Showing papers on "Network planning and design published in 2004"

Principles and Practices of Interconnection Networks

Abstract: One of the greatest challenges faced by designers of digital systems is optimizing the communication and interconnection between system components. Interconnection networks offer an attractive and economical solution to this communication crisis and are fast becoming pervasive in digital systems. Current trends suggest that this communication bottleneck will be even more problematic when designing future generations of machines. Consequently, the anatomy of an interconnection network router and science of interconnection network design will only grow in importance in the coming years. This book offers a detailed and comprehensive presentation of the basic principles of interconnection network design, clearly illustrating them with numerous examples, chapter exercises, and case studies. It incorporates hardware-level descriptions of concepts, allowing a designer to see all the steps of the process from abstract design to concrete implementation. ·Case studies throughout the book draw on extensive author experience in designing interconnection networks over a period of more than twenty years, providing real world examples of what works, and what doesn't. ·Tightly couples concepts with implementation costs to facilitate a deeper understanding of the tradeoffs in the design of a practical network. ·A set of examples and exercises in every chapter help the reader to fully understand all the implications of every design decision. Table of Contents Chapter 1 Introduction to Interconnection Networks 1.1 Three Questions About Interconnection Networks 1.2 Uses of Interconnection Networks 1.3 Network Basics 1.4 History 1.5 Organization of this Book Chapter 2 A Simple Interconnection Network 2.1 Network Specifications and Constraints 2.2 Topology 2.3 Routing 2.4 Flow Control 2.5 Router Design 2.6 Performance Analysis 2.7 Exercises Chapter 3 Topology Basics 3.1 Nomenclature 3.2 Traffic Patterns 3.3 Performance 3.4 Packaging Cost 3.5 Case Study: The SGI Origin 2000 3.6 Bibliographic Notes 3.7 Exercises Chapter 4 Butterfly Networks 4.1 The Structure of Butterfly Networks 4.2 Isomorphic Butterflies 4.3 Performance and Packaging Cost 4.4 Path Diversity and Extra Stages 4.5 Case Study: The BBN Butterfly 4.6 Bibliographic Notes 4.7 Exercises Chapter 5 Torus Networks 5.1 The Structure of Torus Networks 5.2 Performance 5.3 Building Mesh and Torus Networks 5.4 Express Cubes 5.5 Case Study: The MIT J-Machine 5.6 Bibliographic Notes 5.7 Exercises Chapter 6 Non-Blocking Networks 6.1 Non-Blocking vs. Non-Interfering Networks 6.2 Crossbar Networks 6.3 Clos Networks 6.4 Benes Networks 6.5 Sorting Networks 6.6 Case Study: The Velio VC2002 (Zeus) Grooming Switch 6.7 Bibliographic Notes 6.8 Exercises Chapter 7 Slicing and Dicing 7.1 Concentrators and Distributors 7.2 Slicing and Dicing 7.3 Slicing Multistage Networks 7.4 Case Study: Bit Slicing in the Tiny Tera 7.5 Bibliographic Notes 7.6 Exercises Chapter 8 Routing Basics 8.1 A Routing Example 8.2 Taxonomy of Routing Algorithms 8.3 The Routing Relation 8.4 Deterministic Routing 8.5 Case Study: Dimension-Order Routing in the Cray T3D 8.6 Bibliographic Notes 8.7 Exercises Chapter 9 Oblivious Routing 9.1 Valiant's Randomized Routing Algorithm 9.2 Minimal Oblivious Routing 9.3 Load-Balanced Oblivious Routing 9.4 Analysis of Oblivious Routing 9.5 Case Study: Oblivious Routing in the Avici Terabit Switch Router(TSR) 9.6 Bibliographic Notes 9.7 Exercises Chapter 10 Adaptive Routing 10.1 