Showing papers on "Network planning and design published in 2014"

Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application

Abstract: This paper presents a robust network design model for the supply of blood during and after disasters. A practical optimization model is developed that can assist in blood facility location and allocation decisions for multiple post-disaster periods. The application of the proposed model is investigated in a case problem where real data is utilized to design a network for emergency supply of blood during potential disasters. Our analysis on the tradeoff between solution robustness and model robustness arrives at important practical insights. The performance of the proposed ‘robust optimization’ approach is also compared with that of an ‘expected value’ approach.

FireFly: a reconfigurable wireless data center fabric using free-space optics

Abstract: Conventional static datacenter (DC) network designs offer extreme cost vs. performance tradeoffs---simple leaf-spine networks are cost-effective but oversubscribed, while "fat tree"-like solutions offer good worst-case performance but are expensive. Recent results make a promising case for augmenting an oversubscribed network with reconfigurable inter-rack wireless or optical links. Inspired by the promise of reconfigurability, this paper presents FireFly, an inter-rack network solution that pushes DC network design to the extreme on three key fronts: (1) all links are reconfigurable; (2) all links are wireless; and (3) non top-of-rack switches are eliminated altogether. This vision, if realized, can offer significant benefits in terms of increased flexibility, reduced equipment cost, and minimal cabling complexity. In order to achieve this vision, we need to look beyond traditional RF wireless solutions due to their interference footprint which limits range and data rates. Thus, we make the case for using free-space optics (FSO). We demonstrate the viability of this architecture by (a) building a proof-of-concept prototype of a steerable small form factor FSO device using commodity components and (b) developing practical heuristics to address algorithmic and system-level challenges in network design and management.

A Base Integer Programming Model and Benchmark Suite for Liner-Shipping Network Design

Abstract: The liner-shipping network design problem is to create a set of nonsimple cyclic sailing routes for a designated fleet of container vessels that jointly transports multiple commodities. The objective is to maximize the revenue of cargo transport while minimizing the costs of operation. The potential for making cost-effective and energy-efficient liner-shipping networks using operations research OR is huge and neglected. The implementation of logistic planning tools based upon OR has enhanced performance of airlines, railways, and general transportation companies, but within the field of liner shipping, applications of OR are scarce. We believe that access to domain knowledge and data is a barrier for researchers to approach the important liner-shipping network design problem. The purpose of the benchmark suite and the paper at hand is to provide easy access to the domain and the data sources of liner shipping for OR researchers in general. We describe and analyze the liner-shipping domain applied to network design and present a rich integer programming model based on services that constitute the fixed schedule of a liner shipping company. We prove the liner-shipping network design problem to be strongly NP-hard. A benchmark suite of data instances to reflect the business structure of a global liner shipping network is presented. The design of the benchmark suite is discussed in relation to industry standards, business rules, and mathematical programming. The data are based on real-life data from the largest global liner-shipping company, Maersk Line, and supplemented by data from several industry and public stakeholders. Computational results yielding the first best known solutions for six of the seven benchmark instances is provided using a heuristic combining tabu search and heuristic column generation.

Spatial modeling of the traffic density in cellular networks

Abstract: Modeling and simulation of a cellular network typically assumes that the target area is divided into regular hexagonal cells and mobile stations (MSs) are uniformly scattered in each cell. This implies a statistically uniform distribution of traffic load over space, but in reality the spatial traffic distribution is highly non-uniform across different cells, which calls for actual spatial traffic models. In this article, we first present the analysis of traffic measurements collected from commercial cellular networks in China, and demonstrate that the spatial distribution of the traffic density (the traffic load per unit area) can be approximated by the log-normal or Weibull distribution depending on time and space. Then we propose a spatial traffic model which generates large-scale spatial traffic variations by a sum of sinusoids that captures the characteristics of log-normally distributed and spatially correlated cellular traffic. The proposed model can be directly used to generate realistic spatial traffic patterns for cellular network simulations, such as performance evaluations of network planning and load balancing.

