A low-state packet marking framework for approximate fair bandwidth allocation

Misbehaving, non-congestion-reactive traffic is on the rise in the Internet. One way to control misbehaving traffic is to enforce local fairness among flows. Locally fair policies, such as fair-queueing and other fair AQM schemes, are inadequate to simultaneously control misbehaving traffic and provide high network utilization. We thus need to enforce globally fair bandwidth allocations. However, such schemes have typically been stateful and complex to implement and deploy. In this letter, we present a low state, lightweight scheme based on stateless fair packet marking at network edges followed by RIO queueing at core nodes, to control misbehaving flows with more efficient utilization of network bandwidth. Additionally, with low-state feedback from bottleneck routers, we show that, in practice, we can approximate global max-min fairness within an island of routers. We show, using simulations, that we can indeed control misbehaving flows and provide more globally fair bandwidth allocation.     

The impact of multicast layering on network fairness

Many definitions of fairness for multicast networks assume that sessions are single rate, requiring that each multicast session transmits data to all of its receivers at the same rate. These definitions do not account for multirate approaches, such as layering, that permit receiving rates within a session to be chosen independently. We identify four desirable fairness properties for multicast networks, derived from properties that hold within the max-min fair allocations of unicast networks. We extend the definition of multicast max-min fairness to networks that contain multirate sessions, and show that all four fairness properties hold in a multirate max-min fair allocation, but need not hold in a single-rate max-min fair allocation. We then show that multirate max-min fair rate allocations can be achieved via intra-session coordinated joins and leaves of multicast groups. However, in the absence of coordination, the resulting max-min fair rate allocation uses link bandwidth inefficiently, and does not exhibit some of the desirable fairness properties. We evaluate this inefficiency for several layered multirate congestion control schemes, and find that, in a protocol where the sender coordinates joins, this inefficiency has minimal impact on desirable fairness properties. Our results indicate that sender-coordinated layered protocols show promise for achieving desirable fairness properties for allocations in large-scale multicast networks     

Computing Optimal Max-Min Fair Resource Allocation for Elastic Flows

In this paper, we consider the max-min fair resource allocation problem as applied to elastic flows. We are interested in computing the optimal max-min fair rate allocation. The proposed approach is a linear programming based one and allows the computation of optimal routing paths with regard to max-min fairness, in stable and known traffic conditions. We consider non-bounded access rates, but we show how the proposed approach can handle the case of upper-bounded access rates. A proof of optimality and some computational results are also presented     

Fairness and Load Balancing in Wireless LANs Using Association Control

The traffic load of wireless LANs is often unevenly distributed among the access points (APs), which results in unfair bandwidth allocation among users. We argue that the load imbalance and consequent unfair bandwidth allocation can be greatly reduced by intelligent association control. In this paper, we present an efficient solution to determine the user-AP associations for max-min fair bandwidth allocation. We show the strong correlation between fairness and load balancing, which enables us to use load balancing techniques for obtaining optimal max-min fair bandwidth allocation. As this problem is NP-hard, we devise algorithms that achieve constant-factor approximation. In our algorithms, we first compute a fractional association solution, in which users can be associated with multiple APs simultaneously. This solution guarantees the fairest bandwidth allocation in terms of max-min fairness. Then, by utilizing a rounding method, we obtain the integral solution from the fractional solution. We also consider time fairness and present a polynomial-time algorithm for optimal integral solution. We further extend our schemes for the on-line case where users may join and leave dynamically. Our simulations demonstrate that the proposed algorithms achieve close to optimal load balancing (i.e., max-min fairness) and they outperform commonly used heuristics.     