Adaptive Routing Basics 10.2 Minimal Adaptive Routing 10.3 Fully Adaptive Routing 10.4 Load-Balanced Adaptive Routing 10.5 Search-Based Routing 10.6 Case Study: Adaptive Routing in the Thinking Machines CM-5 10.7 Bibliographic Notes 10.8 Exercises Chapter 11 Routing Mechanics 11.1 Table-Based Routing 11.2 Algorithmic Routing 11.3 Case Study: Oblivious Source Routing in the IBM Vulcan Network 11.4 Bibliographic Notes 11.5 Exercises Chapter 12 Flow Control Basics 12.1 Resources and Allocation Units 12.2 Bufferless Flow Control 12.3 Circuit Switching 12.4 Bibliographic Notes 12.5 Exercises Chapter 13 Buffered Flow Control 13.1 Packet-Buffer Flow Control 13.2 Flit-Buffer Flow Control 13.3 Buffer Management and Backpressure 13.4 Flit-Reservation Flow Control 13.5 Bibliographic Notes 13.6 Exercises Chapter 14 Deadlock and Livelock 14.1 Deadlock 14.2 Deadlock Avoidance 14.3 Adaptive Routing 14.4 Deadlock Recovery 14.5 Livelock 14.6 Case Study: Deadlock Avoidance in the Cray T3E 14.7 Bibliographic Notes 14.8 Exercises Chapter 15 Quality of Service 15.1 Service Classes and Service Contracts 15.2 Burstiness and Network Delays 15.3 Implementation of Guaranteed Services 15.4 Implementation of Best-Effort Services 15.5 Separation of Resources 15.6 Case Study: ATM Service Classes 15.7 Case Study: Virtual Networks in the Avici TSR 15.8 Bibliographic Notes 15.9 Exercises Chapter 16 Router Architecture 16.1 Basic Router Architecture 16.2 Stalls 16.3 Closing the Loop with Credits 16.4 Reallocating a Channel 16.5 Speculation and Lookahead 16.6 Flit and Credit Encoding 16.7 Case Study: The Alpha 21364 Router 16.8 Bibliographic Notes 16.9 Exercises Chapter 17 Router Datapath Components 17.1 Input Buffer Organization 17.2 Switches 17.3 Output Organization 17.4 Case Study: The Datapath of the IBM Colony Router 17.5 Bibliographic Notes 17.6 Exercises Chapter 18 Arbitration 18.1 Arbitration Timing 18.2 Fairness 18.3 Fixed Priority Arbiter 18.4 Variable Priority Iterative Arbiters 18.5 Matrix Arbiter 18.6 Queuing Arbiter 18.7 Exercises Chapter 19 Allocation 19.1 Representations 19.2 Exact Algorithms 19.3 Separable Allocators 19.4 Wavefront Allocator 19.5 Incremental vs. Batch Allocation 19.6 Multistage Allocation 19.7 Performance of Allocators 19.8 Case Study: The Tiny Tera Allocator 19.9 Bibliographic Notes 19.10 Exercises Chapter 20 Network Interfaces 20.1 Processor-Network Interface 20.2 Shared-Memory Interface 20.3 Line-Fabric Interface 20.4 Case Study: The MIT M-Machine Network Interface 20.5 Bibliographic Notes 20.6 Exercises Chapter 21 Error Control 411 21.1 Know Thy Enemy: Failure Modes and Fault Models 21.2 The Error Control Process: Detection, Containment, and Recovery 21.3 Link Level Error Control 21.4 Router Error Control 21.5 Network-Level Error Control 21.6 End-to-end Error Control 21.7 Bibliographic Notes 21.8 Exercises Chapter 22 Buses 22.1 Bus Basics 22.2 Bus Arbitration 22.3 High Performance Bus Protocol 22.4 From Buses to Networks 22.5 Case Study: The PCI Bus 22.6 Bibliographic Notes 22.7 Exercises Chapter 23 Performance Analysis 23.1 Measures of Interconnection Network Performance 23.2 Analysis 23.3 Validation 23.4 Case Study: Efficiency and Loss in the BBN Monarch Network 23.5 Bibliographic Notes 23.6 Exercises Chapter 24 Simulation 24.1 Levels of Detail 24.2 Network Workloads 24.3 Simulation Measurements 24.4 Simulator Design 24.5 Bibliographic Notes 24.6 Exercises Chapter 25 Simulation Examples 495 25.1 Routing 25.2 Flow Control Performance 25.3 Fault Tolerance Appendix A Nomenclature Appendix B Glossary Appendix C Network Simulator

