Long-term Fairness Research Articles

A Quality-Centric TCP-Friendly Congestion Control for Multimedia Transmission

In this paper, we propose a quality-centric congestion control for multimedia streaming over wired IP networks, which we refer to as media-TCP-friendly congestion control (MTCC). Our solution adapts the sending rate to both the network condition and the application characteristics by explicitly considering the distortion impacts, delay deadlines, and interdependencies of different video packet classes. The media-aware solution is able to provide differential services for transmitting various packet classes and thereby, further improves the multimedia streaming quality compared to the conventional network-aware congestion control. We use finite-horizon Markov decision process (FHMDP) to determine the optimal congestion control policy that maximizes the long-term multimedia quality, while adhering to the horizon- <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$K$</tex></formula> TCP-friendliness constraint, which ensures long-term fairness with existing TCP applications. Moreover, the proposed MTCC is able to achieve quality-based fairness among multimedia users. We derive sufficient conditions for multiple multimedia users to achieve quality-based fairness using MTCC congestion control. Note that the proposed solution only modifies the adaptation mechanism of the TCP congestion window size at the sender, without changing the design at the receiver side (i.e., each current TCP receiver can correctly receive and process MTCC streams). Our simulation results show that MTCC achieves more than 3 dB improvement in terms of PSNR over the conventional TCP congestion control approaches, with the largest improvements observed for real-time streaming applications requiring stringent playback delays.

On the Impact of TCP and Per-Flow Scheduling on Internet Performance

Internet performance is tightly related to the properties of TCP and UDP protocols, jointly responsible for the delivery of the great majority of Internet traffic. It is well understood how these protocols behave under first-in-first-out (FIFO) queuing and what are the network congestion effects. However, no comprehensive analysis is available when flow-aware mechanisms such as per-flow scheduling and dropping policies are deployed. Previous simulation and experimental results leave a number of unanswered questions. In this paper, we tackle this issue by modeling via a set of fluid nonlinear ordinary differential equations (ODEs) the instantaneous throughput and the buffer occupancy of N long-lived TCP sources under three per-flow scheduling disciplines (Fair Queuing, Longest Queue First, Shortest Queue First) and with longest queue drop buffer management. We study the system evolution and analytically characterize the stationary regime: Closed-form expressions are derived for the stationary throughput/sending rate and buffer occupancy, which give a thorough understanding of short/ long-term fairness for TCP traffic. Similarly, we provide the characterization of the loss rate experienced by UDP flows in the presence of TCP traffic. As a result, the analysis allows to quantify benefits and drawbacks related to the deployment of flow-aware scheduling mechanisms in different networking contexts. The model accuracy is confirmed by a set of ns2 simulations and by the evaluation of the three scheduling disciplines in a real implementation in the Linux kernel.

A study of QoS guarantee and fairness based on cross-layer channel state in Worldwide Interoperability for Microwave Access

Because the bandwidth usage of wireless transmission is limited, one of the major research topics in this field is to improve system throughput by supporting multiple users with limited bandwidth resources. Although there are several studies on cross-layer designs for improving system throughput, previous research on quality-of-service guarantee and fairness are relatively rare. This study proposes a cross-layer subcarrier permutation (CLSP) mechanism that uses cross-layer strategies to select suboptimal subcarriers. Service flows simulations in the IEEE 802.16e system indicate that CLSP achieved a lower delay time and a long-term fairness among multiple users. Experimental results further show that the throughput of CLSP is 28 percent higher than that of the partial usage of subchannels model using the orthogonal frequency division multiple access technique. Copyright © 2011 John Wiley & Sons, Ltd.

A Cross-Layer Framework for Overhead Reduction, Traffic Scheduling, and Burst Allocation in IEEE 802.16 OFDMA Networks

IEEE 802.16 orthogonal frequency-division multiple access (OFDMA) downlink subframes have a special 2-D channel-time structure. Allocation resources from such a 2-D structure incur extra control overheads that hurt network performance. Existing solutions try to improve network performance by designing either the scheduler in the medium access control layer or the burst allocator in the physical layer, but the efficiency of overhead reduction is limited. In this paper, we point out the necessity of “codesigning” both the scheduler and the burst allocator to efficiently reduce overheads and improve network performance. Under the partial-usage-of-subcarriers model, we propose a cross-layer framework that covers overhead reduction, real-time and non-real-time traffic scheduling, and burst allocation. The framework includes a two-tier priority-based scheduler and a bucket-based burst allocator, which is more complete and efficient than prior studies. Both the scheduler and the burst allocator are tightly coupled together to solve the problem of arranging resources to data traffic. Given available space and bucket design from the burst allocator, the scheduler can well utilize the frame resource, reduce real-time traffic delays, and maintain fairness. On the other hand, with priority knowledge and resource assignment from the scheduler, the burst allocator can efficiently arrange downlink bursts to satisfy traffic requirements with low complexity. Through analysis, the cross-layer framework is validated to give an upper bound to overheads and achieve high network performance. Extensive simulation results verify that the cross-layer framework significantly increases network throughput, maintains long-term fairness, alleviates real-time traffic delays, and enhances frame utilization.