Bandwidth sharing: objectives and algorithms

This paper concerns the design of distributed algorithms for sharing network bandwidth resources among contending flows. The classical fairness notion is the so-called max-min fairness. The alternative proportional fairness criterion has recently been introduced by F. Kelly (see Eur. Trans. Telecommun., vol.8, p.33-7, 1997); we introduce a third criterion, which is naturally interpreted in terms of the delays experienced by ongoing transfers. We prove that fixed-size window control can achieve fair bandwidth sharing according to any of these criteria, provided scheduling at each link is performed in an appropriate manner. We then consider a distributed random scheme where each traffic source varies its sending rate randomly, based on binary feedback information from the network. We show how to select the source behavior so as to achieve an equilibrium distribution concentrated around the considered fair rate allocations. This stochastic analysis is then used to assess the asymptotic behavior of deterministic rate adaption procedures     

Utility Max-Min Flow Control Using Slope-Restricted Utility Functions

We present a network architecture for the distributed utility max-min flow control of elastic and nonelastic flows where utility values of users (rather than data rates of users) are enforced to achieve max-min fairness. The proposed link algorithm converges to utility max-min fair bandwidth allocation in the presence of round-trip delays without using the information of users' utility functions. To show that the proposed algorithm can be stabilized not locally but globally, we found that the use of nonlinear control theory is inevitable. Even though we use a distributed flow-control algorithm, it is shown that any kind of utility function can be used as long as the minimum slopes of the functions are greater than a certain positive value. Though our analysis is limited to the single-bottleneck and homogeneous-delay case, we believe that the proposed algorithm is the first to achieve utility max-min fairness with guaranteed stability in a distributed manner     

Application-Oriented Flow Control: Fundamentals, Algorithms and Fairness

This paper is concerned with flow control and resource allocation problems in computer networks in which real-time applications may have hard quality of service (QoS) requirements. Recent optimal flow control approaches are unable to deal with these problems since QoS utility functions generally do not satisfy the strict concavity condition in real-time applications. For elastic traffic, we show that bandwidth allocations using the existing optimal flow control strategy can be quite unfair. If we consider different QoS requirements among network users, it may be undesirable to allocate bandwidth simply according to the traditional max-min fairness or proportional fairness. Instead, a network should have the ability to allocate bandwidth resources to various users, addressing their real utility requirements. For these reasons, this paper proposes a new distributed flow control algorithm for multiservice networks, where the application's utility is only assumed to be continuously increasing over the available bandwidth. In this, we show that the algorithm converges, and that at convergence, the utility achieved by each application is well balanced in a proportionally (or max-min) fair manner     

Centralized and Distributed Algorithms for Routing and Weighted Max-Min Fair Bandwidth Allocation

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 per-commodity 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 max-min 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.      

Throughput-based fair bandwidth allocation in OBS networks

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max-min fairness in traditional IP networks to the fair-loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput-based-FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.     

Cross-Layer Design for End-to-End Throughput and Fairness Enhancement in Multi-Channel Wireless Mesh Networks

In this paper, we study joint rate control, routing and scheduling in multi-channel wireless mesh networks (WMNs), which are traditionally known as transport layer, network layer and MAC layer issues respectively. Our objective is to find a rate allocation along with a flow allocation and a transmission schedule for a set of end-to-end communication sessions such that the network throughput is maximized, which is formally defined as the maximum throughput rate allocation (MRA) problem. As simple throughput maximization may result in a severe bias on rate allocation, we take account of fairness based on a simplified max-min fairness model and the proportional fairness models. We define the max-min guaranteed maximum throughput rate allocation (MMRA) problem and proportional fair rate allocation (PRA) problem. We present efficient linear programming (LP) and convex programming (CP) based schemes to solve these problems. Numerical results show that proportional fair rate allocation schemes achieves a good tradeoff between throughput and fairness.     

