Network planning and design

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

Wavelength-routed optical-networks: linear formulation, resource budgeting tradeoffs, and a reconfiguration study

Abstract: We consider a wavelength-routed optical network operated as a lightpath-based virtual topology. We present an exact linear programming formulation for the complete virtual topology design, including choice of constituent lightpaths, routes for these lightpaths, and intensity of packet flows through these lightpaths. By making a shift in the objective function to minimal hop distance and by relaxing the wavelength-continuity constraints (i.e., assuming wavelength converters at all nodes), we demonstrate that the entire optical network design problem can be linearized and hence solved optimally. The linear formulation can be used to design a balanced network, such that the utilizations of both transceivers and wavelengths are high, i.e., neither of these expensive resources are under-utilized. We also use the linear formulation to provide a reconfiguration methodology in order to adapt the virtual topology to changing traffic conditions.

Coverage prediction and optimization algorithms for indoor environments

Abstract: A heuristic algorithm is developed for the prediction of indoor coverage. Measurements on one floor of an office building are performed to investigate propagation characteristics and validations with very limited additional tuning are performed on another floor of the same building and in three other buildings. The prediction method relies on the free-space loss model for every environment, this way intending to reduce the dependency of the model on the environment upon which the model is based, as is the case with many other models. The applicability of the algorithm to a wireless testbed network with fixed WiFi 802.11b/g nodes is discussed based on a site survey. The prediction algorithm can easily be implemented in network planning algorithms, as will be illustrated with a network reduction and a network optimization algorithm. We aim to provide an physically intuitive, yet accurate prediction of the path loss for different building types.

Chapter 10 Design of survivable networks

Abstract: Publisher Summary This chapter focuses on the important practical and theoretical problem of designing survivable communication networks, i.e., communication networks that are still functional after the failure of certain network components. A very general model (for undirected networks) is presented which includes practical, as well as theoretical, problems, including the well-studied minimum spanning tree, Steiner tree, and minimum cost k-connected network design problems. The development of this area starts with outlining structural properties which are useful for the design and analysis of algorithms for designing survivable networks. These lead to worst-case upper and lower bounds. Heuristics that work well in practice are also described. Polynomially-solvable special cases of the general survivable network design problem are summarized. The chapter discusses polyhedral results from the study of these problems as integer programming models. The chapter provides complete and nonredundant descriptions of a number of polytopes related to network survivability problems of small dimensions. The computational results using cutting plane approaches basedon the polyhedral results are given. The results show that these methods are efficient and effective in producing optimal or near-optimal solutions to real-world problems. A brief review of the work on survivability models of directed networks is given.

A QoS-Provisioning neural fuzzy connection admission controller for multimedia high-speed networks

Abstract: This paper proposes a neural fuzzy approach for connection admission control (CAC) with QoS guarantee in multimedia high-speed networks. Fuzzy logic systems have been successfully applied to deal with traffic-control-related problems and have provided a robust mathematical framework for dealing with real-world imprecision. However, there is no clear and general technique to map domain knowledge on traffic control onto the parameters of a fuzzy logic system. Neural networks have learning and adaptive capabilities that can be used to construct intelligent computational algorithms for traffic control. However, the knowledge embodied in conventional methods is difficult to incorporate into the design of neural networks. The proposed neural fuzzy connection admission control (NFCAC) scheme is an integrated method that combines the linguistic control capabilities of a fuzzy logic controller and the learning abilities of a neural network. It is an intelligent implementation so that it can provide a robust framework to mimic experts' knowledge embodied in existing traffic control techniques and can construct efficient computational algorithms for traffic control. We properly choose input variables and design the rule structure for the NFCAC controller so that it can have robust operation even under dynamic environments. Simulation results show that compared with a conventional effective-bandwidth-based CAC, a fuzzy-logic-based CAC, and a neural-net-based CAC, the proposed NFCAC can achieve superior system utilization, high learning speed, and simple design procedure, while keeping the QoS contract.