A Dynamic Utility Adaptation Framework for Efficient Multimedia Service Support in CDMA Wireless Networks

In this paper the problem of channel-aware opportunistic resource allocation for the downlink in CDMA wireless networks supporting simultaneously real-time multimedia and non-real-time data services is addressed. In order to treat different types of services with diverse QoS prerequisites through common optimization formulation a utility-based power and rate allocation framework is adopted. Emphasis is placed on real-time services' strict short-term QoS prerequisites, the fulfillment of which requires a significantly different treatment than the use of static utility functions, traditionally used to address long-term QoS or fairness prerequisites of delay-tolerant data services. To that end, we introduce a novel framework that enables the dynamic adaptation of real-time multimedia users' utilities as the system evolves, with respect to the corresponding short-term throughput service performance variations. The corresponding non-convex network utility maximization (NUM) problem is then formulated and solved, to obtain optimal power and rate allocation. Via simulation and analysis it is demonstrated that significant performance improvements are achieved in terms of real-time user's short-term throughput requirement satisfaction, without any considerable loss in total system throughput. Finally, essential tradeoffs between fulfilling real-time services' short-term QoS prerequisites and maximizing system performance, under an opportunistic scheduling wireless environment, are revealed and quantified.

Pension Fund Design under Long-term Fairness Constraints

We consider optimal portfolio insurance for a mutually owned with-profits pension fund. First, intergenerational fairness is imposed by requiring that the pension fund is driven towards a steady state. Subject to this condition the optimal asset allocation is identified among the class of constant proportion portfolio insurance strategies by maximising expected power utility of the benefit. For a simple contract approximate analytical results are available and accurate, whereas for a more involved contract Monte Carlo methods must be applied to pick out the best design. The main insights are (i) aggressive investment strategies are disastrous for the clients; (ii) in most cases it is optimal to gear the bonus reserve; and (iii) the results are far less sensitive to the agent's risk aversion than in the classical case of Merton (1969), and as opposed to Merton horizon matters even with constant investment opportunities (because of the serial dependence between bonuses).

Adaptive TXOP Allocation Based on Channel Conditions and Traffic Requirements in IEEE 802.11e Networks

IEEE 802.11e has established a new access mechanism called the hybrid coordination function (HCF) as a step toward provisioning quality-of service (QoS) support. In this mechanism, a simple HCF scheduler is introduced to take the QoS requirements of admitted flows into account and allocate transmission opportunities (TXOPs), which is the time under which a station (STA) can send its burst of data packets, to STAs. Although many approaches have been taken to address the mechanism's inherent problems, unsubstantial effort has been afforded in tackling a channel-aware allocation mechanism. An STA can be in either the good or bad channel state in any feasible data rate, which can be modeled as a Markov chain of two states for each data rate. In view of this, we propose a mechanism of adaptive TXOP allocation that is applicable to existing scheduling algorithms. Our method works in accordance with channel and traffic conditions and complies with the link adaptation mechanism. Extensive simulation results verify that our method shows improved performance while ensuring long-term fairness among STAs and being adaptive to the channel conditions and underlying physical transmission rates.

The Long-Term Care Job Fair Is Coming

The Long-Term Care Job Fair Is Coming

Long-term flow fairness with fixed memory space

We provide a minimal overhead FIFO queue management scheme which controls link congestion and realizes long-term flow fairness. The proposed scheme is very simple but effective to regulate long term high bandwidth flows. The proposed scheme uses light resources including additional small fixed size memory. The evaluation result verifies the max-min convergence of the proposed mechanism and shows that the proposed scheme outperforms the compared related schemes.

