup time and are based on the connection characterization and the network state at that time. They perform efficient allocation of resources to ensure performance guarantees for connections while achieving high utilization of network resources. Various packet-level controls developed include access or rate control and intermediate node buffer management and scheduling. For connections that do not require explicit service guarantees, NBBS offers an available bit rate service. This service mostly relies on packet-level control in the form of an end-to-end rate-based flow control algorithm that regulates the flow of traffic into the network. This paper, in addition to providing an overview of the different mechanisms used for traffic management in NBBS, highlights how they interact to ensure efficient network operation.