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)

Lessons from a Sensor Network Expedition

Abstract: Habitat monitoring is an important driving application for wireless sensor networks (WSNs). Although researchers anticipate some challenges arising in the real-world deployments of sensor networks, a number of problems can be discovered only through experience. This paper evaluates a sensor network system described in an earlier work and presents a set of experiences from a four month long deployment on a remote island off the coast of Maine. We present an in-depth analysis of the environmental and node health data. The close integration of WSNs with their environment provides biological data at densities previous impossible; however, we show that the sensor data is also useful for predicting system operation and network failures. Based on over one million data and health readings, we analyze the node and network design and develop network reliability profiles and failure models.

The price of stability for network design with fair cost allocation

Abstract: Network design is a fundamental problem for which it is important to understand the effects of strategic behavior. Given a collection of self-interested agents who want to form a network connecting certain endpoints, the set of stable solutions - the Nash equilibria - may look quite different from the centrally enforced optimum. We study the quality of the best Nash equilibrium, and refer to the ratio of its cost to the optimum network cost as the price of stability. The best Nash equilibrium solution has a natural meaning of stability in this context - it is the optimal solution that can be proposed from which no user will "defect". We consider the price of stability for network design with respect to one of the most widely-studied protocols for network cost allocation, in which the cost of each edge is divided equally between users whose connections make use of it; this fair-division scheme can be derived from the Shapley value, and has a number of basic economic motivations. We show that the price of stability for network design with respect to this fair cost allocation is O(log k), where k is the number of users, and that a good Nash equilibrium can be achieved via best-response dynamics in which users iteratively defect from a starting solution. This establishes that the fair cost allocation protocol is in fact a useful mechanism for inducing strategic behavior to form near-optimal equilibria. We discuss connections to the class of potential games defined by Monderer and Shapley, and extend our results to cases in which users are seeking to balance network design costs with latencies in the constructed network, with stronger results when the network has only delays and no construction costs. We also present bounds on the convergence time of best-response dynamics, and discuss extensions to a weighted game.

A study of the coverage of large-scale sensor networks

Abstract: We study the coverage properties of large-scale sensor networks. Three coverage measures are defined to characterize the fraction of the area covered by sensors (area coverage), the fraction of sensors that can be removed without reducing the covered area (node coverage), and the capability of the sensor network to detect objects moving in the network (detectability), respectively. We approach the coverage problem from a theoretical perspective and explore the fundamental limits of the coverage of a large-scale sensor network. We characterize the asymptotic behavior of the coverage measures for a variety of sensor network scenarios. We find that the coverage of a sensor network exhibits different behaviors for different network configuration and parameters. Based on the analytical characterizations of the network coverage, we further discuss the implications to network planning and protocol performance of sensor networks.