Survivor: An enhanced controller placement strategy for improving SDN survivability

Abstract: In SDN, forwarding devices can only operate correctly while connected to a logically centralized controller To avoid single-point-of-failure, controller architectures are usually implemented as distributed systems In this context, recent literature identified fundamental issues, such as device isolation and controller overload, and proposed controller placement strategies to tackle them However, current proposals have crucial limitations: (i) device-controller connectivity is modeled using single paths, yet in practice multiple concurrent connections may occur; (ii) peaks in the arrival of new flows are only handled on-demand, assuming that the network itself can sustain high request rates; and (iii) failover mechanisms require predefined information, which, in turn, has been overlooked This paper proposes Survivor, a controller placement strategy that addresses these challenges The strategy explicitly considers path diversity, capacity, and failover mechanisms at network design Comparisons to the state-of-the-art on survivable controller placement show that Survivor is superior because (a) path diversity increases the survivability significantly; and (b) capacity-awareness is essential to handle overload during both normal and failover states

A Network Lifetime Enhancement Method for Sink Relocation and Its Analysis in Wireless Sensor Networks

Abstract: Recent advances in micromanufacturing technology have enabled the development of low-cost, low-power, multifunctional sensor nodes for wireless communication. Diverse sensing applications have also become a reality as a result. These include environmental monitoring, intrusion detection, battlefield surveillance, and so on. In a wireless sensor network (WSN), how to conserve the limited power resources of sensors to extend the network lifetime of the WSN as long as possible while performing the sensing and sensed data reporting tasks, is the most critical issue in the network design. In a WSN, sensor nodes deliver sensed data back to the sink via multihopping. The sensor nodes near the sink will generally consume more battery power than others; consequently, these nodes will quickly drain out their battery energy and shorten the network lifetime of the WSN. Sink relocation is an efficient network lifetime extension method, which avoids consuming too much battery energy for a specific group of sensor nodes. In this paper, we propose a moving strategy called energy-aware sink relocation (EASR) for mobile sinks in WSNs. The proposed mechanism uses information related to the residual battery energy of sensor nodes to adaptively adjust the transmission range of sensor nodes and the relocating scheme for the sink. Some theoretical and numerical analyze are given to show that the EASR method can extend the network lifetime of the WSN significantly.

Optimal synchronization of complex networks.

Abstract: We study optimal synchronization in networks of heterogeneous phase oscillators. Our main result is the derivation of a synchrony alignment function that encodes the interplay between network structure and oscillators' frequencies and that can be readily optimized. We highlight its utility in two general problems: constrained frequency allocation and network design. In general, we find that synchronization is promoted by strong alignments between frequencies and the dominant Laplacian eigenvectors, as well as a matching between the heterogeneity of frequencies and network structure.

On the impacts of locally adaptive signal control on urban network stability and the Macroscopic Fundamental Diagram

Abstract: Urban traffic networks are inherently unstable when congested. This instability causes a natural tendency towards spatially inhomogeneous vehicle distributions and less consistent and reproducible relationships between urban traffic variables. It is important to find ways to mitigate this unstable behavior since well-defined relationships between average network flow and density – the MFD – are useful to aid network design and control. This paper examines the impacts of locally adaptive traffic signals – e.g., those that allocate green times proportionally to upstream approach densities – on network stability and the MFD. A family of adaptive signal control strategies is examined on two abstractions of an idealized grid network using an analytical model and an interactive simulation. The results suggest that locally adaptive traffic signals provide stability when the network is moderately congested, which increases average flows and decreases the likelihood of gridlock. These benefits increase with the overall adaptivity of the signals. However, adaptive signals appear to have little to no effect on network stability or the MFD in heavily congested networks as vehicle movement becomes more constrained by downstream congestion and queue spillbacks. Under these conditions, other strategies should be used to mitigate the instability, such as adaptively routing drivers to avoid locally congested regions. These behaviors are verified using more realistic micro-simulations and are consistent with other observations documented in the literature.

