Showing papers on "Network planning and design published in 2008"

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.

Power Awareness in Network Design and Routing

Abstract: Exponential bandwidth scaling has been a fundamental driver of the growth and popularity of the Internet. However, increases in bandwidth have been accompanied by increases in power consumption, and despite sustained system design efforts to address power demand, significant technological challenges remain that threaten to slow future bandwidth growth. In this paper we describe the power and associated heat management challenges in today's routers. We advocate a broad approach to addressing this problem that includes making power-awareness a primary objective in the design and configuration of networks, and in the design and implementation of network protocols. We support our arguments by providing a case study of power demands of two standard router platforms that enables us to create a generic model for router power consumption. We apply this model in a set of target network configurations and use mixed integer optimization techniques to investigate power consumption, performance and robustness in static network design and in dynamic routing. Our results indicate the potential for significant power savings in operational networks by including power-awareness.

Transit network design and scheduling: A global review

Abstract: This paper presents a global review of the crucial strategic and tactical steps of transit planning: the design and scheduling of the network. These steps influence directly the quality of service through coverage and directness concerns but also the economic profitability of the system since operational costs are highly dependent on the network structure. We first exhibit the context and the goals of strategic and tactical transit planning. We then establish a terminology proposal in order to name sub-problems and thereby structure the review. Then, we propose a classification of 69 approaches dealing with the design, frequencies setting, timetabling of transit lines and their combinations. We provide a descriptive analysis of each work so as to highlight their main characteristics in the frame of a two-fold classification referencing both the problem tackled and the solution method used. Finally, we expose recent context evolutions and identify some trends for future research. This paper aims to contribute to unification of the field and constitutes a useful complement to the few existing reviews.

Ship Scheduling and Network Design for Cargo Routing in Liner Shipping

Abstract: Acommon problem faced by carriers in liner shipping is the design of their service network. Given a set of demands to be transported and a set of ports, a carrier wants to design service routes for its ships as efficiently as possible, using the underlying facilities. Furthermore, the profitability of the service routes designed depends on the paths chosen to ship the cargo. We present an integrated model, a mixed-integer linear program, to solve the ship-scheduling and the cargo-routing problems, simultaneously. The proposed model incorporates relevant constraints, such as the weekly frequency constraint on the operated routes, and emerging trends, such as the transshipment of cargo between two or more service routes. To solve the mixed-integer program, we propose algorithms that exploit the separability of the problem. More specifically, a greedy heuristic, a column generation-based algorithm, and a two-phase Benders decomposition-based algorithm are developed, and their computational efficiency in terms of the solution quality and the computational time taken is discussed. An efficient iterative search algorithm is proposed to generate schedules for ships. Computational experiments are performed on randomly generated instances simulating real life with up to 20 ports and 100 ships. Our results indicate high percentage utilization of ships' capacities and a significant number of transshipments in the final solution.

Characterization of failures in an operational IP backbone network

Abstract: As the Internet evolves into a ubiquitous communication infrastructure and supports increasingly important services, its dependability in the presence of various failures becomes critical. In this paper, we analyze IS-IS routing updates from the Sprint IP backbone network to characterize failures that affect IP connectivity. Failures are first classified based on patterns observed at the IP-layer; in some cases, it is possible to further infer their probable causes, such as maintenance activities, router-related and optical layer problems. Key temporal and spatial characteristics of each class are analyzed and, when appropriate, parameterized using well-known distributions. Our results indicate that 20% of all failures happen during a period of scheduled maintenance activities. Of the unplanned failures, almost 30% are shared by multiple links and are most likely due to router-related and optical equipment-related problems, respectively, while 70% affect a single link at a time. Our classification of failures reveals the nature and extent of failures in the Sprint IP backbone. Furthermore, our characterization of the different classes provides a probabilistic failure model, which can be used to generate realistic failure scenarios, as input to various network design and traffic engineering problems.