QoS Differentiated and Fair Packet Scheduling in Broadband Wireless Access Networks

This paper studies the packet scheduling problem in Broadband Wireless Access (BWA) networks. The key difficulties of the BWA scheduling problem lie in the high variability of wireless channel capacity and the unknown model of packet arrival process. It is difficult for traditional heuristic scheduling algorithms to handle the situation and guarantee satisfying performance in BWA networks. In this paper, we introduce learning-based approach for a better solution. Specifically, we formulate the packet scheduling problem as an average cost Semi-Markov Decision Process (SMDP). Then, we solve the SMDP by using reinforcement learning. A feature-based linear approximation and the Temporal-Difference learning technique are employed to produce a near optimal solution of the corresponding SMDP problem. The proposed algorithm, called Reinforcement Learning Scheduling (RLS), has in-built capability of self-training. It is able to adaptively and timely regulate its scheduling policy according to the instantaneous network conditions. Simulation results indicate that RLS outperforms two classical scheduling algorithms and simultaneously considers: (i) effective QoS differentiation, (ii) high bandwidth utilization, and (iii) both short-term and long-term fairness.

Long-term fairness with bounded worst-case losses

How does one repeatedly choose actions so as to be fairest to the multiple beneficiaries of those actions? We examine approaches to discovering sequences of actions for which the worst-off beneficiaries are treated maximally well, then secondarily the second-worst-off, and so on. We formulate the problem for the situation where the sequence of action choices continues forever; this problem may be reduced to a set of linear programs. We then extend the problem to situations where the game ends at some unknown finite time in the future. We demonstrate that an optimal solution is intractable, and present two good approximation algorithms.

Achieving Long-Term Fairness and Optimum Multiuser Diversity Gain in Time-Varying Broadcast Channels

In this paper, a downlink system in which a single-antenna base station communicates with k single antenna users over a time-correlated fading channel is considered. It is assumed that each receiver knows its own channel state, while the rate of the channel variation for all users and the corresponding initial fading gains are known to the base station. The average (per channel use) throughput of the system is studied by applying various adaptive signaling schemes. Assuming a large number of users in the system, it is shown that using a scheduling scheme in which the base station transmits to the user with the maximum initial fading gain, while using a fixed codeword length for all users, achieves the order of the maximum throughput. Moreover, an alternative scheduling scheme is proposed (by accounting for users' delays) and shown to achieve the optimum long-term fairness, while preserving the order of the maximum throughput.

On the fairness of large CSMA networks

We characterize the fairness of decentralized medium access control protocols based on CSMA/CA, in large multi-hop wireless networks. In particular, we show that the widely observed unfairness of these protocols in small network topologies does not always persist in large topologies. In regular networks, this unfairness is essentially due to the unfair advantage of nodes at the border of the network, which have a restricted neighborhood and thus a higher probability to access the communication channel. In large 1D lattice networks these border effects do not propagate inside the network, and nodes sufficiently far away from the border have equal access to the channel; as a result the protocol is long-term fair. In 2D lattice networks, we observe a phase transition. If the access intensity of the protocol is small, the border effects remain local and the protocol behaves similarly as in one-dimensional networks. However, if the access intensity of the protocol is large enough, the border effects persist independently of the size of the network and the protocol is strongly unfair. In irregular networks, the topology is inherently unfair. This unfairness increases with the access intensity of the protocol, but in a much smoother way than in regular two-dimensional networks. Finally, in situations where the protocol is long-term fair, we provide a characterization of its short-term fairness.

Opportunistic CSMA/CA for achieving multi-user diversity in wireless LAN

The throughput of an IEEE 802.11 network decreases as the number of users increases because of the increased collision probability. To improve the throughput in the presence of a large population, this paper presents an opportunistic carrier-sense multiple-acces/collision-avoidance (CSMA/CA) scheme that exploits multi-user diversity while minimally modifying the IEEE 802.11 medium-access control. This method prioritizes those users having high signal-to-noise-ratio by granting earlier access to these users, thus improving the throughput. This prioritization, however, can cause repeated collisions of same users, which is similar to so-called head-of-line (HOL) blocking. To reduce the probability of the occurrence of the HOL blocking, a simple randomization is proposed. A probabilistic analysis shows that this scheme significantly reduces the HOL blocking probability. The simulation results show that the proposed method improves the throughput by as much as 100%, while achieving long-term fairness among users with different channel conditions.

A comprehensive TCP fairness analysis in high speed networks

The short-term dynamics of competing high speed TCP flows can have strong impacts on their long-term fairness. This leads to severe problems for both the co-existence and the deployment feasibility of different proposals for the next generation networks. However, to our best knowledge, no root-cause analysis of this observation is available. This is the major motivation of our work. The contribution of the paper is twofold. First, we present our comprehensive performance evaluation results of both inter- and intra-protocol fairness behavior of different TCP versions to get an overall view of these protocols. The analysis has revealed not only the equilibrium behavior but also the transient characteristics besides the dynamic behavior. Second, we show the results of a root-cause analysis to get a deeper understanding in the case of some promising TCP versions. This study does not only fill the “black holes”, i.e. answers the questions which remained unanswered in some cases, but rather goes deeper and investigates questions which have never been asked yet. The work includes flow-level, packet-level, queueing and also spectral analyses. Three loss-based (HighSpeed TCP, Scalable TCP and BIC TCP) proposals and the delay-based FAST TCP are investigated in details with both “dumb-bell” and “parking-lot” topologies.