Introduction to Logistics Systems Planning and Control

Abstract: Foreword.Preface.Abbreviations.Problems and Website.Acknowledgements.About the Authors.1 Introducing Logistics Systems.1.1 Introduction.1.2 How Logistics Systems Work.1.2.1 Order processing.1.2.2 Inventory management.1.2.3 Freight transportation.1.3 Logistics Managerial Issues.1.4 Emerging Trends in Logistics.1.5 Logistics Decisions.1.5.1 Decision support methods.1.5.2 Outline of the book.1.6 Questions and Problems.1.7 Annotated Bibliography.2 Forecasting Logistics Requirements.2.1 Introduction.2.2 Demand Forecasting Methods.2.2.1 Qualitative methods.2.2.2 Quantitative methods.2.2.3 Notation.2.3 Causal Methods.2.4 Time Series Extrapolation.2.4.1 Time series decomposition method.2.5 Further Time Series Extrapolation Methods: the Constant Trend Case.2.5.1 Elementary technique.2.5.2 Moving average method.2.5.3 Exponential smoothing method.2.5.4 Choice of the smoothing constant.2.5.5 The demand forecasts for the subsequent time periods.2.6 Further Time Series Extrapolation Methods: the Linear Trend Case.2.6.1 Elementary technique.2.6.2 Linear regression method.2.6.3 Double moving average method.2.6.4 The Holt method.2.7 Further Time Series Extrapolation Methods: the Seasonal Effect Case.2.7.1 Elementary technique.2.7.2 Revised exponential smoothing method.2.7.3 The Winters method.2.8 Advanced Forecasting Methods.2.9 Selection and Control of Forecasting Methods.2.9.1 Accuracy measures.2.9.2 Forecast control.2.10 Questions and Problems.2.11 Annotated Bibliography.3 Designing the Logistics Network.3.1 Introduction.3.2 Classification of Location Problems.3.3 Single-Echelon Single-Commodity Location Models.3.3.1 Linear transportation costs and facility fixed costs.3.3.2 Linear transportation costs and concave piecewise linear facility operating costs.3.4 Two-Echelon Multicommodity Location Models.3.5 Logistics Facility Location in the Public Sector.3.5.1 p-centre models.3.5.2 The location-covering model.3.6 Data Aggregation.3.7 Questions and Problems.3.8 Annotated Bibliography.4 Solving Inventory Management Problems.4.1 Introduction.4.2 Relevant Costs.4.3 Classification of Inventory Management Models.4.4 Single Stocking Point: Single-Commodity Inventory Models under Constant Demand Rate.4.4.1 Noninstantaneous resupply.4.4.2 Instantaneous resupply.4.4.3 Reorder point.4.5 Single Stocking Point: Single-Commodity Inventory Models under Deterministic Time-Varying Demand Rate.4.6 Models with Discounts.4.6.1 Quantity-discounts-on-all-units.4.6.2 Incremental quantity discounts.4.7 Single Stocking Point: Multicommodity Inventory Models.4.7.1 Models with capacity constraints.4.7.2 Models with joint costs.4.8 Stochastic Models.4.8.1 The Newsboy Problem.4.8.2 The (s, S) policy for single period problems.4.8.3 The reorder point policy.4.8.4 The periodic review policy.4.8.5 The (s, S) policy.4.8.6 The two-bin policy.4.9 Selecting an Inventory Policy.4.10 Multiple Stocking Point Models.4.11 Slow-Moving Item Models.4.12 Policy Robustness.4.13 Questions and Problems.4.14 Annotated Bibliography.5 Designing and Operating a Warehouse.5.1 Introduction.5.1.1 Internal warehouse structure and operations.5.1.2 Storage media.5.1.3 Storage/retrieval transport mechanisms and policies.5.1.4 Decisions support methodologies.5.2 Warehouse Design.5.2.1 Selecting the storage medium and the storage/retrieval transport mechanism.5.2.2 Sizing the receiving and shipment subsystems.5.2.3 Sizing the storage subsystems.5.3 Tactical Decisions.5.3.1 Product allocation.5.4 Operational Decisions.5.4.1 Batch formation.5.4.2 Order picker routing.5.4.3 Packing problems.5.5 Questions and Problems.5.6 Annotated Bibliography.6 Planning and Managing Long-Haul Freight Transportation.6.1 Introduction.6.2 Relevant Costs.6.3 Classification of Transportation Problems.6.4 Fleet Composition.6.5 Freight Traffic Assignment Problems.6.5.1 Minimum-cost flow formulation.6.5.2 Linear single-commodity minimum-cost flow problems.6.5.3 Linear multicommodity minimum-cost flow problems.6.6 Service Network Design Problems.6.6.1 Fixed-charge network design models.6.6.2 The linear fixed-charge network design model.6.7 Shipment Consolidation and Dispatching.6.8 Freight Terminal Design and Operations.6.8.1 Design issues.6.8.2 Tactical and operational issues.6.9 Vehicle Allocation Problems.6.10 The Dynamic Driver Assignment Problem.6.11 Questions and Problems.6.12 Annotated Bibliography.7 Planning and Managing Short-Haul Freight Transportation.7.1 Introduction.7.2 Vehicle Routing Problems.7.3 The Travelling Salesman Problem.7.3.1 The asymmetric travelling salesman problem.7.3.2 The symmetric travelling salesman problem.7.4 The Node Routing Problem with Capacity and Length Constraints.7.4.1 Constructive heuristics.7.5 The Node Routing and Scheduling Problem with TimeWindows.7.5.1 An insertion heuristic.7.5.2 A unified tabu search procedure for constrained node routing problems.7.6 Arc Routing Problems.7.6.1 The Chinese postman problem.7.6.2 The rural postman problem 2867.7 Real-Time Vehicle Routing and Dispatching.7.8 Integrated Location and Routing.7.9 Vendor-Managed Inventory Routing.7.10 Questions and Problems.7.11 Annotated Bibliography.8 Linking Theory to Practice.8.1 Introduction.8.2 Shipment Consolidation and Dispatching at ExxonMobil Chemical.8.3 Distribution Management at Pfizer.8.3.1 The Logistics System.8.3.2 The Italian ALFA10 distribution system.8.4 Freight Rail Transportation at Railion.8.5 Yard Management at the Gioia Tauro Marine Terminal.8.6 Municipal Solid Waste Collection and Disposal Management at the Regional Municipality of Hamilton-Wentworth.8.7 Demand Forecasting at Adriatica Accumulatori.8.8 Distribution Logistics Network Design at DowBrands.8.9 ContainerWarehouse Location at Hardcastle.8.10 Inventory Management atWolferine.8.11 Airplane Loading at FedEx.8.12 Container Loading atWaterworld.8.12.1 Packing rolls into containers.8.12.2 Packing pallets into containers.8.13 Air Network Design at Intexpress.8.14 Bulk-Cargo Ship Scheduling Problem at the US Navy.8.15 Meter Reader Routing and Scheduling at Socal.8.16 Annotated Bibliography.8.17 Further Case Studies.Index.

Does conservation planning matter in a dynamic and uncertain world

Abstract: We show that while comprehensive reserve network design is best when the entire network can be implemented immediately, when conservation investments must be staged over years, such solutions actually may be sub-optimal in the context of biodiversity loss and uncertainty.

