Efficiency-fairness tradeoff in telecommunications networks

Introducing the concept of /spl alpha/-fairness, which allows for a bounded fairness compromise, so that no source is allocated less than a fraction /spl alpha/ of its fair share, this letter studies tradeoffs between efficiency (utilization, throughput or revenue) and fairness in a general telecommunications network with relation to any fairness criterion. We formulate a linear program that finds the optimal bandwidth allocation by maximizing efficiency subject to /spl alpha/-fairness constraints. This leads to what we call an efficiency-fairness curve, which shows the benefit in efficiency as a function of the extent to which fairness is compromised.     

Pricing in multiservice loss networks: static pricing, asymptoticoptimality and demand substitution effects

We consider a communication network with fixed routing that can accommodate multiple service classes, differing in bandwidth requirements, demand pattern, call duration and routing. The network charges a fee per call which can depend on the current congestion level and which affects user's demand. Building on the single-node results of I.Ch. Paschalidis and J.N. Tsitsiklis (see IEEE/ACM Trans. Networking, vol.8, p.171-84, 2000), we consider both problems of revenue and of welfare maximization, and show that static pricing is asymptotically optimal in a regime of many, relatively small, users. In particular, the performance of an optimal (dynamic) pricing strategy is closely matched by a suitably chosen class-dependent static price, which does not depend on instantaneous congestion. This result holds even when we incorporate demand substitution effects into the demand model. More specifically, we model the situation where price increases for a class of service might lead users to use another class as an imperfect substitute. For both revenue and welfare maximization objectives we characterize the structure of the asymptotically optimal static prices, expressing them as a function of a parsimonious number of parameters. We employ a simulation-based approach to tune those parameters and to compute efficiently an effective policy away from the limiting regime. Our approach can handle large, realistic, instances of the problem     

一种具有弹性服务质量要求的多业务最优接纳控制策略

随着无线网络所支持的业务种类的增加和具有弹性服务质量要求的业务的大量出现，与服务质量保证密切相关的呼叫接纳控制问题成了近年来无线网络研究的热点之一。本文研究了基于准马尔可夫决策过程方法的多业务最优呼叫接纳控制问题。根据业务的特点，首先引入了带宽分配满意度函数和收益率函数，在此基础上，提出了基于带宽分配满意度的最优带宽分配算法和基于准马尔可夫决策过程方法的最优呼叫接纳控制策略。计算结果表明，本文方案能够在对各类业务的呼叫阻塞率进行适当权衡的前提下，进一步提高网络的期望收益率和期望带宽利用率，同时满足了各类业务的最低服务质量要求。     

Optimized bandwidth allocation with fairness and service differentiation in multimedia wireless networks

In this article we present an optimal Markov Decision‐based Call Admission Control (MD‐CAC) policy for the multimedia services that characterize the next generation of wireless cellular networks. A Markov decision process (MDP) is used to represent the CAC policy. The MD‐CAC is formulated as a linear programming problem with the objectives of maximizing the system utilization while ensuring class differentiation and providing quantitative fairness guarantees among different classes of users. Through simulation, we show that the MD‐CAC policy potentially achieves the optimal decisions. Hence our proposed MD‐CAC policy satisfies its design goals in terms of call‐class‐differentiation, fairness and system utilization. Copyright © 2006 John Wiley & Sons, Ltd.     

A game theoretic framework for bandwidth allocation and pricing inbroadband networks

In this paper, we present a game theoretic framework for bandwidth allocation for elastic services in high-speed networks. The framework is based on the idea of the Nash bargaining solution from cooperative game theory, which not only provides the rate settings of users that are Pareto optimal from the point of view of the whole system, but are also consistent with the fairness axioms of game theory. We first consider the centralized problem and then show that this procedure can be decentralized so that greedy optimization by users yields the system optimal bandwidth allocations. We propose a distributed algorithm for implementing the optimal and fair bandwidth allocation and provide conditions for its convergence. The paper concludes with the pricing of elastic connections based on users' bandwidth requirements and users' budget. We show that the above bargaining framework can be used to characterize a rate allocation and a pricing policy which takes into account users' budget in a fair way and such that the total network revenue is maximized     

Enabling seamless multimedia wireless access through QoS‐based bandwidth adaptation

