Differentiated Predictive Fair Service for TCP Flows

The majority of the traffic (bytes) flowing over the Internet today have been attributed to the Transmission Control Protocol (TCP). This strong presence of TCP has recently spurred further investigations into its congestion avoidance mechanism and its effect on the performance of short and long data transfers. At the same time, the rising interest in enhancing Internet services while keeping the implementation cost low has led to several service-differentiation proposals. In such service-differentiation architectures, much of the complexity is placed only in access routers, which classify and mark packets from different flows. Core routers can then allocate enough resources to each class of packets so as to satisfy delivery requirements, such as predictable (consistent) and fair service. In this paper, we investigate the interaction among short and long TCP flows, and how TCP service can be improved by employing a low-cost service-differentiation scheme. Through control-theoretic arguments and extensive simulations, we show the utility of isolating TCP flows into two classes based on their lifetime/size, namely one class of short flows and another of long flows. With such class-based isolation, short and long TCP flows have separate service queues at routers. This protects each class of flows from the other as they possess different characteristics, such as burstiness of arrivals/departures and congestion/sending window dynamics. We show the benefits of isolation, in terms of better predictability and fairness, over traditional shared queueing systems with both tail-drop and Random-Early-Drop (RED) packet dropping policies. The proposed class-based isolation of TCP flows has several advantages: (1) the implementation cost is low since it only requires core routers to maintain per-class (rather than per-flow) state; (2) it promises to be an effective traffic engineering tool for improved predictability and fairness for both short and long TCP flows; and (3) stringent delay requirements of short interactive transfers can be met by increasing the amount of resources allocated to the class of short flows.National Science Foundation (CAREER ANI-0096045, MRI EIA-9871022

IP-based virtual private networks and proportional quality of service differentiation

IP-based virtual private networks (VPNs) have the potential of delivering cost-effective, secure, and private network-like services. Having surveyed current enabling techniques, an overall picture of IP VPN implementations is presented. In order to provision the equivalent quality of service (QoS) of legacy connection-oriented layer 2 VPNs (e.g., Frame Relay and ATM), IP VPNs have to overcome the intrinsically best effort characteristics of the Internet. Subsequently, a hierarchical QoS guarantee framework for IP VPNs is proposed, stitching together development progresses from recent research and engineering work. To differentiate IP VPN QoS, the proportional QoS differentiation model, whose QoS specification granularity compromises that of IntServ and Diffserv, emerges as a potential solution. The investigation of its claimed capability of providing the predictable and controllable QoS differentiation is then conducted. With respect to the loss rate differentiation, the packet shortage phenomenon shown in two classical proportional loss rate (PLR) dropping schemes is studied. On the pursuit of a feasible solution, the potential of compromising the system resource, that is, the buffer, is ruled out; instead, an enhanced debt-aware mechanism is suggested to relieve the negative effects of packet shortage. Simulation results show that debt-aware partially curbs the biased loss rate ratios, and improves the queueing delay performance as well. With respect to the delay differentiation, the dynamic behavior of the average delay difference between successive classes is first analyzed, aiming to gain insights of system dynamics. Then, two classical delay differentiation mechanisms, that is,proportional average delay (PAD) and waiting time priority (WTP), are simulated and discussed. Based on observations on their differentiation performances over both short and long time periods, a combined delay differentiation (CDD) scheme is introduced. Simulations are utilized to validate this method. Both loss and delay differentiations are based on a series of differentiation parameters. Though previous work on the selection of delay differentiation parameters has been presented, that of loss differentiation parameters mostly relied on network operators\u27 experience. A quantitative guideline, based on the principles of queueing and optimization, is then proposed to compute loss differentiation parameters. Aside from analysis, the new approach is substantiated by numerical results

A Simple FIFO-Based Scheme for Differentiated Loss Guarantees

Today’s Internet carries traffic from a broad range of applications with different requirements. This has stressed its original, one-class, best-effort model, and has been a major driver of the many efforts aimed at introducing QoS. These efforts have, however, been met with only limited success, in part because the complexity they add is often at odds with the scalability requirements of the Internet. This has motivated many investigations for solutions that offer a better trade-off between service differentiation and complexity. This paper shares similar goals and proposes a simple scheme, Bounded Random Drop (BRD), that supports multiple service classes and is implemented using a single FIFO queue and a basic random dropping mechanism. BRD focuses on loss differentiation, as although losses and delay are both important, the steady rise of Internet link speeds is progressively limiting the impact of delay differentiation. It offers strong loss differentiation capabilities, and does not require traffic profiles or admission controls. BRD guarantees each class losses that, when feasible, are no worse than a specified bound, while enforcing differentiation only when required to meet those bounds. The performance of BRD is investigated for a broad range of traffic mixes and shown to consistently achieve its design goals

Multiplexing regulated traffic streams: design and performance

The main network solutions for supporting QoS rely on traf- fic policing (conditioning, shaping). In particular, for IP networks the IETF has developed Intserv (individual flows regulated) and Diffserv (only ag- gregates regulated). The regulator proposed could be based on the (dual) leaky-bucket mechanism. This explains the interest in network element per- formance (loss, delay) for leaky-bucket regulated traffic. This paper describes a novel approach to the above problem. Explicitly using the correlation structure of the sources’ traffic, we derive approxi- mations for both small and large buffers. Importantly, for small (large) buffers the short-term (long-term) correlations are dominant. The large buffer result decomposes the traffic stream in a stream of constant rate and a periodic impulse stream, allowing direct application of the Brownian bridge approximation. Combining the small and large buffer results by a concave majorization, we propose a simple, fast and accurate technique to statistically multiplex homogeneous regulated sources. To address heterogeneous inputs, we present similarly efficient tech- niques to evaluate the performance of multiple classes of traffic, each with distinct characteristics and QoS requirements. These techniques, applica- ble under more general conditions, are based on optimal resource (band- width and buffer) partitioning. They can also be directly applied to set GPS (Generalized Processor Sharing) weights and buffer thresholds in a shared resource system

ABE: providing a low-delay service within best effort

Alternative best effort (ABE) is a novel service for IP networks, which relies on the idea of providing low delay at the expense of possibly less throughput. The objective is to retain the simplicity of the original Internet single-class best-effort service while providing low delay to interactive adaptive applications