Fair Round-Robin: A Low Complexity Packet Schduler with Proportional and Worst-Case Fairness

Round robin based packet schedulers generally have a low complexity and provide long-term fairness. The main limitation of such schemes is that they do not support short-term fairness. In this paper, we propose a new low complexity round robin scheduler, called Fair Round Robin (FRR), that overcomes this limitation. FRR has similar complexity and long-term fairness properties as the stratified round robin scheduler, a recently proposed scheme that arguably provides the best quality-of-service properties among all existing round robin based low complexity packet schedulers. FRR offers better short-term fairness than stratified round robin and other existing round robin schedulers.

Modified bipartite matching for multiobjective optimization: Application to antenna assignments in MIMO systems

Based on the Hungarian algorithm, the Kuhn-Munkres algorithm can provide the maximum weight bipartite matching for assignment problems. However, it can only solve the single objective optimization problem. In this paper, we formulate the multi-objective optimization (MO) problem for bipartite matching, and propose a modified bipartite matching (MBM) algorithm to approach the Pareto set with a low computational complexity and to dynamically select proper solutions with given constraints among the reduced matching set. In addition, our MBM algorithm is extended to the case of asymmetric bipartite graphs. Finally, we illustrate the application of MBM to antenna assignments in wireless multiple-input multiple-output (MIMO) systems for both symmetric and asymmetric scenarios, where we consider the multi-objective optimization problem with the maximization of the system capacity, total traffic priority, and long-term fairness among all mobile users. The simulation results show that MBM can effectively reduce the matching set and dynamically provide the optimized performance with different quality of service (QoS) requirements.

CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems

Adaptive resource allocation has been shown to provide substantial performance gain in OFDMA-based wireless systems, such as WiMAX, when full channel state information (CSI) is available at the transmitter. However, in some fading environments (e.g., fast fading), there may not be a feedback link sufficiently fast to convey the CSI to the transmitter. In this paper, we consider resource allocation strategies for downlink multiuser mobile WiMAX systems, where the transmitter has only the channel distribution information (CDI), but no knowledge of the instantaneous channel realization. We address the problem of subchannel assignment and power allocation, to maximize the ergodic weighted-sum rate under long-term fairness, minimum data rate requirement and power budget constraints. This problem is formulated as a nonlinear stochastic constrained optimization problem. We provide an analytical solution based on the Lagrange dual decomposition framework. The proposed method has a complexity of (KM) for K users and M subchannels. Simulation results are provided to compare the performance of this method with other allocation schemes and to illustrate the tradeoff between maximized weighted-sum rate and the constraints.

A Novel Packet Scheduling for Wireless Channels with Adaptive Burst Profile

This paper proposes an Adaptive Profile Packet Scheduling (APS) algorithm for the down-link of IEEE 802.16 W-MAN, which is identified as a candidate standard for High Attitude Platforms (HAP) in the EU IST CAPANINA project. The proposed APS takes into account different wireless channel conditions observed by different subscriber stations to enhance the whole system utility and preserves the property of the long-term fairness.

Rate Maximization for Downlink OFDMA With Proportional Fairness

In this paper, we study the sum throughput maximization with access proportional fairness (APF) for downlink orthogonal frequency-division multiple access (OFDMA) channels. We propose selective multiuser diversity (SMuD) schemes with normalized signal-to-noise ratio (n-SNR)-based ranking for user selection at each carrier to achieve long-term fairness. We also propose a modified absolute signal-to-noise ratio (a-SNR)-ranking-based SMuD scheme, which provides improved performance over the original a-SNR SMuD scheme. The total transmit power is assigned to the allocated carriers using either equal power allocation (EPA) or water filling. Closed-form throughput and fairness expressions for both the n-SNR and a-SNR SMuD schemes with EPA over Rayleigh channels are derived, which are accurate for even highly correlated frequency channels. Numerical results show that the long-term fairness gives a substantially higher rate than the more stringent short- term fairness. The n-SNR scheme brings perfect access fairness; the sum rate is slightly degraded compared to the a-SNR scheme without fairness, and it is not very sensitive to the imperfect estimation of the average channel signal-to-noise ratio. These results put new insight into the achievable downlink OFDMA performance with proportional fairness and the effects of various system and channel parameters.