A heuristic approach to logistics network design for end-of-lease computer products recovery

Abstract: This paper discusses the logistics network design for end-of-lease computer products recovery by developing a deterministic programming model for systematically managing forward and reverse logistics flows. Due to the complexity of such network design problem, a two-stage heuristic approach is developed to decompose the integrated design of the distribution networks into a location–allocation problem and a revised network flow problem. The applicability of the proposed method is illustrated in a numerical study. Computational experiments demonstrate that high-quality solutions are obtained while modest computational overheads are incurred.

Optical Network Design and Planning

Abstract: Telecommunications carriers have begun to upgrade their networks with state-of-the-art optical equipment, referred to as optical-bypass technology. The ramifications of this technology are manifold, affecting the architecture, operation, and economics of the network, all of which are covered in this book. The book is oriented towards practical implementation in metro and backbone networks, taking advantage of the authors extensive experience with actual commercial equipment and carrier networks. The book starts with an overview of optical networking, including an introduction to state-of-the-art optical networks. The second chapter covers legacy optical equipment and the new optical-bypass technology, with an emphasis on the architectural impact of the equipment. For example, the discussion covers how the various types of equipment affect the economics and flexibility of the network. One of the challenges of optical-bypass technology is that it requires sophisticated algorithms in order to operate the network efficiently. Chapters three, four, and five describe such algorithms, where the focus is on techniques that have been proven to produce efficient results in realistic carrier networks. The design and planning strategies described in these chapters are readily implementable. All of the algorithms presented scale well with network size so that they are suitable for real-time design. Chapters six and seven focus on two important aspects of optical networks, namely efficient bundling of the traffic and protection of the traffic. Rather than cover every aspect of these two subjects, the book focuses on how best to perform bundling and protection in the presence of optical-bypass technology. Again, the emphasis is on techniques that have proven effective in real network environments. The final chapter explores the economics of optical networking. Several studies are presented that offer guidelines as to when and how optical-bypass technology should be deployed. The code for some of the routing algorithms is provided in the appendix, which adds to the utility of the book.

Network topologies: inference, modeling, and generation

Abstract: Accurate measurement, inference and modeling techniques are fundamental to Internet topology research. Spatial analysis of the Internet is needed to develop network planning, optimal routing algorithms, and failure detection measures. A first step toward achieving such goals is the availability of network topologies at different levels of granularity, facilitating realistic simulations of new Internet systems. The main objective of this survey is to familiarize the reader with research on network topology over the past decade. We study techniques for inference, modeling, and generation of the Internet topology at both the router and administrative levels. We also compare the mathematical models assigned to various topologies and the generation tools based on them. We conclude with a look at emerging areas of research and potential future research directions.

Cost modeling and evaluation of capital expenditures in optical multilayer networks

Abstract: Optical multilayer networks offer a high degree of freedom in network design, adapting to actual network requirements (demand types, topologies, etc.) and achieving cost-efficient realizations. Capital expenditures are one of the key differentiators for the evaluation of multilayer networks. A realistic cost model for Internet protocol/multiprotocol label switching (IP/MPLS), carrier-grade Ethernet, synchronous digital hierarchy/optical transport network (SDH/OTN), and WDM equipment from which overall capital expenditures can consistently be derived is contributed and discussed. A comprehensive collection of detailed cost values for different equipment types is presented. Furthermore, the cost model is applied to two case studies, one IP/MPLS-over-WDM study and one WDM study with two topologies, showing substitution effects of network elements to achieve overall capital expenditure minimization.

Review of traffic data estimations extracted from cellular networks

Abstract: One of the main characteristics of modern society is the never-ending increase in mobility. This leads to a series of problems such as congestion and increased pollution. To resolve these problems, it is imperative to have a good road network management and planning. To efficiently identify the characteristics of traffic in the road network, it would be necessary to perform a permanent monitorisation of all roadway links. This would involve an excessive cost of installation and maintenance of road infrastructure. Hence, new alternatives are required which can characterise traffic in a real time with good accuracy at an acceptable price. Mobile telephone systems are considered as a promising technology for the traffic data collection system. Its extensive use in converting its subscribers in a broad sample to draw information from phones becomes anonymous probes to monitor traffic. It is reviewed how to obtain parameters related to traffic from cellular-network-based data, describing methods used in existing simulation works as well as field tests in the academic and industrial field.

