On single-path network routing subject to max-min fair flow allocation (original) (raw)
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Maximum flow routing with weighted max-min fairness
2004
Max-min is an established fairness criteria for allocating bandwidth for flows. In this work we look at the combined problem of routing and bandwidth allocation such that the flow allocation for each connection will be maximized and fairness will be maintained. We use the weighted extension of the max-min criteria to allocate bandwidth proportionaly to the flows' demand. Our contribution is an algorithm which, for the first time, solve the combined routing and bandwidth allocation problem for the case where flows are allowed to be splitted along several paths. We use multi commodity flow (MCF) formulation which is solved using linear programming (LP) techniques. These building blocks are used by our algorithm to derive the required optimal routing and allocation.
Optimal multi-path routing and bandwidth allocation under utility max-min fairness
2009 17th International Workshop on Quality of Service, 2009
An important goal of bandwidth allocation is to maximize the utilization of network resources while sharing the resources in a fair manner among network flows. To strike a balance between fairness and throughput, a widely studied criterion in the network community is the notion of max-min fairness. However, the majority of work on max-min fairness has been limited to the case where the routing of flows has already been defined and this routing is usually based on a single fixed routing path for each flow. In this paper, we consider the more general problem in which the routing of flows, possibly over multiple paths per flow, is an optimization parameter in the bandwidth allocation problem. Our goal is to determine a routing assignment for each flow so that the bandwidth allocation achieves optimal utility max-min fairness with respect to all feasible routings of flows. We present evaluations of our proposed multi-path utility max-min fair allocation algorithms on a statistical traffic engineering application to show that significantly higher minimum utility can be achieved when multi-path routing is considered simultaneously with bandwidth allocation under utility maxmin fairness, and this higher minimum utility corresponds to significant application performance improvements.
Network optimization problems subject to max-min fair flow allocation
We propose a novel way to consider the max-min fairness (MMF) paradigm in traffic engineering. Since MMF appears as a reference model for a fair capacity allocation when the traffic flows are elastic and rates are adapted based on resource availability, we consider it as a requirement due to the way resources are shared by the transportation protocol, rather than the routing objective. In particular, we address the traffic engineering problem where, given a network topology with link capacities and a set of communications to route, we must select a single path for each communication so as to maximize a network utility function, assuming a MMF bandwidth allocation. We give a compact mixed-integer linear programming formulation as well as a restricted path model. Computational experiments show that the exact formulation can be solved in a reasonable amount of computing time for medium-size networks and that the restricted path model provides solutions of comparable quality much faster.
A Mathematical Model for Efficient and Fair Resource Assignment in Multipath Transport
Future Internet
Multipath transport protocols are aimed at increasing the throughput of data flows as well as maintaining fairness between users, which are both crucial factors to maximize user satisfaction. In this paper, a mixed (non)linear programming (MINLP) solution is developed which provides an optimum solution to allocate link capacities in a network to a number of given traffic demands considering both the maximization of link utilization as well as fairness between transport layer data flows or subflows. The solutions of the MINLP formulation are evaluated w. r. t. their throughput and fairness using well-known metrics from the literature. It is shown that network flow fairness based capacity allocation achieves better fairness results than the bottleneck-based methods in most cases while yielding the same capacity allocation performance.
Utility max–min fair resource allocation for communication networks with multipath routing
Computer Communications, 2009
This paper considers the flow control and resource allocation problem as applied to the generic multipath communication networks with heterogeneous applications. We propose a novel distributed algorithm, show and prove that among all the sources with positive increasing and bounded utilities (no need to be concave) in steady state, the utility max-min fairness is achieved, which is essential for balancing QoS (Quality of Service) for different applications. By combining the first order Lagrangian method and filtering mechanism, the adopted approach eliminates typical oscillation behavior in multipath networks and possesses a rapid convergence property. In addition, the algorithm is capable of deciding the optimal routing strategy and distributing the total traffic evenly out of the available paths. The performance of our utility max-min fair flow control algorithm is evaluated through simulations under two representative case studies, as well as the real implementation issues are addressed deliberately for the practical purpose.
