This document (ns Notes and Documentation) provides reference documentation for ns. Although we begin with a simple simulation script, resources like Marc Greis's tutorial web pages (originally at his web site, now at http://www.isi. edu/nsnam/ns/tutorial/) or the slides from one of the ns tutorials are problably better places to begin for the ns novice

ns c ○ is LBNL’s Network Simulator [24]. The simulator is written in C++; it uses OTcl as a command and configuration interface. ns v2 has three substantial changes from ns v1: (1) the more complex objects in ns v1 have been decomposed into simpler components for greater flexibility and composability; (2) the configuration interface is now OTcl, an object oriented version of Tcl; and (3) the interface code to the OTcl interpreter is separate from the main simulator. Ns documentation is available in html, Postscript, and PDF formats. See

The phenomenal growths of group communications and QoS-aware applications over the Internet have respectively accelerated the development of two key technologies, namely, multicasting and Differentiated Services (DiffServ). Although both are complementary technologies, the integration of the two technologies is a nontrivial task due to architectural conflicts between multicasting and DiffServ. In this paper, we propose an approach for providing multicast support across a DiffServ domain that is scalable in terms of group size, network size, and number of groups. We analyze our approach in a detailed manner for feasibility, adaptiveness, and deployment considerations.

The emergence of the Internet as the de facto communication infrastructure means that it is asked to carry an ever broadening range of application traffic with different requirements. This in turn has stressed its original, one-class, best-effort model, and has been one of the main drivers behind the many efforts aimed at introducing QoS. Those efforts have, however, experienced only limited success because the added complexity QoS introduces is at odds with the scaling requirements of the Internet. This has motivated a number of proposals that have strived to balance the need for service differentiation with the requirement for low complexity that the Internet scale mandates. This paper shares similar goals and proposes a simple scheme, BoundedRandomDrop (BRD), that supports multiple service classes. BRD focuses on loss differentiation, as although both losses and delay are important performance parameters, the steadily rising speed of Internet links, including access links, is progressively limiting the potential impact of delay differentiation. BRD offers strong loss differentiation capabilities with minimal implementation and deployment cost. BRD does not require the specification of a traffic profile, nor does it rely on call admission to control the amount of traffic in different classes. It guarantees each class losses that, when feasible, are no worse than a specified bound, but enforces differentiation only when required to meet those bounds. In addition, BRD is implemented using a single FIFO queue and a simple random dropping mechanism. The performance of BRD is investigated for a broad range of traffic mixes and shown to consistently achieve its goal of effective service differentiation. I.

In this paper, we focus on efficiently achieving Proportional Delay Differentiation (PDD), an instance of the Proportional Differentiation Model (PDM) first proposed under the DiffServ framework [3]. Waiting Time Priority (WTP) has been found to be a suitable algorithm to achieve PDD. Using WTP [4] as a reference, we show that our proposed Scaled Time Priority (STP) algorithm is able to provide near proportional delay at a complexity of O(1), which is lower than the O(N) complexity of WTP, where N is the number of service classes in the system. Simulation results also show that STP is able to emulate the performance of WTP.

In this dissertation, we present a novel service architecture for the Internet, which reconciles application demand for strong service guarantees with the need for low computational overhead in network routers. The main contribution of this dissertation is the definition and realization of a new service, called Quantitative Assured Forwarding, which can offer absolute and relative differentiation of loss, service rates, and packet delays to classes of traffic. We devise and analyze mechanisms that implement the proposed service, and demonstrate the effectiveness of the approach through analysis, simulation and measurement experiments in a testbed network. To enable

Abstract. This paper shows a configuration scheme for networks with WFQ schedulers. It guarantees maximum revenue for the service provider in the worst case of network congestion. We focus on best effort traffic and select those flows that maximize the benefit while keeping the network utilization high. We show that optimum network configuration is feasible based only on knowledge of the topology. Its dependence on the pricing scheme can be reduced and even eliminated. We offer a formulation that reaches a tradeoff between network utilization, fairness, and user satisfaction.

This paper shows a configuration scheme for networks with WFQ schedulers that maximizes the amount of best effort traffic carried. We focus on those cases where traffic flows would congest critical links and lower network performance. The proposal is based on a Linear Programming formulation. The solution provides the weights that will allow us to control the best effort flows and reach the optimal situation. We offer a formulation that reaches a trade-off between network utilization, fairness, and user satisfaction.

For the past decade, a lot of Internet research has been devoted to providing different levels of service to applications. Initial proposals for service differentiation provided strong service guarantees, with strict bounds on delays, loss rates, and throughput, but required high overhead in terms of computational complexity and memory, both of which raise scalability concerns. Recently, the interest has shifted to service architectures with low overhead. However, these newer service architectures only provide weak service guarantees, which do not always address the needs of applications. In this paper, we describe a service architecture that supports strong service guarantees, can be implemented with low computational complexity, and only requires to maintain little state information. A key mechanism of the proposed service architecture is that it addresses scheduling and buffer management in a single algorithm. The presented architecture offers no solution for controlling the amount of traffic that enters the network. Instead, we plan on exploiting feedback mechanisms of TCP congestion control algorithms for the purpose of regulating the traffic entering the network.

xample, for three classes, the QoS constraints could be of the form: @BA:C Class-2 Delay, Class-2 Loss Rate @EDGFIH C Class-3 Loss Rate, or JLKNMO/ . 78 Here, the first two constraints are relative constraints and the last one is an absolute constraint. The set of constraints can be any mix of relative and absolute constraints. More specifically, JoBS supports the five following types of constraints: - Relative delay constraints (RDC) specify a proportional delay differentiation between classes. As an example, for two classes D and A , the RDC enforces a relationship Delay of Class 2 Delay of Class 1 @ constant - Absolute delay constraints (ADC): An ADC on class requires that the delays of class satisfy a worst-case bound 6R . - Relative loss constraints (RLC) specify a proportional loss differentiation between classes. - Absolute loss constraints (ALC): An ALC on class requires that the loss rate of class be bounded by an upper SNR . - Absolut