The Internet is a gigantic distributed system where the end-to-end (E2E) quality-of-service (QoS) plays an important role. Yet the current inter-domain routing protocol, namely, the Border Gateway Protocol (BGP), cannot provide E2E QoS guarantees. The main reason is that an autonomous system (AS) can only receive guarantees from its first-hop ASes via service level agreements (SLAs). But beyond the first-hop, QoS along the path from a source AS to a destination AS is not within the source AS's control regime. This makes it difficult to provide high quality-of-experience services to many Internet users even when many content providers are willing to pay for such high quality E2E guarantees. In this paper, we investigate the feasibility of providing high QoS-guaranteed E2E transit services by utilizing a (small) set of ASes/IXPs to serve as “brokers” to provide supervision, control and resource negotiation. Finding an optimal set of ASes as brokers can be formulated as a Maximum Coverage with$B-$dominating path Guarantee (MCBG) problem, and we show that it is in fact NP-hard. To address this problem, we design a$(\frac{1{-}e^{-\!1}}{2}){-}$approximation algorithm and also an efficient heuristic algorithm when additional constraints (e.g., the path length) are considered. We further analyze the APX-hardness of the MCBG problem to reveal the existence of the best approximation ratio. Based on the current Internet topology, we demonstrate that it is indeed feasible to provide high QoS guarantees for most E2E connections with only a small broker set: with only 0.19, 1.9 or 6.8 percent ASes/IXPs serving as brokers, 53.13, 85.41 or 99.29 percent of all global E2E connections can receive high QoS-guaranteed services. Finally, we provide an economic model to study the behaviours of ASes when cooperating our brokerage scheme with the BGP protocol, and show that there are incentives to form and maintain such a brokerage coalition.

The current inter-domain routing protocol, namely, the Border Gateway Protocol (BGP), cannot provide end-to-end (E2E) quality-of-service (QoS) guarantees. The main reason is that an autonomous system (AS) can only receive guarantees from its first hop ASes via service level agreements (SLAs). But beyond the first hop, QoS along the path from source to destination AS is not within the source AS's control regime. In this paper, we investigate the feasibility of providing high QoS-guaranteed E2E transit services by utilizing a (small) set of ASes/IXPs to serve as "brokers" to provide supervision, control and resource negotiation. Finding an optimal set of ASes as brokers can be formulated as a Maximum Coverage with B-dominating path Guarantee (MCBG) problem, which we prove to be NP-hard. To address this problem, we design a (1-e-1/4)-approximation algorithm and also an efficient heuristic algorithm when considering additional constraints (e.g., path length). Based on the current Internet topology, we discover a "3540-alliance" subset (accounting only 6.8%) of 52,079 ASes/IXPs, which can provide high QoS guarantees for 99.29% E2E connections.

Abstract-Delay-sensitive cross-layer design has recently attracted increasing interests in providing delay performance guarantee and exploiting multi-user diversity throughput advantage for real-time traffic. Most of the existing solutions are centralized which are undesirable from the complexity scalability, signaling overhead scalability as well as the flexibility w.r.t. dynamic active sessions. In this work, we focus on delay-sensitive decentralized cross-layer design of OFDMA systems. Due to the stochastic system state, combinatorial nature of subcarrier allocation as well as the consideration for efficient feedback, conventional brute force decomposition technique failed to work. By using a novel two-level dual decomposition technique with comparison argument, we shall derive a feedback-efficient decentralized OFDMA cross-layer solution, with consideration of the stochastic system state, heterogeneous delay requirements, outdated CSIT as well as the combinatorial nature of subcarrier allocation. The proposed distributive design achieves optimal performance as the centralized solution scheduling with scalable complexity, signaling overhead as well as flexibility w.r.t. dynamic active sessions in the systems. In addition, using asymptotic analysis, we have derived the minimum feedback cost for ϵ-optimal system performance, wherein the average feedback cost per user is also shown to quickly approaches zero as systems scales.

Delay-sensitive cross-layer design has recently attracted increasing interests in providing delay performance guarantee and exploiting multi-user diversity throughput advantage for real-time traffic. However, existing cross-layer designs usually require centralized scheduling and information gathering, including full channel state information (CSI) and delay requirements, to exploit multiuser diversity gain as well as QoS (delay) provisioning. In this work, we provide a novel distributive solution to the delay-sensitive cross-layer OFDMA scheduling problem as well as introducing significant saving in the average feedback cost per user compared to classical cross- layer design. Simulation results illustrate that our proposed distributive design achieves the optimal performance as the centralized scheduling with much lower implementation complexity while maintaining heterogeneous users' delay requirements. Effects of CSIT outdateness are also considered in the proposed distributive cross-layer design framework.