Radio planning and coverage optimization of 3G cellular networks

Abstract: Radio planning and coverage optimization are critical issues for service providers and vendors that are deploying third generation mobile networks and need to control coverage as well as the huge costs involved. Due to the peculiarities of the Code Division Multiple Access (CDMA) scheme used in 3G cellular systems like UMTS and CDMA2000, network planning cannot be based only on signal predictions, and the approach relying on classical set covering formulations adopted for second generation systems is not appropriate. In this paper we investigate mathematical programming models for supporting the decisions on where to install new base stations and how to select their configuration (antenna height and tilt, sector orientations, maximum emission power, pilot signal, etc.) so as to find a trade-off between maximizing coverage and minimizing costs. The overall model takes into account signal-quality constraints in both uplink and downlink directions, as well as the power control mechanism and the pilot signal. Since even small and simplified instances of this NP-hard problem are beyond the reach of state-of-the-art techniques for mixed integer programming, we propose a Tabu Search algorithm which provides good solutions within a reasonable computing time. Computational results obtained for realistic instances, generated according to classical propagation models, with different traffic scenarios (voice and data) are reported and discussed.

Discrete Optimization A hierarchical location model for public facility planning

Abstract: In this article, we present a discrete hierarchical location model for public facility planning. The main features of the model are: an accessibility maximization objective; several levels of demand and of facilities; a nested hierarchy of facilities (i.e. a facility of a given level can serve demand of equal and lower levels); maximum and minimum capacity constraints; and user-to-facility assignment constraints. The latter include single-assignment and closest-assignment constraints, as well as a new type of constraints called path-assignment constraints. Their purpose is to enforce some desirable properties for the spatial pattern of assignments. If they are not included, model solutions are difficult to interpret and to explain in a public facility planning context, therefore being less likely to be accepted by the users. The usefulness of the model is illustrated through a real-world application to school network planning. 2007 Elsevier B.V. All rights reserved.

Robust solutions for network design under transportation cost and demand uncertainty

Abstract: In many applications, the network design problem (NDP) faces significant uncertainty in transportation costs and demand, as it can be difficult to estimate current (and future values) of these quantities. In this paper, we present a robust optimization-based formulation for the NDP under transportation cost and demand uncertainty. We show that solving an approximation to this robust formulation of the NDP can be done efficiently for a network with single origin and destination per commodity and general uncertainty in transportation costs and demand that are independent of each other. For a network with path constraints, we propose an efficient column generation procedure to solve the linear programming relaxation. We also present computational results that show that the approximate robust solution found provides significant savings in the worst case while incurring only minor sub-optimality for specific instances of the uncertainty.

Mixed-Integer Nonlinear Programming Models and Algorithms for Large-Scale Supply Chain Design with Stochastic Inventory Management

Abstract: An important challenge for most chemical companies is to simultaneously consider inventory optimization and supply chain network design under demand uncertainty. This leads to a problem that requires integrating a stochastic inventory model with the supply chain network design model. This problem can be formulated as a large-scale combinatorial optimization model that includes nonlinear terms. Since these models are very difficult to solve, they require exploiting their properties and developing special solution techniques to reduce the computational effort. In this work, we analyze the properties of the basic model and develop solution techniques for a joint supply chain network design and inventory management model for a given product. The model is formulated as a nonlinear integer programming problem. By reformulating it as a mixed-integer nonlinear programming (MINLP) problem and using an associated convex relaxation model for initialization, we first propose a heuristic method to quickly obtain good-...