Effective support of real‐time multimedia applications in wireless access networks, viz. cellular networks and wireless LANs, requires a dynamic bandwidth adaptation framework where the bandwidth of an ongoing call is continuously monitored and adjusted. Since bandwidth is a scarce resource in wireless networking, it needs to be carefully allocated amidst competing connections with different Quality of Service (QoS) requirements. In this paper, we propose a new framework called QoS‐adaptive multimedia wireless access (QoS‐AMWA) for supporting heterogeneous traffic with different QoS requirements in wireless cellular networks. The QoS‐AMWA framework combines the following components: (i) a threshold‐based bandwidth allocation policy that gives priority to handoff calls over new calls and prioritizes between different classes of handoff calls by assigning a threshold to each class, (ii) an efficient threshold‐type connection admission control algorithm, and (iii) a bandwidth adaptation algorithm that dynamically adjusts the bandwidth of an ongoing multimedia call to minimize the number of calls receiving lower bandwidth than the requested. The framework can be modeled as a multi‐dimensional Markov chain, and therefore, a product‐form solution is provided. The QoS metrics—new call blocking probability (NCBP), handoff call dropping probability (HCDB), and degradation probability (DP)—are derived. The analytical results are supported by simulation and show that this work improves the service quality by minimizing the handoff call dropping probability and maintaining the bandwidth utilization efficiently. Copyright © 2006 John Wiley & Sons, Ltd.     

Proportional degradation services in wireless/mobile adaptive multimedia networks

Adaptive multimedia services are very attractive since resources in wireless/mobile networks are relatively scarce and widely variable, and more importantly the resource fluctuation caused by mobility and channel fading can be mitigated using adaptive services. Therefore, there are extensive research activities on Quality of Service (QoS), call admission control, as well as bandwidth degradation and adaptation for adaptive multimedia services in wireless/mobile networks in recent years. However, fairness of bandwidth degradation has largely been ignored in previous work and remains an important issue in adaptive multimedia service provisioning. In this paper, we propose and study proportional degradation service provisioning in wireless/mobile networks that offer multiple classes of adaptive multimedia services. The proposed proportional degradation fairness model guarantees the proportional bandwidth degradation among different classes of services. Two proportional degradation scenarios are studied in this paper. In the first scenario, we study the proportional degradation provisioning with two QoS parameters for adaptive multimedia: the degradation ratio (DR) and the degradation degree (DD). In the second scenario, we study the proportional degradation provisioning with a new QoS parameter for adaptive multimedia: the degradation area (DA). For each scenario, based on the QoS parameters, proportional degradation adaptation algorithms are proposed to approximate the proportional degradation model, to fairly adapt calls' degradations, to utilize the system resource efficiently, as well as to optimize QoS parameters. Performance studies show that in the first scenario, proportional DR has been achieved very well, whereas proportional DD has not been well achieved. In other words, DR outperforms DD in terms of proportional degradation. In the second scenario, proportional DA has been well achieved. Furthermore, bandwidth resources have been efficiently utilized and DA has been minimized. Copyright © 2004 John Wiley & Sons, Ltd.     

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.     

A call admission control for service differentiation and fairness management in WDM grooming networks

We investigate a call admission control (CAC) mechanism for providing fairness control and service differentiation in a WDM network with grooming capabilities. A WDM grooming network can handle different classes of traffic streams which differ in their bandwidth requirements. We assume that for each class, call interarrival and holding times are exponentially distributed. Using a Markov Decision Process approach, an optimal CAC policy is derived for providing fairness in the network. The Policy Iteration algorithm is used to numerically compute the optimal policy. Furthermore, we propose a heuristic decomposition algorithm with lower computational complexity and good performance. Simulation results compare the performance of our proposed policy with those of Complete Sharing and Complete Partitioning policies. Comparisons show that our proposed policy provides the best performance in most cases. Although this approach is motivated by WDM networks, it may be deployed to determine the optimal resource allocation in many problems in wireless and wired telecommunications systems.     

A comprehensive resource management framework for next generation wireless networks

We propose an integrated resource management approach that can be implemented in next generation wireless networks that support multimedia services (data, voice, video, etc.). Specifically, we combine the use of position-assisted and mobility predictive advanced bandwidth reservation with a call admission control and bandwidth reconfiguration strategy to support flexible QoS management. We also introduce a mobile agent based framework that can be used to carry out the functions of geolocation and of the proposed resource management in wireless networks. A model is also developed to obtain the optimal location information update interval in order to minimize the total cost of the system operation. The comparison of the achievable performance results of our proposed scheme with the corresponding results of a conventional system that supports advanced bandwidth reservation only, as means of supporting the QoS requirements, demonstrate that our integrated scheme can alleviate the problem of overreservation, support seamless operation throughout the wireless network, and increase significantly the system capacity.     