There are two important aspects of cross-layer gains in multiuser OFDMA systems with slow fading channels. They are the system goodput gain as well as the packet diversity gain. The former aspect of cross-layer designs has been well- studied under perfect CSIT conditions and is known as the multi-user diversity gain (MuDiv). In cross-layer OFDMA systems with perfect CSIT, it is well known that the system throughput (ergodic capacity) scales in the order of O(log log Kldquo) due to the MuDiv gain, where K is the number users. However, in slow fading channels with delayed CSIT, there will always be potential packet errors (due to channel outage if the scheduled data rate exceeds the instantaneous mutual information) even if very strong channel coding is applied at the base station. In this case, the cross-layer packet outage diversity is important to protect the packet errors due to channel outage and there is a natural tradeoff between the goodput gain and packet diversity. In this paper, we shall focus on the asymptotic tradeoff analysis between the system goodput gain and the packet outage diversity gain in cross-layer OFDMA systems with delayed CSIT.

In this paper, we consider on the asymptotic tradeoff analysis between the system goodput gain and the packet outage diversity gain in cross-layer OFDMA systems with slow frequency selective fading and delayed CSIT. The OFDMA cross-layer design with delayed CSIT is modeled as an optimization problem where the rate adaptation, power adaptation and subcarrier allocation policies are designed to optimize the system goodput (b/s/Hz successfully received by the mobiles). We derived simple closed-form expressions for the power and rate allocations as well as the asymptotic order of growth in system goodput for general CSIT error sigmae2. We found that the system goodput scales in the order of O(log(1-sigmae2/ Nd(log K + Ndlog log K))) for large K where Nd is the packet outage diversity and K is the number of user in the cross-layer OFDMA system. Hence, double exponentially larger K is needed to compensate for the penalty in system goodput gain due to CSIT errors sigmae2or packet outage diversity Ndfor large Nd.

Cross-layer scheduling has been proposed to effectively boost the spectral efficiency of multi-user orthogonal frequency division multiple access (OFDMA) systems through multi-user selection diversity under two important assumptions - users are delay insensitive and channel state information at the transmitter (CSIT) is perfect. However, in practice, users may be delay sensitive with heterogeneous delay requirements, and CSIT usually becomes outdated in time varying channel. When CSIT is outdated, there will always be systematic packet errors even if powerful channel coding is applied, resulting in significant degradation on the delay performance of heterogeneous users. In this paper, we propose a novel delay-sensitive cross-layer design framework for multi-user OFDMA systems with heterogeneous delay requirements in slow fading channels, by utilizing both queueing theory and information theory to model the system dynamics as well as accounting impacts upon outdated CSIT. Based on the framework, the optimal power and subcarrier allocation solution is shown to maintain heterogeneous users' delay constraints and guarantee a fixed target outage probability, and its asymptotic multi-user diversity gain over fixed allocation scheme is also obtained analytically. Simulation results further show that our proposed delay-sensitive CSIT error considerate schemes provide robust system performance enhancement over naive scheduler while satisfying heterogeneous delay requirements even at moderate to high CSIT errors.

This paper proposes a cross-layer scheduling scheme for OFDMA wireless systems with heterogeneous delay requirements. We shall focus on the cross-layer design which takes into account both queueing theory and information theory in modeling the system dynamics. We propose a delay-sensitive cross-layer design, which determines the optimal subcarrier allocation and power allocation policies to maximize the total system throughput, subject to the individual user's delay constraint and total base station transmit power constraint. The delay-sensitive power allocation was found to be multilevel water-filling in which urgent users have higher water-filling levels. The delay-sensitive subcarrier allocation strategy has linear complexity with respect to number of users and number of subcarriers. Simulation results show that substantial throughput gain is obtained while satisfying the delay constraints when the delay-sensitive jointly optimal power and subcarrier allocation policy is adopted.

This paper investigates a cross layer scheduling scheme for OFDMA wireless system with heterogeneous delay requirements. Unlike most existing cross layer designs which take a decoupling approach, our design considers both queueing theory and information theory in modeling the system dynamics. The cross layer design is formulated as an optimization of total system throughput, subject to individual user's delay constraint and total base station transmit power constraint. The optimal scheduling algorithm for the delay-sensitive cross layer optimization is to dynamically allocate radio resources based on users' channel state information, source statistics and delay requirements. Specifically, optimal power allocation was found to be multilevel water-filling where urgent users have higher water-filling filinglevels, while optimal subcarrier allocation strategy is shown to be achievable by low complexity greedy algorithm. Simulation results also show the proposed jointly optimal power and subcarrier allocation policy can provide substantial throughput gain with all delay constraints being satisfied.

Cross-layer design for multi-antenna system has been shown to offer high spectral efficiency for multiuser system due to the multi-user diversity and the spatial multiplexing in wireless fading channels. Yet, most of the existing works assumed homogeneous user type (pure delay-insensitive data application). The effect of source statistics, queueing delay and application level requirements were completely ignored. In this paper, we shall propose an analytical cross layer design framework for multi-user multi-antenna systems for wireless multimedia applications with heterogeneous delay requirements. To take delay sensitive users into consideration, we shall utilize both queueing theory and information theory to model the system dynamics. A novel cross layer scheduler is designed to exploit the spatial multiplexing gain as well as the multi-user selection diversity gain, and at the same time maintain the delay constraints of the delay sensitive users. Simulation results indicate that the proposed scheduling design provides desirable delay performance and high throughput gain compared to other heuristic schemes.