Network planning and design

About: Network planning and design is a research topic. Over the lifetime, 12393 publications have been published within this topic receiving 229776 citations. The topic is also known as: network design.

Self-Similar Network Traffic and Performance Evaluation

Abstract: Self-Similar Network Traffic: An Overview (K. Park & W. Willinger). Wavelets for the Analysis, Estimation, and Synthesis of Scaling Data (P. Abry, et al.). Simulations with Heavy-Tailed Workloads (M. Crovella & L. Lipsky). Queueing Behavior Under Fractional Brownian Traffic (I. Norros). Heavy Load Queueing Analysis with LRD On/Off Sources (F. Brichet, et al.). The Single Server Queue: Heavy Tails and Heavy Traffic (O. Boxma & J. Cohen). Fluid Queues, On/Off Processes, and Teletraffic Modeling with Highly Variable and Correlated Inputs (S. Resnick & G. Samorodnitsky). Bounds on the Buffer Occupancy Probability with Self-Similar Input Traffic (N. Likhanov). Buffer Asymptotics for M/G/ Input Processes (A. Makowski & M. Parulekar). Asymptotic Analysis of Queues with Subexponential Arrival Processes (P. Jelenkovi). Traffic and Queueing from an Unbounded Set of Independent Memoryless On/Off Sources (P. Jacquet). Long-Range Dependence and Queueing Effects for VBR Video (D. Heyman & T. Lakshman). Analysis of Transient Loss Performance Impact of Long-Range Dependence in Network Traffic (G.-L. Li & V. Li). The Protocol Stack and Its Modulating Effect on Self-Similar Traffic (K. Park, et al.). Characteristics of TCP Connection Arrivals (A. Feldmann). Engineering for Quality of Service (J. Roberts). Network Design and Control Using On/Off and Multilevel Source Traffic Models with Heavy-Tailed Distributions (N. Duffield & W. Whitt). Congestion Control for Self-Similar Network Traffic (T. Tuan & K. Park). Quality of Service Provisioning for Long-Range-Dependent Real-Time Traffic (A. Adas & A. Mukherjhee). Toward an Improved Understanding of Network Traffic Dynamics (R. Riedi & W. Willinger). Future Directions and Open Problems in Performance Evaluation and Control of Self-Similar Network Traffic (K. Park). Index.

Network Design and Transportation Planning: Models and Algorithms

Abstract: Numerous transportation applications as diverse as capital investment decision-making, vehicle fleet planning, and traffic light signal setting all involve some form of (discrete choice) network design. In this paper, we review some of the uses and limitations of integer programming-based approaches to network design, and describe several discrete and continuous choice models and algorithms. Our objectives are threefold—to provide a unifying view for synthesizing many network design models, to propose a unifying framework for deriving many network design algorithms, and to summarize computational experience in solving design problems. We also show that many of the most celebrated combinatorial problems that arise in transportation planning are specializations and variations of a generic design model. Consequently, the network design concepts described in this paper have great potential application in a wide range of problem settings.

Long-range dependence in variable-bit-rate video traffic

Abstract: We analyze 20 large sets of actual variable-bit-rate (VBR) video data, generated by a variety of different codecs and representing a wide range of different scenes. Performing extensive statistical and graphical tests, our main conclusion is that long-range dependence is an inherent feature of VBR video traffic, i.e., a feature that is independent of scene (e.g., video phone, video conference, motion picture video) and codec. In particular, we show that the long-range dependence property allows us to clearly distinguish between our measured data and traffic generated by VBR source models currently used in the literature. These findings give rise to novel and challenging problems in traffic engineering for high-speed networks and open up new areas of research in queueing and performance analysis involving long-range dependent traffic models. A small number of analytic queueing results already exist, and we discuss their implications for network design and network control strategies in the presence of long-range dependent traffic. >

Routing, Flow, And Capacity Design In Communication And Computer Networks

Abstract: In network design, the gap between theory and practice is woefully broad. This book narrows it, comprehensively and critically examining current network design models and methods. You will learn where mathematical modeling and algorithmic optimization have been under-utilized. At the opposite extreme, you will learn where they tend to fail to contribute to the twin goals of network efficiency and cost-savings. Most of all, you will learn precisely how to tailor theoretical models to make them as useful as possible in practice. Throughout, the authors focus on the traffic demands encountered in the real world of network design. Their generic approach, however, allows problem formulations and solutions to be applied across the board to virtually any type of backbone communication or computer network. For beginners, this book is an excellent introduction. For seasoned professionals, it provides immediate solutions and a strong foundation for further advances in the use of mathematical modeling for network design. (Less)

Designing Network Design Spaces

Abstract: In this work, we present a new network design paradigm. Our goal is to help advance the understanding of network design and discover design principles that generalize across settings. Instead of focusing on designing individual network instances, we design network design spaces that parametrize populations of networks. The overall process is analogous to classic manual design of networks, but elevated to the design space level. Using our methodology we explore the structure aspect of network design and arrive at a low-dimensional design space consisting of simple, regular networks that we call RegNet. The core insight of the RegNet parametrization is surprisingly simple: widths and depths of good networks can be explained by a quantized linear function. We analyze the RegNet design space and arrive at interesting findings that do not match the current practice of network design. The RegNet design space provides simple and fast networks that work well across a wide range of flop regimes. Under comparable training settings and flops, the RegNet models outperform the popular EfficientNet models while being up to 5x faster on GPUs.