Near-Optimal Network Design with Selfish Agents

Abstract: We introduce a simple network design game that models how independent selfish agents can build or maintain a large network. In our game every agent has a specific connectivity requirement, i.e. each agent has a set of terminals and wants to build a network in which his terminals are connected. Possible edges in the network have costs and each agent's goal is to pay as little as possible. Determining whether or not a Nash equilibrium exists in this game is NP-complete. However, when the goal of each player is to connect a terminal to a common source, we prove that there is a Nash equilibrium as cheap as the optimal network, and give a polynomial time algorithm to find a (1+e)-approximate Nash equilibrium that does not cost much more. For the general connection game we prove that there is a 3-approximate Nash equilibrium that is as cheap as the optimal network, and give an algorithm to find a (4.65+e)-approximate Nash equilibrium that does not cost much more.

Biomimetic reliability strategies for self-healing vascular networks in engineering materials.

Abstract: Self-healing via a vascular network is an active research topic, with several recent publications reporting the application and optimization of these systems. This work represents the first consideration of the probable failure modes of a self-healing system as a driver for network design. The critical failure modes of a proposed self-healing system based on a vascular network were identified via a failure modes, effects and criticality analysis and compared to those of the human circulatory system. A range of engineering and biomimetic design concepts to address these critical failure modes is suggested with minimum system mass the overall design driver for high-performance systems. Plant vasculature has been mimicked to propose a segregated network to address the risk of fluid leakage. This approach could allow a network to be segregated into six separate paths with a system mass penalty of only approximately 25%. Fluid flow interconnections that mimic the anastomoses of animal vasculatures can be used within a segregated network to balance the risk of failure by leakage and blockage. These biomimetic approaches define a design space that considers the existing published literature in the context of system reliability.

Circuit-Switched Coherence

Abstract: Our characterization of a suite of commercial and scientific workloads on a 16-core cache-coherent chip multiprocessor (CMP) shows that overall system performance is sensitive to on-chip communication latency, and can degrade by 20% or more due to long interconnect latencies. On the other hand, communication bandwidth demand is low. These results prompt us to explore circuit-switched networks. Circuit-switched networks can significantly lower the communication latency between processor cores, when compared to packet-switched networks, since once circuits are set up, communication latency approaches pure interconnect delay. However, if circuits are not frequently reused, the long setup time can hurt overall performance, as is demonstrated by the poor performance of traditional circuit-switched networks - all applications saw a slowdown rather than a speedup with a traditional circuit-switched network. To combat this problem, we propose hybrid circuit switching (HCS), a network design which removes the circuit setup time overhead by intermingling packet-switched flits with circuit-switched flits. Additionally, we co-design a prediction-based coherence protocol that leverages the existence of circuits to optimize pair-wise sharing between cores. The protocol allows pair-wise sharers to communicate directly with each other via circuits and drives up circuit reuse. Circuit-switched coherence provides up to 23% savings in network latency which leads to an overall system performance improvement of up to 15%. In short, we show HCS delivering the latency benefits of circuit switching, while sustaining the throughput benefits of packet switching, in a design realizable with low area and power overhead.

Carbon Market Sensitive Green Supply Chain Network Design

Abstract: This paper introduces a mixed integer mathematical model formulation for the ?Carbon-Market Sensitive - Green Supply Chain Network Design? problem (CMS/GSCND) where carbon trading considerations are integrated within the supply chain network design phase. The solution methodology allows the evaluation of different strategic decisions alternatives, such as supplier and subcontractor selection, product allocation, capacity utilization, and transportation configuration, and their impact in terms of carbon footprint. This new formulation provides decision makers with the ability to understand the trade-offs between total logistics costs and the impact of greenhouse gases reduction. It also allows offsetting the latter through both supply chain reengineering and carbon trading. Model validation, results, and extended analysis are demonstrated via a numerical study.

Linear Programming Models for the User and System Optimal Dynamic Network Design Problem: Formulations, Comparisons and Extensions

Abstract: In this paper we formulate a network design model in which the traffic flows satisfy dynamic user equilibrium conditions for a single destination. The model presented here incorporates the Cell Transmission Model (CTM); a traffic flow model capable of capturing shockwaves and link spillovers. Comparisons are made between the properties of the Dynamic User equilibrium Network Design Problem (DUE NDP) and an existing Dynamic System Optimal (DSO) NDP formulation. Both network design models have different objective functions with similar constraint sets which are linear and convex. Numerical demonstrations are made on multiple networks to demonstrate the efficacy of the model and demonstrate important differences between the DUE and DSO NDP approaches. In addition, the flexibility of the approach is demonstrated by extending the formulation to account for demand uncertainty. This is formulated as a stochastic programming problem and initial test results are demonstrated on test networks. It is observed that not accounting for demand uncertainty explicitly, provides sub-optimal solution to the DUE NDP problem.