An active queue management scheme based on a capture-recapture model

One of the challenges in the design of switches/routers is the efficient and fair use of the shared bottleneck bandwidth among different Internet flows. In particular, various active queue management (AQM) schemes have been developed to regulate transmission control protocol traffic in response to router congestion. In addition, in order to provide fair bandwidth sharing, these AQM must protect the well-behaved flows from the misbehaving flows. However, most of the existing AQM schemes cannot provide accurate fair bandwidth sharing while being scalable. The key to the scalability and fairness of the AQM schemes is the accurate estimation of certain network resources without keeping too much state information. We propose a novel technique to estimate two network resource parameters: the number of flows in the buffer and the data source rate of a flow by using a capture-recapture (CR) model. The CR model depends on simply the random capturing/recapturing of the incoming packets, and as a result, it provides a good approximation tool with low time/space complexity. These network resource parameters are then used to provide fair bandwidth sharing among the Internet flows. Our experiments and analysis will demonstrate that this new technique outperforms the existing mechanisms and closely approximates the "ideal" case, where full state information is needed.     

Session-aware popularity-based resource allocation for assureddifferentiated services

Differentiated services networks are fair in the way that different types of traffic can be associated to different network services, and so to different quality levels. However, fairness among flows sharing the same service, may, not be provided. Our goal is to study fairness between scalable multimedia sessions for assured DS services in a multicast network environment. To achieve this goal, we present a fairness mechanism called session-aware popularity-based resource allocation (SAPRA), which allocates resources to scalable. sessions based on their number of receivers. Simulation results in a scalable and multireceiver scenario show that SAPRA maximizes the utilization, of bandwidth and the number of receivers with high-quality reception     

基于PII控制器的XCP带宽补偿算法

 XCP在多瓶颈网络中存在缺陷,利用率和公平性显著下降.本文根据控制论中的反馈补偿原理,提出一个基于PII控制器的XCP带宽补偿算法.仿真实验表明该带宽补偿算法能够有效消除XCP在多瓶颈网络中的缺陷,各条链路都能够获得100％的利用率,各条瓶颈流都能够获得最大最小公平带宽.     

Fair Bandwidth Allocation Using Effective Multicast Traffic Share in TDM-PONs

In this paper, the effects of optical traffic-sharing on the performance of multicast video delivery in terms of the efficiency of bandwidth allocation and the fairness of link-sharing are discussed for the downstream direction of a time-division-multiplexed passive optical network (TDM-PON). We analyze the practical issues associated with multicast packet switching and transmission control in a TDM-PON and also propose a fair bandwidth allocation mechanism, called share-based proportional bandwidth allocation (S-PBA), to effectively support multicast services. In order to provide an optical network unit with a fair amount of link bandwidth and high throughput independent of traffic type, S-PBA arbitrates the amount of unicast timeslot by using effective multicast traffic share, which is determined based on multicast traffic load distribution and traffic-sharing density. Analytic and simulation results clearly validate the effectiveness of the proposed mechanism. This work is applicable to multicast video delivery or multicast traffic transmission in general, such as voice traffic, or a combination of both in the case of video conferencing, for example.     

Fair Bandwidth Allocation in Optical Burst Switching Networks

Optical burst switching (OBS) is a promising switching technology for next-generation Internet backbone networks. One of the design challenges is how to provide fair bandwidth allocation in OBS networks; the schemes proposed for general store-and-forward IP switching networks can not be used because of the non-buffering and un-fully utilized bandwidth characteristics of OBS networks. We propose a rate fairness preemption (RFP) scheme to achieve approximately weighted max-min fair bandwidth allocation in OBS networks. We present an analysis of the burst loss probability in RFP-based OBS networks. The analysis and simulation results show that the RFP scheme provides fair bandwidth allocation in OBS networks.      

Dynamic bandwidth allocation with fair scheduling for WCDMA systems

Dynamic bandwidth allocation (DBA) will play an important role in future broadband wireless networks, including the 3G and 4G WCDMA systems. A code-division generalized processor sharing (CDGPS) fair scheduling DBA scheme is proposed for WCDMA systems. The scheme exploits the capability of the WCDMA physical layer, reduces the computational complexity in the link layer, and allows channel rates to be dynamically and fairly scheduled in response to the variation of traffic rates. Deterministic delay bounds for heterogeneous packet traffic are derived. Simulation results show that the proposed CDGPS scheme is effective in supporting differentiated QoS, while achieving efficient utilization of radio resources.     