An optimization framework for balancing throughput and fairness in wireless networks with QoS support

Quality-of-service (QoS) provisioning, high system throughput, and fairness assurance are indispensable for heterogeneous traffic in future wireless broadband networks. With limited radio resources, increasing system throughput and maintaining fairness are conflicting performance metrics, leading to a natural tradeoff between these two measures. Balancing system throughput and fairness is desired. In this paper, we consider an interference-limited wireless network, and derive a generic optimization framework to obtain an optimal relationship of system throughput and fairness with QoS support and efficient resource utilization, by introducing the bargaining floor. From the relationship curve, different degrees of performance tradeoff between throughput and fairness can be obtained by choosing different bargaining floors. In addition, our framework facilitates call admission control to effectively guarantee QoS of. multimedia traffic. The solutions of resource allocation obtained from the optimization framework achieve the pareto optimality, demonstrating efficient use of network resources.     

QoS Provisioning in Wireless/Mobile Multimedia Networks Using an Adaptive Framework

Recently there is a growing interest in the adaptive multimedia networking where the bandwidth of an ongoing multimedia call can be dynamically adjusted. In the wireless/mobile multimedia networks using the adaptive framework, the existing QoS provisioning focused on the call blocking probability and the forced termination probability should be modified. We, therefore, redefine a QoS parameter – the cell overload probability – from the viewpoint of the adaptive multimedia networking. Then, we propose a distributed call admission control (CAC) algorithm that guarantees the upper bound of the cell overload probability. Also, a bandwidth adaptation algorithm which seeks to minimize the cell overload probability is also presented. Simulation experiments are carried out to verify the performance of the proposed CAC algorithm. Furthermore, the performance of the adaptive wireless/mobile network is compared to that of the existing non-adaptive wireless/mobile networks. As a further step in QoS provisioning, we propose another QoS parameter, the degradation period ratio, and discuss analytically how the CAC algorithm guarantees the upper bound of the degradation period ratio.     

A Prioritized Real-Time Wireless Call Degradation Framework for Optimal Call Mix Selection

This paper describes a framework for selecting the optimal call mix to be admitted while employing a bandwidth degradation policy in a wireless cellular network. The optimal property is achieved by maximizing the revenue generated by different calls in a cell for the service provider. By degradation, we mean that: (1) some channels can be taken away from ongoing calls that are assigned multiple channels, and/or (2) newly admitted calls that require multiple channels get fewer than what they requested. To avoid removing more channels from calls than they could tolerate, we incorporate a new call attribute: the degradation tolerance, i.e., the number of channels a call can be degraded without sacrificing the acceptable level of quality. We also consider priorities over calls to influence the admission and/or degradation decision. Our analytical framework includes both static and dynamic scenarios. The dynamic case is enhanced with the ability to select the optimal call mix using incoming and departing handoffs, new calls, and call terminations in a recursive way, thus, resulting in a call admission policy. We also discuss how to accommodate non-real-time calls into our system. To evaluate the performance of the proposed scheme, a discrete event simulation tool has been developed that models our dynamic framework built on a customized simulated annealing optimization function. Simulation results demonstrate that not only does the proposed degradation framework maximize the total revenue generated by the admitted calls in the cells, but also reduce the handoff and new call blocking probabilities.     

Class-Based Service Connectivity Using Multi-level Bandwidth Adaptation in Multimedia Wireless Networks

Due to the fact that quality of service requirements are not very strict for all traffic types, more calls of higher priority can be accommodated by reducing some bandwidth allocation for the bandwidth adaptive calls. The bandwidth adaptation to accept a higher priority call is more than that of a lower priority call. Therefore, the multi-level bandwidth adaptation technique improves the overall forced call termination probability as well as provides priority of the traffic classes in terms of call blocking probability without reducing the bandwidth utilization. We propose a novel bandwidth adaptation model that releases multi-level of bandwidth from the existing multimedia traffic calls. The amount of released bandwidth is decided based on the priority of the requesting traffic calls and the number of existing bandwidth adaptive calls. This prioritization of traffic classes does not reduce the bandwidth utilization. Moreover, our scheme reduces the overall forced call termination probability significantly. The proposed scheme is modeled using the Markov Chain. The numerical results show that the proposed scheme is able to provide negligible handover call dropping probability as well as significantly reduced new call blocking probability of higher priority calls without increasing the overall forced call termination probability.     

Opportunistic call admission control for wireless broadband cognitive networks

Wireless Broadband Cognitive Networks (WBCN) are new trend to better utilization of spectrum and resources. However, in multiservice WBCN networks, call admission control (CAC) is a challenging point to effectively control different traffic loads and prevent the network from being overloaded and thus provide promised quality of service. In this paper, we propose a CAC framework and formulate it as an optimization problem, where the demands of both WBCN service providers and cognitive subscribers are taken into account. To solve the optimization problem, we developed an opportunistic multivariate CAC algorithm based on a joint optimization of utility, weighted fairness, and greedy revenue algorithms. Extensive simulation results show that, the proposed call admission control framework can meet the expectations of both service providers and subscribers in wireless broadband cognitive networks.     