Traffic signal timing optimisation based on genetic algorithm approach, including drivers’ routing

Abstract: The genetic algorithm approach to solve traffic signal control and traffic assignment problem is used to tackle the optimisation of signal timings with stochastic user equilibrium link flows. Signal timing is defined by the common network cycle time, the green time for each signal stage, and the offsets between the junctions. The system performance index is defined as the sum of a weighted linear combination of delay and number of stops per unit time for all traffic streams, which is evaluated by the traffic model of TRANSYT [User guide to TRANSYT, version 8, TRRL Report LR888, Transport and Road Research Laboratory, Crowthorne, 1980]. Stochastic user equilibrium assignment is formulated as an equivalent minimisation problem and solved by way of the Path Flow Estimator (PFE). The objective function adopted is the network performance index (PI) and its use for the Genetic Algorithm (GA) is the inversion of the network PI, called the fitness function. By integrating the genetic algorithms, traffic assignment and traffic control, the GATRANSPFE (Genetic Algorithm, TRANSYT and the PFE), solves the equilibrium network design problem. The performance of the GATRANSPFE is illustrated and compared with mutually consistent (MC) solution using numerical example. The computation results show that the GA approach is efficient and much simpler than previous heuristic algorithm. Furthermore, results from the test road network have shown that the values of the performance index were significantly improved relative to the MC.

Multiple sink network design problem in large scale wireless sensor networks

Abstract: The battery resource of the sensor nodes should be managed efficiently, in order to prolong network lifetime in wireless sensor networks. Moreover, in large-scale networks with a large number of sensor nodes, multiple sink nodes should be deployed, not only to increase the manageability of the network, but also to reduce the energy-dissipation at each node. In this paper, we focus on the multiple sink location problems in large-scale wireless sensor networks. Different problems depending on the design criteria are presented. We consider locating sink nodes to the sensor environment, where we are given a time constraint that states the minimum required operational time for the sensor network. We use simulation techniques to evaluate the quality of our solution.

Broadband powerline communications networks : network design

Abstract: Preface.1. Introduction.2. PLC in the Telecommunications Access Area.3. PLC Network Characteristics.4. Realization of PLC Access Systems.5. PLC MAC Layer.6. Performance Evaluation of Reservation MAC Protocols.Appendix A.References.Index.

Auto-IP traffic optimization in mobile telecommunications systems

Abstract: A system and method for the implementation of fine-grained quality of service in a mobile telecommunications environment uses an Auto-IP policy Decision Point (220) to determine what traffic optimizations actions should be taken in reaction to various network conditions. The Auto-IP PDP (220) uses as inputs information from a Gb interface probe (230) to determine the user identification of an IP data flow, information from the radio access network (RAN) network management system (240) regarding network congestion. The cell traffic information is passed onto a traffic analysis and processing engine, the Auto-IP PDP (220) which maps the real-time traffic information into an n-dimensional traffic model. An automated policy decision guiding algorithm is executed on the n-dimensional traffic model and selects policy based on the traffic and cell congestion conditions, without human intervention. Additionally, a consistency check is performed to ensure that new policies are consistent with existing policies. The policy decision outcome is forwarded to the Auto-IP Traffic Optimizer (210) that acts on the network at a point in the network GI (151) that is different from where traffic problem occurs in the RAN. The Auto-IP Traffic Optimizer (210) implements the decisions of the Auto-IP-PDP (220) by performing traffic shaping, TCP window clamping or other traffic optimizations procedures on a cell-by-cell basis.

Analysis of wireless sensor networks for habitat monitoring

Abstract: We provide an in-depth study of applying wireless sensor networks (WSNs) to real-world habitat monitoring. A set of system design requirements were developed that cover the hardware design of the nodes, the sensor network software, protective enclosures, and system architecture to meet the requirements of biologists. In the summer of 2002, 43 nodes were deployed on a small island off the coast of Maine streaming useful live data onto the web. Although researchers anticipate some challenges arising in real-world deployments of WSNs, many problems can only be discovered through experience. We present a set of experiences from a four month long deployment on a remote island. We analyze the environmental and node health data to evaluate system performance. The close integration of WSNs with their environment provides environmental data at densities previously impossible. We show that the sensor data is also useful for predicting system operation and network failures. Based on over one million data readings, we analyze the node and network design and develop network reliability profiles and failure models.

Congestion-driven transmission expansion in competitive power markets

Abstract: A framework for transmission planning in a deregulated power market environment is discussed. The level of congestion in the network is utilized as the driving signal for the need of network expansion. A compromise between the congestion cost and the investment cost is used to determine the optimal expansion scheme. The long-term network expansion problem is formed as the decoupled combination of: 1) the master problem (minimization of investment costs subject to investment constraints and the Benders cuts generated by the operational problem (power pool) and 2) the operational problem, whose solution provides congestion details and associated multipliers. A proper power-pool model is developed and solved for congestion cost, congestion revenue, and transmission shadow prices. Linear programming is utilized to solve the investment subproblem, while the quadratic programming technique has been used to solve the operational problem. The algorithm has been developed for the complete planning process, which provides the expansion schemes for the planning horizon. The technique has been applied to illustrate the network planning study for a modified IEEE 24-bus test system.