Routing, spectrum and core allocation in flexgrid SDM networks with multi-core fibers

Abstract: Space division multiplexing (SDM) over multi-core fiber (MCF) is advocated as a promising technology to overcome the capacity limit of the current single-core optical networks. However, employing the MCF for flexgrid networks necessitates the development of new concepts, such as routing, spectrum and core allocation (RSCA) for traffic demands. The introduction of MCF in the networks mitigates the spectrum continuity constraint of the routing and spectrum assignment (RSA) problem. In fact cores can be switched freely on different links during routing of the network traffic. Similarly, the route disjointness for demands with same allocated spectrum diminishes to core disjointness at the link level. On the other hand, some new issues such as the inter-core crosstalk should be taken into account while solving the RSCA problem. This paper formulates the RSCA network planning problem using the integer linear programming (ILP) formulation. The aim is to optimally minimize the maximum number of spectrum slices required on any core of MCF of a flexgrid SDM network. Furthermore, a scalable and effective heuristic is proposed for the same problem and its performance is compared with the optimal solution. The results show that the proposed algorithm is able to well approximate the optimal solution based on ILP model.

Cooperative distributed optimization for the hyper-dense small cell deployment

Abstract: The fifth generation mobile networks will be developed to improve area spectral and energy efficiency, and provide uniform user experience. Hyper-dense small cell deployment can move devices closer to the wireless network and satisfy 5G system requirements. The main challenge of this network deployment results from the random deployment, dynamic on-off, flexible connection to cellular core networks, and flat system architecture of 5G systems. Therefore, conventional network planning and radio resource management, which depend on a central control node, cannot be applied to small cell networks. In this article some cooperative distributed radio resource management algorithms for time synchronization, carrier selection, and power control are discussed for hyper-dense small cell deployment.

Efficient Allocation of Electric Vehicles Charging Stations: Optimization Model and Application to a Dense Urban Network

Abstract: The deployment of Electric Vehicles (EVs) needs an optimized and cost-effective implementation of charging stations. As a decision support tool for network design, we define a methodology to allocate charging stations in a real network. This study uses trip OD matrix information from household travel survey coupled with a dynamic vehicle model to evaluate EVs consumption based on realistic trips (urban drive cycles). These trips are computed based on routing tools and supplied with elevation information. This enables an accurate characterization of energy needs in the Lyon Metropolitan Area. All these parameters are used as inputs of an integer linear optimization program for the location of charging stations. The methodology is based on an adaption of the classic fixed charge location model with a p-dispersion constraint. The results indicate that this methodology can help the future implementation of charging stations at an urban scale.

Synchronization analysis of complex networks with multi-weights and its application in public traffic network

Abstract: On the basis of traditional weighted network, we study a new complex network model with multi-weights, which has one or several different types of weights between any two nodes. According to the method of network split, we split the complex network with multi-weights into several different complex networks with single weight, and study its global synchronization. Taking bus lines as the network nodes, a new public traffic roads network model with multi-weights is established by the proposed network model and space R modeling approach. Then based on the Lyapunov stability theory, the criteria is designed for the global synchronization of the public traffic roads networks with multi-weights. By changing the different weights and taking the Lorenz chaotic system for example, some numerical examples are given to discuss the balance of the whole public traffic roads network.

Scheduled Service Network Design for Freight Rail Transportation

Abstract: This paper addresses the scheduled service network design problem for freight rail transportation. The proposed model integrates service selection and scheduling, car classification and blocking, train makeup, and routing of time-dependent customer shipments based on a cyclic three-layer space--time network representation of the associated operations and decisions and their relations and time dimensions. This paper also proposes a matheuristic solution methodology integrating slope scaling, a dynamic block-generation mechanism, long-term-memory-based perturbation strategies, and ellipsoidal search, a new intensification mechanism to thoroughly explore very large neighborhoods of elite solutions restricted using information from the history of the search. Experimental results show that the proposed solution method is efficient and robust, yielding high-quality solutions for realistically sized problem instances.

