George F. Riley

The ns-3 Network Simulator

As networks of computing devices grow larger and more complex, the need for highly accurate and scalable network simulation technologies becomes critical. Despite the emergence of large-scale testbeds for network research, simulation still plays a vital role in terms of scalability (both in size and in experimental speed), reproducibility, rapid prototyping, and education. With simulation based studies, the approach can be studied in detail at varying scales, with varying data applications, varying field conditions, and will result in reproducible and analyzable results.

The Georgia Tech Network Simulator

We introduce a new network simulation environment, developed by our research group, called the Georgia Tech Network Simulator (GTNetS). Our simulator is designed specifically to allow much larger-scale simulations than can easily be created by existing network simulation tools. The design of the simulator very closely matches the design of real network protocol stacks and hardware. Thus, anyone with a good understanding of networking in general can easily understand how the simulations are constructed. Further, our simulator is implemented completely in object-oriented C++, which leads to easy extension by users to experiment with new or modified behavior of existing simulation models. Our tool is designed from the beginning with scalability in mind, including the support for distributed simulations on a network of workstations as part of the basic design.We give an overview of the features of GTNetS, and present some preliminary scalability results we have obtained by running GTNetS on a computing cluster at the Pittsburgh Supercomputer Center.

ns-3 project goals

This paper reports on the project plan to develop a new major version of the popular ns-2 networking simulator. The authors have organized an NSF-funded, four-year community infrastructure project to develop the next version of ns. The project will also be oriented towards community development and open source software practices to encourage participation from the broader research and educational community. The purpose of this paper is to expand on the goals and initial design concepts for this new software development effort.

Large-scale network simulation: how big? how fast?

Parallel and distributed simulation tools are emerging that offer the ability to perform detailed, packet-level simulations of large-scale computer networks on an unprecedented scale. The state-of-the-art in large-scale network simulation is characterized quantitatively. For this purpose, a metric based on the number of packet transmissions that can be processed by a simulator per second of wallclock time (PTS) is used as a means to quantitatively assess packet-level network simulator performance. An approach to realizing scalable network simulations that leverages existing sequential simulation models and software is described. Results from a recent performance study are presented concerning large-scale network simulation on a variety of platforms ranging from workstations to cluster computers to supercomputers. These experiments include runs utilizing as many as 1536 processors yielding performance as high as 106 million PTS. The performance of packet-level simulations of web and ftp traffic, and denial of service attacks on networks containing millions of network nodes are briefly described, including a run demonstrating the ability to simulate a million web traffic flows in near real-time. New opportunities and research challenges to fully exploit this capability are discussed.

A generic framework for parallelization of network simulations

Discrete event simulation is widely used within the networking community for purposes such as demonstrating the validity of network protocols and architectures. Depending on the level of detail modeled within the simulation, the running time and memory requirements can be excessive. The goal of our research is to develop and demonstrate a practical, scalable approach to parallel and distributed simulation that will enable widespread reuse of sequential network simulation models and software. We focus on an approach to parallelization where an existing network simulator is used to build models of subnetworks that are composed to create simulations of larger networks. Changes to the original simulator care minimized, enabling the parallel simulator to easily track enhancements to the sequential version. We describe our lessons learned in applying this approach to the publicly available ns software package (McCanne and Floyd, 1997) and converting it to run in a parallel fashion on a network of workstations. This activity highlights a number of important problems, from the standpoint of how to parallelize an existing serial simulation model and achieving acceptable parallel performance.

Round-robin Arbiter Design and Generation

In this paper, we introduce a Round-robin Arbiter Generator (RAG) tool. The RAG tool can generate a design for a Bus Arbiter (BA). The BA is able to handle the exact number of bus masters for both on-chip and off-chip buses. RAG can also generate a distributed and parallel hierarchical Switch Arbiter (SA). The first contribution of this paper is the automated generation of a round-robin token passing BA to reduce time spent on arbiter design. The generated arbiter is fair, fast, and has a low and predictable worst-case wait time. The second contribution of this paper is the design and integration of a distributed fast arbiter, e.g., for a terabit switch, based on 2/spl times/2 and 4/spl times/4 switch arbiters (SAs). Using a .25/spl mu/ TSMC standard cell library from LEDA Systems [10, 14], we show the arbitration time of a 256/spl times/256 SA for a terabit switch and demonstrate that the SA generated by RAG meets the time constraint to achieve approximately six terabits of throughput in a typical network switch design. Furthermore, our generated SA performs better than the Ping-Pong Arbiter and Programmable Priority Encoder by a factor of 1.9/spl times/ and 2.4/spl times/, respectively.