Implied Costs for Multirate Wireless Networks

Implied costs for multirate wireless networks are calculated and their use is demonstrated for quantifying mobility, traffic load, call pricing, network optimization and for evaluating trade-offs between calls of different rates. User mobility is modeled by assigning call termination and call handoff probabilities. Fixed Channel Assignment (FCA) is used with priority for handoffs over new call arrivals by reserving a number of channels in all the cells. The performance measures used are new call blocking and handoff drop probabilities. The implied cost is calculated for the network net revenue, which considers the revenue generated by accepting a new call arrival into the network as well as the cost of a handoff drop in any cell. Simulation and numerical results are presented to show the accuracy of the model. The implied costs are used to suggest pricing techniques for different calls based on mobilities and bandwidth. Finally, a nonlinear constrained optimization problem is formulated to calculate the sum revenue for a given network by maximizing the net revenue using implied costs in a gradient descent algorithm. The implied cost analysis also shows that matching capacity distribution to not only exogenous traffic, but also to mobility can significantly increase revenue.     

Layered media multicast control (LMMC): rate allocation and partitioning

The objective of layering techniques of distributing multimedia traffic over multicast IP networks is to effectively cope with the challenges in continuous media applications. The challenges include heterogeneity, fairness, real-time constraints, and quality of service. We study the problem of rate allocation and receiver partitioning in layered and replicated media systems. We formulate an optimization problem aimed at maximizing a close approximation of the so-called max-min fairness metric subject to loss and bandwidth constraints. Our optimal layered media multicast control (LMMC) solution to the problem analytically determines the layer rates and the corresponding partitioning of the receivers. Our simulation results show the effectiveness of our proposed solution in realistic scenarios.     

Measurement-based TFRC: improving TFRC in heterogeneous mobile networks

As a well-known multimedia stream transport protocol, TFRC provides smooth transfer rate under stable network conditions, and achieves good fairness to TCP. However, it is not flexible in heterogeneous mobile networks because the available bandwidth varies rapidly. This paper proposes a measurement based TFRC (MBTFRC) protocol, which uses passive bandwidth measurements at the receiver to improve the flexibility of TFRC. In addition, a window-based EWMA filter with two weights is used to achieve stability and fairness simultaneously. Simulation results verify the flexibility, stability and fairness of MBTFRC.     

Fair admission control scheme based on conditional preemption in traffic-groomed optical networks

In optical-grooming networks, the capacity fairness issue can be resolved by utilizing a call admission control mechanism. Existing call admission control schemes are generally based on one of the four different techniques, namely static bandwidth reservation (SBR), static threshold setting (STS), mathematical statistics (MS), and Markov decision processing without buffer implementation (NB). However, irrespective of the technique used, a tradeoff exists between the network fairness and the network throughput. Accordingly, this article presents a conditional-preemption call admission control (CP-CAC) scheme designed to increase the network throughput while simultaneously maintaining the fairness. The CP-CAC method is based on a dynamic threshold setting concept and is implemented using a single connection buffer (C-Buf) and a set of virtual buffers (V-Bufs). In general CAC mechanisms, if the residual bandwidth is sufficient to satisfy a new request but some requests are already buffered, the new request can be treated in two different modes, i.e. with-preemption (WP) or without-preemption (NP). In contrast, in the CP-CAC scheme proposed in this study, a conditional-preemption (CP) mode is proposed in which statistical information about the blocking probability is used to determine the preempt (or not) decision. The simulation results show that compared to the NB call admission control mechanism, the proposed CP-CAC scheme improves the network throughput without sacrificing the fairness. In addition, the average waiting time induced by the buffer implementation is just 0.25 time units. Finally, it is shown that the proposed method ensures fairness in a variety of common network topologies, including 6 × 6 mesh-torus, NSF, and Cost 239.     

基于最优化的多媒体多播速率控制

传输多媒体流的一种有效方法是采用多速率多播,但多速率多播的速率控制面临许多挑战,如异构性、公平性、实时性及服务质量(QoS)等。提出了一种两阶段优化的策略进行多媒体多播速率控制。把问题公式化为求系统效用最大化的最优化问题,推导出有效的算法。方法综合考虑了服务质量、异构性等,且满足协议间的公平性和多播会晤内各接收者间的公平性。仿真实验表明算法的有效性,与现有的算法相比系统总效用大大提高。