An Empirical Analysis of Network Externalities in Peer-to-Peer Music-Sharing Networks

Abstract: Peer-to-peer (P2P) file sharing networks are an important medium for the distribution of information goods. However, there is little empirical research into the optimal design of these networks under real-world conditions. Early speculation about the behavior of P2P networks has focused on the role that positive network externalities play in improving performance as the network grows. However, negative network externalities also arise in P2P networks because of the consumption of scarce network resources or an increased propensity of users to free ride in larger networks, and the impact of these negative network externalities--while potentially important--has received far less attention.Our research addresses this gap in understanding by measuring the impact of both positive and negative network externalities on the optimal size of P2P networks. Our research uses a unique dataset collected from the six most popular OpenNap P2P networks between December 19, 2000, and April 22, 2001. We find that users contribute additional value to the network at a decreasing rate and impose costs on the network at an increasing rate, while the network increases in size. Our results also suggest that users are less likely to contribute resources to the network as the network size increases. Together, these results suggest that the optimal size of these centralized P2P networks is bounded--At some point the costs that a marginal user imposes on the network will exceed the value they provide to the network. This finding is in contrast to early predictions that larger P2P networks would always provide more value to users than smaller networks. Finally, these results also highlight the importance of considering user incentives--an important determinant of resource sharing in P2P networks--in network design.

Optimization of robustness of complex networks

Abstract: Networks with a given degree distribution may be very resilient to one type of failure or attack but not to another. The goal of this work is to determine network design guidelines which maximize the robustness of networks to both random failure and intentional attack while keeping the cost of the network (which we take to be the average number of links per node) constant. We find optimal parameters for: (i) scale free networks having degree distributions with a single power-law regime, (ii) networks having degree distributions with two power-law regimes, and (iii) networks described by degree distributions containing two peaks. Of these various kinds of distributions we find that the optimal network design is one in which all but one of the nodes have the same degree, k 1 (close to the average number of links per node), and one node is of very large degree, $k_2 \sim N^{2/3}$ , where N is the number of nodes in the network.

Network robustness and graph topology

Abstract: Two important recent trends in military and civilian communications have been the increasing tendency to base operations around an internal network, and the increasing threats to communications infrastructure. This combination of factors makes it important to study the robustness of network topologies. We use graph-theoretic concepts of connectivity to do this, and argue that node connectivity is the most useful such measure. We examine the relationship between node connectivity and network symmetry, and describe two conditions which robust networks should satisfy. To assist with the process of designing robust networks, we have developed a powerful network design and analysis tool called CAVALIER, which we briefly describe.

Warehouse-Retailer Network Design Problem

Abstract: In this paper, we study the distribution network design problem integrating transportation and infinite horizon multiechelon inventory cost function. We consider the trade-off between inventory cost, direct shipment cost, and facility location cost in such a system. The problem is to determine how many warehouses to set up, where to locate them, how to serve the retailers using these warehouses, and to determine the optimal inventory policies for the warehouses and retailers. The objective is to minimize the total multiechelon inventory, transportation, and facility location costs. To the best of our knowledge, none of the papers in the area of distribution network design has explicitly addressed the issues of the 2-echelon inventory cost function arising from coordination of replenishment activities between the warehouses and the retailers. We structure this problem as a set-partitioning integer-programming model and solve it using column generation. The pricing subproblem that arises from the column generation algorithm gives rise to a new class of the submodular function minimization problem. We show that this pricing subproblem can be solved inO( n?log? n) time, wheren is the number of retailers. Computational results show that the moderate size distribution network design problem can be solved efficiently via this approach.

A continuous equilibrium network design model and algorithm for transit systems

Abstract: In this paper, a bilevel programming model for transit network design problem is presented, in which the upper model is a normal transit network design model, and the lower model is a transit equilibrium assignment model. A heuristic solution algorithm based on sensitivity analysis is designed for the model proposed. Finally, a simple numerical example is given to illustrate the application of the model and algorithm and some conclusions are drawn.