Worm detection, early warning and response based on local victim information

Worm detection systems have traditionally focused on global strategies. In the absence of a global worm detection system, we examine the effectiveness of local worm detection and response strategies. This paper makes three contributions: (1) we propose a simple two-phase local worm victim detection algorithm, DSC (Destination-Source Correlation), based on worm behavior in terms of both infection pattern and scanning pattern. DSC can detect zero-day scanning worms with a high detection rate and very low false positive rate. (2) We demonstrate the effectiveness of early worm warning based on local victim information. For example, warning occurs with 0.19% infection of all vulnerable hosts on Internet when using a /12 monitored network. (3) Based on local victim information, we investigate and evaluate the effectiveness of an automatic real-time local response in terms of slowing down the global Internet worms propagation. (2) and (3) are general results, not specific to certain detection algorithm like DSC. We demonstrate (2) and (3) with both analytical models and packet-level network simulator experiments.

Analytical models for information propagation in vehicle-to-vehicle networks

There has been increasing interest in information infrastructures based on vehicle-to-vehicle communications. Proposed network architectures have unique characteristics that distinguish them from other systems. We present analytical models to study spatial propagation of information in a highly mobile vehicle-to-vehicle ad-hoc network. We show that information propagation depends on vehicle traffic characteristics, e.g., the vehicle density, average vehicle speed and relative speed among vehicles. Simulations validate these models and highlight the need to include other vehicle traffic models.

A federated approach to distributed network simulation

We describe an approach and our experiences in applying federated simulation techniques to create large-scale parallel simulations of computer networks. Using the federated approach, the topology and the protocol stack of the simulated network is partitioned into a number of submodels, and a simulation process is instantiated for each one. Runtime infrastructure software provides services for interprocess communication and synchronization (time management). We first describe issues that arise in homogeneous federations where a sequential simulator is federated with itself to realize a parallel implementation. We then describe additional issues that must be addressed in heterogeneous federations composed of different network simulation packages, and describe a dynamic simulation backplane mechanism that facilitates interoperability among different network simulators. Specifically, the dynamic simulation backplane provides a means of addressing key issues that arise in federating different network simulators: differing packet representations, incomplete implementations of network protocol models, and differing levels of detail among the simulation processes. We discuss two different methods for using the backplane for interactions between heterogeneous simulators: the cross-protocol stack method and the split-protocol stack method. Finally, results from an experimental study are presented for both the homogeneous and heterogeneous cases that provide evidence of the scalability of our federated approach on two moderately sized computing clusters. Two different homogeneous implementations are described: Parallel/Distributed ns (pdns) and the Georgia Tech Network Simulator (GTNetS). Results of a heterogeneous implementation federating ns with GloMoSim are described. This research demonstrates that federated simulations are a viable approach to realizing efficient parallel network simulation tools.

Spatial Propagation of Information in Vehicular Networks

There has been increasing interest in building an information infrastructure for mobile vehicles in surface transportation systems that principally rely on vehicle-to-vehicle (v2v) communications. The various network architectures proposed for this purpose have unique characteristics that distinguish them from other systems. However, only a limited amount of work has been completed to understand the fundamental network properties of such systems. In this paper, we present analytical models to study the spatial propagation of information in a highly mobile v2v ad hoc network. We explore both one- and two-way vehicle traffic scenarios. These models can help better understand data dissemination in this environment. Our results show that information propagation depends on some vehicle traffic characteristics, e.g., vehicle density, average vehicle speed, and relative vehicle movement. These models lead to some interesting discoveries, e.g., a message can propagate in the opposite direction as the vehicle traffic flow and can propagate much faster than vehicle movement.