Distance and time in intermodal goods transport networks in Europe: A generic approach

Abstract: This paper is about distance and time as factors of competitiveness of intermodal transport. It reviews the relevance of the factors, evaluates time models in practice, compares network distances and times in alternative bundling networks with geometrically varied layouts, and points out how these networks perform in terms of vehicle scale, frequency and door-to-door time. The analysis focuses on intermodal transport in Europe, especially intermodal rail transport, but is in search for generic conclusions. The paper does not incorporate the distance and time results in cost models, and draws conclusions for transport innovation, wherever this is possible without cost modelling. For instance, the feature vehicle scale, an important factor of transport costs, is analysed and discussed. Distance and time are important factors of competitiveness of intermodal transport. They generate (direct) vehicle costs and – via transport quality – indirect costs to the customers. Clearly direct costs/prices are the most important performance of the intermodal transport system. The relevance of quality performances is less clarified. Customers emphasise the importance of a good match between the transport and the logistic system. In this framework (time) reliability is valued high. Often transport time, arrival and departure times, and frequency have a lower priority. But such conclusions can hardy be generalised. The range of valuations reflects the heterogeneity of situations. Some lack of clarity is obviously due to overlapping definitions of different performance types. The following parts of the paper are about two central fields of network design, which have a large impact on transport costs and quality, namely the design of vehicle roundtrips (and acceleration of transport speed) and the choice of bundling type: do vehicles provide direct services or run in what we call complex bundling networks? An example is the hub-and-spoke network. The objective of complex bundling is to increase vehicle scale and/or transport frequency even if network volumes are restricted. Complex bundling requires intermediate nodes for the exchange of load units. Examples of complex bundling networks are the hub-and-spoke network or the line network. Roundtrip and bundling design are interrelated policy fields: an acceleration of the roundtrip speed, often desirable from the cost point of view, can often only be carried out customer friendly, if the transport frequency is increased. But often the flow size is not sufficient for a higher frequency. Then a change of bundling model can be an outcome. Complex bundling networks are known to have longer average distances and times, the latter also due to the presence of additional intermediate exchange nodes. However, this disadvantage is – inside the limits of maximal vehicle sizes – overruled by the advantage of a restricted number of network links. Therefore generally, complex bundling networks have shorter total vehicle distances and times. This expression of economies of scale implies lower vehicle costs per load unit. The last part of the paper presents door-to-door times of load units of complex bundling networks and compares them with unimodal road transport. The times of complex bundling networks are larger than that of networks with direct connections, but nevertheless competitive with unimodal road transport, except for short distances.

Tabu Search Strategies for the Public Transportation Network Optimizations with Variable Transit Demand

Abstract: In this article, systematic tabu search (TS)-based heuristic methods are put forward and applied for the design of public transportation networks with variable demand. A multi-objective nonlinear mixed integer model is formulated. Solution methodologies are proposed, which consist of 3 main components: an initial candidate route set generation procedure that generates all feasible routes incorporating practical bus transit industry guidelines; a network analysis procedure that decides transit demand matrix, assigns transit trips, determines service frequencies, and computes performance measures; and a Tabu search method (TSM) that combines these 2 parts, guides the candidate solution generation process, and selects an optimal set of routes from the huge solution space. Comprehensive tests are conducted and sensitivity analyses are performed. Characteristics analyses are undertaken and solution qualities from different algorithms are compared. Numerical results indicate that the preferred TSM outperforms the genetic algorithm used as a benchmark for the optimal bus transit route network design problem without zone demand aggregation.