Centralized and Distributed Algorithms for Routing and Weighted Max-Min Fair Bandwidth Allocation
IEEE/ACM Transactions on Networking, 2000
Given a set of demands between pairs of nodes, we examine the traffic engineering problem of flow routing and fair bandwidth allocation where flows can be split to multiple paths (e.g., MPLS tunnels). This paper presents an algorithm for finding an optimal and global percommodity max-min fair rate vector in a polynomial number of steps. In addition, we present a fast and novel distributed algorithm where each source router can find the routing and the fair rate allocation for its commodities while keeping the locally optimal maxmin fair allocation criteria. The distributed algorithm is a fully polynomial epsilon-approximation (FPTAS) algorithm and is based on a primal-dual alternation technique. We implemented these algorithms to demonstrate its correctness, efficiency, and accuracy.
2005
Given a set of demands between pairs of nodes, we examine the Traffic Engineering problem of maximal flow routing and fair bandwidth allocation where flows can be split to multiple paths (e.g., MPLS tunnels). In the past we presented a polynomial solution for this problem but its complexity makes it hard to implement for large problem sizes. Thus, this paper presents a fully polynomial epsilon-approximation (FPTAS) algorithm for the max-min fair allocation problem which is based on a primal-dual alternation technique. In addition we present a fast and novel distributed algorithm where each source router can find the routing and the fair rate allocation for its commodities. We implemented the centralized algorithm to demonstrate its correctness, efficiency, and accuracy.
Bandwidth Allocation with Fairness in Multipath Networks
International Journal of Computer and Communication Engineering, 2017
Network resource management and traffic engineering are important subjects in today's Internet. In terms of traffic engineering, bandwidth allocation and splitting it in a fair manner among different users have become challenging. In addition, optimizing the utilization of network resources, increasing the user utility and throughput are also considerable. So, the user satisfaction with regard to the resource allocation and Quality of Service (QoS) are the most important factors that should be taken into the consideration. At the first step, Network Utility Maximization (NUM) problem has been considered as an initial stage to design any traffic engineering method. In this paper and by considering the mentioned issues, first of all we take into account the NUM problem and optimization decomposition methods by focusing on Traffic Management Using Multipath Protocol (TRUMP), and its weaknesses to tackle the fair resource allocation problem associated with it. We then propose a model to tackle the fair bandwidth allocation issue by implementing an optimized sending rate adaptation model using an intuitive investment method to optimize the link prices (delay and loss) to achieve an efficient fair bandwidth allocation model. The model is evaluated by using different simulations and different topologies under various network conditions. Our results show that the proposed model behaves fairer than TRUMP in certain path selections. As an average from the results and at a minimum point our model achieves 26% improvement in fairness in contrast to TRUMP. In addition, for large networks we can enjoy approximately 90% improvement in fairness measure.
Algorithms for Theoretical Investigation of Fairness in Multipath Transport
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2015
With the onset of multipath transport protocols such as MPTCP and multihomed mobile devices, fairness considerations which have been widely analyzed for legacy TCP need to be re-investigated. A practical realization of fairness amongst different participants is known to be difficult but even the theoretical calculation of the resource capacity and its allocation is not a trivial task. Therefore in this work, resource allocation algorithms are presented to thoroughly evaluate the impact of the fairness definitions. For a rigorous analysis, existing fairness definitions are identified according to the resources (bottleneck or network) and the competing participants (flow, tariff or user). Tariff as the participant, provides a realistic option to comply with the service level agreement between the operator and the user where as flow as the participant leads to TCP-compatible allocation. From the obtained results, it can be seen that if fairness is applied at the bottleneck then it is absolutely fair to the individual participants w.r.t. the bottleneck. On the other hand, fairness mechanisms considering the whole network as a single resource exploit the freedom of resource allocation (due to multipath flows) to achieve an overall similar allocation for the different participants (irrespective if the participant is composed of singlepath or multipath flows) but are still restricted by the topological constraints and might even result in a lower overall network throughput. 3
A tutorial on max-min fairness and its applications to routing, load-balancing and network design
… Research, Innovation and Vision for the …, 2006
This tutorial is devoted to the notion of Max-Min Fairness (MMF), associated optimization problems, and their applications to multi-commodity flow networks. We first introduce a theoretical background for the MMF problem and discuss its relation to lexicographic optimization. We next present resolution algorithms for the MMF optimization, and then give some applications to telecommunication networks, more particularly to routing, load-balancing, and network design.