Multipath Utility Research Articles

A Family of Stable Multipath Dual Congestion Control Algorithms

We consider the problem of multipath congestion control in the Internet. The aim is to take advantage of multiple paths diversity to achieve efficient bandwidth allocation and improve network efficiency. But there exist some potential difficulties when one directly uses the well-known network utility maximization model to design stable multipath congestion control algorithms for the alternative paths. In this paper, we propose a generalized multipath utility maximization model to consider the problem of joint routing and rate control, which can be reduced to specific models with different parameter settings. And then we develop a family of multipath dual congestion control algorithms which are stable in the absence of delays. We also derive decentralized and scalable sufficient conditions for a particular scheme when propagation delays exist in networks. The simulation results show that the proposed multipath dual congestion control algorithms with appropriate parameter settings can achieve stable resource shares while maintaining fairness among the involved users.

A family of multi-path congestion control algorithms with global stability and delay robustness

The goal of traffic management is to efficiently allocate network resources via adjustment of source transmission rates and routes selection. Mathematically, it aims to solve a traditional utility maximization problem in a fair and distributed manner. In this paper, we first develop a generalized multi-path utility maximization problem which features a weighted average of the classical Kelly’s formulation and the Voice’s model. Next, we design from this broader framework a family of multi-path dual congestion control algorithms whose equilibrium point can both achieve a desired bandwidth utilization and preserve a notion of fairness among competing users. Global stability can be guaranteed for the proposed schemes in the absence of delays by use of a totally novel Lyapunov function. Moreover, when heterogeneous propagation delays are taken into account, we establish decentralized and scalable sufficient conditions for robust global stability by constructing a reasonable Lyapunov–Krasovskii functional candidate. These conditions give estimates for the maximum admissible delays that the controller can tolerate without losing stability. Finally, we verify the results through simulation.

Multi-path utility maximization and multi-path TCP design

The canonical multi-path network utility maximization (NUM) model which is extended directly from the single-path NUM has been studied widely in the literature. Most of the previous approaches do not specify the case of subflows on paths with different characteristics. Moreover, the transport protocol derived from the canonical multi-path NUM exhibits flappiness in the subflows because of the non-strictly convexity of the optimization problem.This paper introduces a modified multi-path NUM model and proposes a novel approach to overcome the mentioned issues. Using Jensen’s inequality, the multi-path NUM is approximated to a strictly convex and separable problem which can be solved efficiently by dual-based decomposition method. The algorithm successively solving a sequence of approximation problems is proven to converge at the global optimum of the original problem. Moreover, considering the separable form of the approximation utility and the dual-based nature of the proposed algorithm, the reverse engineering frameworks of the current TCPs are used to develop a series of multi-path TCPs that are compatible with corresponding regular single-path TCPs.

LBMP: A Logarithm-Barrier-Based Multipath Protocol for Internet Traffic Management

Traffic management is the adaptation of source rates and routing to efficiently utilize network resources. Recently, the complicated interactions between different Internet traffic management modules have been elegantly modeled by distributed primal-dual utility maximization, which sheds new light for developing effective management protocols. For single-path routing with given routes, the dual is a strictly concave network optimization problem. Unfortunately, the general form of multipath utility optimization is not strictly concave, making its solution quite unstable. Decomposition-based techniques like TRaffic-management Using Multipath Protocol (TRUMP) alleviates the instability, but their convergence is not guaranteed, nor is their optimality. They are also inflexible in differentiating the control at different links. In this paper, we address the above issues through a novel logarithm-barrier-based approach. Our approach jointly considers user utility and routing/congestion control. It translates the multipath utility maximization into a sequence of unconstrained optimization problems, with infinite logarithm barriers being deployed at the constraint boundary. We demonstrate that setting up barriers is much simpler than choosing traditional cost functions and, more importantly, it makes optimal solution achievable. We further demonstrate a distributed implementation, together with the design of a practical Logarithm Barrier-based-Multipath Protocol (LBMP). We evaluate the performance of LBMP through both numerical analysis and packet-level simulations. The results show that LBMP achieves high throughput and fast convergence over diverse representative network topologies. Such performance is comparable to TRUMP, and is often better. Moreover, LBMP is flexible in differentiating the control at different links, and its optimality and convergence are theoretically guaranteed.

MPCC: Optimal Congestion Control for Multipath Routing in Ad Hoc Networks

Based on the inherent characteristic of the contention relationship between flows in Ad hoc networks,a notion of the link's interference set is introduced,it extends the multipath utility maximization formulating the congestion control problem for multipath routing in Internet to that in Ad hoc networks.As the objective function is not strictly concave in the path rate,the penalty function method is applied to transform the primal problem into a new formulation to obtain the optimal solution based on the subgradient method.And the multiPath congestion control algorithm(MPCC) is also proposed.It can be implemented in a parallel fashion at each source/link.Simulation results show that MPCC can quickly quickly converge to globally optimal solutions;and,compared to the additive-increase-multiplicative-decrease(AIMD) algorithm in TCP-Reno,MPCC is more adaptive to time-varying network situations,and achieves better network performance.And thus it can be used to the practical Ad hoc networks.

Utility Maximization for Communication Networks With Multipath Routing

In this paper, we study utility maximization problems for communication networks where each user (or class) can have multiple alternative paths through the network. This type of multi-path utility maximization problems appear naturally in several resource allocation problems in communication networks, such as the multi-path flow control problem, the optimal quality-of-service (QoS) routing problem, and the optimal network pricing problem. We develop a distributed solution to this problem that is amenable to online implementation. We analyze the convergence of our algorithm in both continuous-time and discrete-time, and with and without measurement noise. These analyses provide us with guidelines on how to choose the parameters of the algorithm to ensure efficient network control.