Determining the operations performed along a service path/service chain

Abstract: Presented herein are techniques performed in a network comprising a plurality of network nodes each configured to apply one or more service functions to traffic that passes the respective network nodes in a service path. At a network node, an indication is received of a failure or degradation of one or more service functions or applications applied to traffic at the network node. Data descriptive of the failure or degradation is generated. A previous service hop network node at which a service function or application was applied to traffic in the service path is determined. The data descriptive of the failure or degradation is communicated to the previous service hop network node.

Sustainable reverse logistics network design for household plastic waste

Abstract: Plastic recycling is a legal requirement and can yield environmental benefits In the Netherlands, there is a complex network of various collection methods, separation centers, sorting centers and reprocessors The first step of the recycling system, separating plastics from other waste, can occur within households (source-separation) or in separation centers (post-separation), making a difference in collection channel choice and technology requirements The purpose of this paper is to provide decision support on choosing the most suitable combination of separation methods in the Netherlands Decision support is given through optimized reverse logistics network design which makes the overall recycling system more efficient and sustainable, while taking into account the interests of various stakeholders (municipalities, households, etc) A mixed integer linear programming (MILP) model, which minimizes both transportation cost and environmental impact, is used in this network design The research follows the approach of scenario study; the baseline scenario is the current situation and other scenarios are designed with various strategic alternatives Modeling is conducted by using a graphical optimization tool IBM LogicNet Plus 71 Comparing these scenarios, the results show that the current network settings of the baseline situation is efficient in logistics terms but has a potential to adapt to strategic changes, depending on the assumptions regarding availability of the required processing facilities to treat plastic waste In some of the tested scenarios, a separate collection channel for Polyethylene Terephthalate (PET) bottles is cost efficient and saves carbon emission Although the figures differ depending on the separation method choices of municipalities, our modeling result of all the tested scenarios shows a saving of more than 25 % carbon emission compared to the current network

AllAboard: A System for Exploring Urban Mobility and Optimizing Public Transport Using Cellphone Data

Abstract: This paper describes a system to leverage data on cell phones to understand mobility patterns and presents a large-scale network design model for public transit while considering existing service offerings. The work is motivated by the rapid urbanization in growth market cities across the world, where adequate resources to develop detailed travel demand models may be absent. Urban growth is coupled with high cell phone penetration which transit operators can leverage to better match observed demand for travel with service offerings. Based on call detail records from a telecommunications operator in Abidjan, Cote d’Ivoire, this paper describes analytics and optimization techniques that result in system-wide journey time improvements of 10%. The main contribution of this paper is to demonstrate how big data analytics and optimization tools can transform data from opportunistic sensing in the real-world to improve urban mobility outcomes.

An integrated approach for timetabling and vehicle scheduling problems to analyze the trade-off between level of service and operating costs of transit networks

Abstract: In transit systems there is a critical trade-o between the level of service and operating costs. At the planning level, for a given network design, this trade-o is captured by the timetabling (TT) and vehicle scheduling (VS) problems. In the TT problem we try to maximize the number of passengers beneted by well timed transfers, while in the VS problem we seek to minimize the operating costs, which are related to the eet size. This paper presents two integer linear programming models for the TT and VS problems, and combines them in a bi-objective integrated model. We propose and implement an -constraint method to jointly solve this TT and VS bi-objective problem. This allows to analyze the trade-o between these two criteria in terms of Pareto fronts. Numerical experiments show that our proposed approach can solve scenarios with up to 50 bus lines.