FEBA: A Bandwidth Allocation Algorithm for Service Differentiation in IEEE 802.16 Mesh Networks

In wireless mesh networks, the end-to-end throughput of traffic flows depends on the path length, i.e., the higher the number of hops, the lower becomes the throughput. In this paper, a fair end-to-end bandwidth allocation (FEBA) algorithm is introduced to solve this problem. FEBA is implemented at the medium access control (MAC) layer of single-radio, multiple channels IEEE 802.16 mesh nodes, operated in a distributed coordinated scheduling mode. FEBA negotiates bandwidth among neighbors to assign a fair share proportional to a specified weight to each end-to-end traffic flow. This way traffic flows are served in a differentiated manner, with higher priority traffic flows being allocated more bandwidth on the average than the lower priority traffic flows. In fact, a node requests/grants bandwidth from/to its neighbors in a round-robin fashion where the amount of service depends on both the load on its different links and the priority of currently active traffic flows. If multiple channels are available, they are all shared evenly in order to increase the network capacity due to frequency reuse. The performance of FEBA is evaluated by extensive simulations. It is shown that wireless resources are shared fairly among best-effort traffic flows, while multimedia streams are provided with a differentiated service that enables quality of service.     

Ad hoc网络基于公平的带宽分配机制研究

Ad hoc网络是一种没有固定基础设施,由多个带有无线收发装置的移动终端组成的多跳临时性自治系统。它独特的个性决定了各数据流之间要竞争共享的有限带宽资源。因此,为了保证Ad hoc网络业务的服务质量,合理的带宽分配机制至关重要。介绍了无线Ad hoc网络的网络模型,对带宽分配机制的定义及约束条件进行描述分析,然后从公平的角度详细地分析了目前Ad hoc网络的带宽分配机制,并总结了各种分配机制的优缺点。     

Bandwidth sharing and admission control for elastic traffic

We consider the performance of a network like the Internet handling so‐called elastic traffic where the rate of flows adjusts to fill available bandwidth. Realized throughput depends both on the way bandwidth is shared and on the random nature of traffic. We assume traffic consists of point to point transfers of individual documents of finite size arriving according to a Poisson process. Notable results are that weighted sharing has limited impact on perceived quality of service and that discrimination in favour of short documents leads to considerably better performance than fair sharing. In a linear network, max–min fairness is preferable to proportional fairness under random traffic while the converse is true under the assumption of a static configuration of persistent flows. Admission control is advocated as a necessary means to maintain goodput in case of traffic overload. This revised version was published online in June 2006 with corrections to the Cover Date.     

Dynamic fair scheduling with QoS constraints in multimedia wideband CDMA cellular networks

A class of dynamic fair scheduling schemes based on the generalized processor sharing (GPS) fair service discipline, under the generic name code-division GPS (CDGPS), is proposed for a wideband direct-sequence code-division multiple-access (CDMA) cellular network to support multimedia traffic. The CDGPS scheduler makes use of both the traffic characteristics in the link layer and the adaptivity of the wideband CDMA physical layer to perform fair scheduling on a time-slot by time-slot basis, by using a dynamic rate-scheduling approach rather than the conventional time-scheduling approach. Soft uplink capacity is characterized for designing an efficient CDGPS resource allocation procedure. A credit-based CDGPS (C-CDGPS) scheme is proposed to further improve the utilization of the soft capacity by trading off the short-term fairness. Theoretical analysis shows that, with the C-CDGPS scheme, tight delay bounds can be provided to delay-sensitive traffic, and short-term unfairness can be bounded so that long-term weighted fairness for all users can still be satisfied. Simulation results show that bounded delays, increased throughput, and long-term fairness can be achieved for both homogeneous and heterogeneous traffic.