A construction of locality-aware overlay network: mOverlay and its performance

Abstract: There are many research interests in peer-to-peer (P2P) overlay architectures. Most widely used unstructured P2P networks rely on central directory servers or massive message flooding, clearly not scalable. Structured overlay networks based on distributed hash tables (DHT) are expected to eliminate flooding and central servers, but can require many long-haul message deliveries. An important aspect of constructing an efficient overlay network is how to exploit network locality in the underlying network. We propose a novel mechanism, mOverlay, for constructing an overlay network that takes account of the locality of network hosts. The constructed overlay network can significantly decrease the communication cost between end hosts by ensuring that a message reaches its destination with small overhead and very efficient forwarding. To construct the locality-aware overlay network, dynamic landmark technology is introduced. We present an effective locating algorithm for a new host joining the overlay network. We then present a theoretical analysis and simulation results to evaluate the network performance. Our analysis shows that the overhead of our locating algorithm is O(logN), where N is the number of overlay network hosts. Our simulation results show that the average distance between a pair of hosts in the constructed overlay network is only about 11% of the one in a traditional, randomly connected overlay network. Network design guidelines are also provided. Many large-scale network applications, such as media streaming, application-level multicasting, and media distribution, can leverage mOverlay to enhance their performance.

RingO: an experimental WDM optical packet network for metro applications

Abstract: This paper presents Ring Optical Network (RingO), a wavelength-division-multiplexing (WDM), ring-based, optical packet network suitable for a high-capacity metro environment. We present three alternative architectural designs and elaborate on the effectiveness of optic with respect to electronic technologies, trying to identify an optimal mix. We present the design and prototyping of a simple but efficient access control protocol, based upon the equivalence of the proposed network architecture with input-buffering packet switches. We discuss the problem of node allocation to WDM channels, which can be viewed as a particular optical network design problem. We, finally, briefly illustrate the fault protection properties of the RingO architecture. The main contribution of this paper is the identification and experimental validation of an innovative optical network architecture, which is feasible and cost effective with technologies available today, and can be a valid alternative to more consolidated solutions in metro applications.

Optimal transit route network design problem: algorithms, implementations, and numerical results

Abstract: Previous approaches used to solve the transit route network design problem (TRNDP) can be classified into three categories: 1) Practical guidelines and ad hoc procedures; 2) Analytical optimization models for idealized situations; and 3) Meta-heuristic approaches for more practical problems. When the TRNDP is solved for a network of realistic size in which many parameters need to be determined, it is a combinatorial and NP-hard problem in nature and several sources of nonlinearities and non-convexities involved preclude guaranteed globally optimal solution algorithms. As a result, the meta-heuristic approaches, which are able to pursue reasonably good local (possibly global) optimal solutions and deal with simultaneous design of the transit route network and determination of its associated service frequencies, become necessary. The objective of this research is to systematically study the optimal TRNDP using hybrid heuristic algorithms at the distribution node level without aggregating the travel demand zones into a single node. A multi-objective nonlinear mixed integer model is formulated for the TRNDP. The proposed solution framework consists of three main components: an Initial Candidate Route Set Generation Procedure (ICRSGP) that generates all feasible routes incorporating practical bus transit industry guidelines; a Network Analysis Procedure (NAP) that determines transit trips for the TRNDP with variable demand, assigns these transit trips, determines service frequencies and computes performance measures; and a Heuristic Search Procedure (HSP) that guides the search techniques. Five heuristic algorithms, including the genetic algorithm, local search, simulated annealing, random search and tabu search, are employed as the solution methods for finding an optimal set of routes from the huge solution space. For the TRNDP with small network, the exhaustive search method is also used as a benchmark to examine the efficiency and measure the quality of the solutions obtained by using these heuristic algorithms. Several C++ program codes are developed to implement these algorithms for the TRNDP with both fixed and variable transit demand. Comprehensive experimental networks are used and successfully tested. Sensitivity analyses for each algorithm are conducted and model comparisons are performed. Numerical results are presented and the multi-objective decision making nature of the TRNDP is explored. Related characteristics underlying the TRNDP are identified, inherent tradeoffs are described and the redesign of the existing transit network is also discussed.

Stochastic transportation network design problem with spatial equity constraint

Abstract: Equity issues and demand uncertainty are two important issues in the network design problem (NDP). Spatial equity in NDP is concerned with the benefit distribution among network users. By considering demand uncertainty, a more realistic evaluation of the network performance given a network improvement plan can be obtained. Two stochastic models that consider both spatial equity and demand uncertainty are formulated: an expected-value model and a chance-constrained model. Both models are solved by a simulation-based genetic algorithm procedure. The genetic algorithm is used to solve NDP, and stochastic simulation is used to simulate the demand uncertainty. The results of numerical experiments are provided to demonstrate the significance of the equity issue and demand uncertainty in NDP.