Closed loop supply chain network design and optimisation using fuzzy mixed integer linear programming model

Abstract: Owing to the revolution in sustainable and green manufacturing the production planning and network design of closed loop supply chain concept has got the attention of researchers and managers. In this paper, a multi-product, multi-facility capacitated closed-loop supply chain framework is proposed in an uncertain environment including reuse, refurbish, recycle and disposal of parts. The uncertainty related to demand, fraction of parts recovered for different product recovery processes, product acquisition cost, purchasing cost, transportation cost, processing, and set-up cost is handled with fuzzy numbers. A fuzzy mixed integer linear programming model is proposed to decide optimally the location and allocation of parts at each facility and number of parts to be purchased from external suppliers in order to maximise the profit of organisation. The proposed solution methodology is able to generate a balanced solution between the feasibility degree and degree of satisfaction of the decision maker. The propo...

Solving Routing and Spectrum Allocation Related Optimization Problems: From Off-Line to In-Operation Flexgrid Network Planning

Abstract: Compared to wavelength switched optical networks (WSON), flexgrid optical networks provide higher spectrum efficiency and flexibility. To properly analyze, design, plan, and operate flexgrid networks, the routing and spectrum allocation (RSA) problem must be solved. The RSA problem involves two different constraints: the continuity constraint to ensure that the allocated spectral resources are the same along the links in the route and the contiguity constraint to guarantee that those resources are contiguous in the spectrum. As a consequence of its complexity, it is crucial that efficient methods are available to allow solving realistic problem instances in practical times. In this paper, we review different RSA-related optimization problems that arise within the life-cycle of flexgrid networks. Different methods to solve those optimization problems are reviewed along with the different requirements related to where those problems appear. Starting from its formulation, we analyze network life-cycle and indicate different solving methods for the kind of problems that arise at each network phase: from off-line to in-operation network planning. We tackle two representative use cases: i) a use case for off-line planning where a flexgrid network is designed and periodically upgraded, and ii) multilayer restoration as a use case for in-operation planning. Three solving methods are proposed for the off-line planning problem: mathematical programming, column generation and metaheuristics, whereas, as a result of its stringent required solving times, two heuristic methods are presented for the on-line problem.

Benders Decomposition for Discrete–Continuous Linear Bilevel Problems with application to traffic network design

Abstract: We propose a new fast solution method for linear Bilevel Problems with binary leader and continuous follower variables under the partial cooperation assumption. We reformulate the Bilevel Problem into a single-level problem by using the Karush–Kuhn–Tucker conditions. This non-linear model can be linearized because of the special structure achieved by the binary leader decision variables and subsequently solved by a Benders Decomposition Algorithm to global optimality. We illustrate the capability of the approach on the Discrete Network Design Problem which adds arcs to an existing road network at the leader stage and anticipates the traffic equilibrium for the follower stage. Because of the non-linear objective functions of this problem, we use a linearization method for increasing, convex and non-linear functions based on continuous variables. Numerical tests show that this algorithm can solve even large instances of Bilevel Problems.

Optimal design of energy-efficient and cost-effective wireless body area networks

Abstract: Wireless Body Area Networks (WBANs) represent one of the most promising approaches for improving the quality of life, allowing remote patient monitoring and other healthcare applications. The deployment of a WBAN is a critical issue that impacts both the network lifetime and the total energy consumed by the network. This work investigates the optimal design of wireless body area networks by studying the joint data routing and relay positioning problem, in order to increase the network lifetime. To this end, we propose a mixed integer linear programming model, the Energy-Aware WBAN Design model, which optimizes the number and location of relays to be deployed and the data routing towards the sink, minimizing both the network installation cost and the energy consumed by wireless sensors and relays. We solve the proposed model in both realistic WBAN scenarios and general topologies, and compare the model performance to the most notable approaches proposed in the literature. Numerical results demonstrate that our model (1) provides a good tradeoff between the energy consumption and the number of installed relays, and (2) designs energy-efficient and cost-effective WBANs in a short computation time, thus representing an interesting framework for the dynamic WBAN design problem.