High-level power analysis for on-chip networks

Abstract: As on-chip networks become prevalent in multiprocessor systems-on-a-chip and multi-core processors, they will be an integral part of the design flow of such systems. With power increasingly the primary constraint in chips, the tool chain in systems design, from simulation infrastructures to compilers and synthesis frameworks, needs to take network power into account, motivating the need for early-stage communication power analysis.While there has been substantial research in network performance analysis that enabled critical insights into network design, no power analysis frameworks for networks exist. In this paper, we propose such a framework that takes as input message flows, and derives a power profile of the network fabric, capturing both the spatial variance across the network fabric as well as the temporal variance across application execution time. Our analysis is based on link utilization as the unit of abstraction for network power, with contention among message flows modeled through propagation of overflow areas in link utilization functions. When validated against Orion, a cycle-accurate network power simulator, we show that relative trends in network power are well-preserved. We then demonstrate potential uses of our analysis framework through three case studies, from speedup of multiprocessor and network simulations, to facilitating power-aware communication synthesis and compiler code placement.

Game-theoretic models for reliable path-length and energy-constrained routing with data aggregation in wireless sensor networks

Abstract: Path length, path reliability, and sensor energy-consumption are three major constraints affecting routing in resource constrained, unreliable wireless sensor networks. By considering the implicit collaborative imperative for sensors to achieve overall network objectives subject to individual resource consumption, we develop a game-theoretic model of reliable, length and energy-constrained, sensor-centric information routing in sensor networks. We define two distinct payoff (benefit) functions and show that computing optimally reliable energy-constrained paths is NP-Hard under both models for arbitrary sensor networks. We then show that optimal length-constrained paths can be computed in polynomial time in a distributed manner (using O(E) messages) for popular sensor network implementations using geographic routing. We also develop sensor-centric metrics called path weakness to measure the qualitative performance of different routing schemes and provide theoretical limits on the inapproximability of computing paths with bounded weakness. Heuristics for computing optimal paths in arbitrary sensor networks are described along with simulation results comparing performance with other routing algorithms.

Network design for a grid hybrid transit service

Abstract: In this paper, we develop an analytical model that aids decision-makers in designing a hybrid grid network that integrates a flexible demand responsive service with a fixed route service. The objective of the model is to determine the optimal number of zones in an area where each zone is served by a number of on-demand vehicles. The function of the on-demand vehicles is to transfer passengers to a fixed route line if the destination is to a different zone or to its final destination if it is within the same zone.

A distributed approach to measure IP traffic matrices

Abstract: The traffic matrix of a telecommunications network is an essential input for any kind of network design and capacity planning decision. In this paper we address a debate surrounding traffic matrix estimation, namely whether or not the costs of direct measurement are too prohibitive to be practical. We examine the feasibility of direct measurement by outlining the computation, communication and storage overheads, for traffic matrices defined at different granularity levels. We illustrate that today's technology, that necessitates a centralized solution, does indeed incur prohibitive costs. We explain what steps are necessary to move towards fully distributed solutions, that would drastically reduce many overheads. However, we illustrate that the basic distributed solution, in which flow monitors are on all the time, is excessive and unnecessary. By discovering and taking advantage of a key stability property underlying traffic matrices, we are able to propose a new scheme that is distributed and relies only on a limited use of flow measurement data. Our approach is simple, accurate and scalable. Furthermore, it significantly reduces the overheads above and beyond the basic distributed solution. Our results imply that direct measurement of traffic matrices should become feasible in the near future.

System and process for managing network traffic

Abstract: A traffic management system for use in a communications network, including a detection module for determining the source addresses of received network packets, and for comparing the source addresses with stored source address data for network packets received in a previous time period. The system monitors increases in the number of new source IP addresses of received packets to detect a network traffic anomaly such as a distributed denial of service (DDoS) attack or a flash crowd. If a traffic anomaly is detected, a filtering module performs history-based filtering to block a received packet unless one or more legitimate packets with the same source address have been previously received in a predetermined time period.

Optical communication network system

Abstract: A fiber optic communication system includes a device of switching and setting wavelength of optical signals used in communication by network-node equipments, which sets the mapping of the wavelength of the optical signal used in communication by the network node equipments, and the input/output ports of an array waveguide grating (AWG), so as to construct a predetermined logical network topology by a plurality of network node equipments which are connected via optical fibers to the array waveguide grating that outputs optical signals inputted to optical input ports, to predetermined optical output ports in accordance with the wavelength thereof. As well as enabling a simple construction, it is easy to realize flexible network design, construction, and operation, and different network groups can also be easily connected to each other. Moreover, a fiber optic communication system having robust security and which can be stably operated even at the time of failure is realized at low cost.