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.

Experimental Demonstration of an Impairment Aware Network Planning and Operation Tool for Transparent/Translucent Optical Networks

Abstract: Core optical networks using reconfigurable optical switches and tunable lasers appear to be on the road towards widespread deployment and could evolve to all-optical mesh networks in the coming future. Considering the impact of physical layer impairments in the planning and operation of all-optical (and translucent) networks is the main focus of the Dynamic Impairment Constraint Optical Networking (DICONET) project. The impairment aware network planning and operation tool (NPOT) is the main outcome of DICONET project, which is explained in detail in this paper. The key building blocks of the NPOT, consisting of network description repositories, the physical layer performance evaluator, the impairment aware routing and wavelength assignment engines, the component placement modules, failure handling, and the integration of NPOT in the control plane are the main contributions of this study. Besides, the experimental result of DICONET proposal for centralized and distributed control plane integration schemes and the performance of the failure handling in terms of restoration time is presented in this study.

Sampling Design Methods For Groundwater Modeling Under Uncertainty

Abstract: A sampling network design model is presented that evaluates the trade-off between the varying costs of different types of data and the contribution of those data to improving model reliability The methodology couples parameter-estimate and model-prediction uncertainty analyses with optimization to identify the mix of hydrogeologic information (eg, head, concentration, and/or hydraulic conductivity measurement locations) that will minimize model prediction uncertainty for a given data collection budget Two alternative optimization algorithms are presented and compared: a branch-and-bound algorithm and a genetic algorithm A series of synthetic examples are presented to demonstrate the adaptability of the methodology to different sampling scenarios The examples reveal two important properties of this network design problem First, model-parameter and model-prediction uncertainty analyses are important components of the network design methodology because they provide a natural framework for evaluating the cost/information trade-off for different types of data and different sampling network designs Second, the genetic algorithm can identify near-optimal solutions for a small fraction of the computational effort needed to determine the globally optimal solutions of the branch-and-bound algorithm

Optimized LTE Cell Planning With Varying Spatial and Temporal User Densities

Abstract: Base station (BS) deployment in cellular networks is one of the fundamental problems in network design. This paper proposes a novel method for the cell planning problem for fourth-generation (4G) cellular networks using metaheuristic algorithms. In this approach, we aim to satisfy both cell coverage and capacity constraints simultaneously by formulating an optimization problem that captures practical planning aspects. The starting point of the planning process is defined through a dimensioning exercise that captures both coverage and capacity constraints. Afterward, we implement a metaheuristic algorithm based on swarm intelligence (e.g., particle swarm optimization or the recently proposed gray-wolf optimizer) to find suboptimal BS locations that satisfy both problem constraints in the area of interest, which can be divided into several subareas with different spatial user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant BSs. We also perform Monte Carlo simulations to study the performance of the proposed scheme and compute the average number of users in outage. Next, the problems of green planning with regard to temporal traffic variation and planning with location constraints due to tight limits on electromagnetic radiations are addressed, using the proposed method. Finally, in our simulation results, we apply our proposed approach for different scenarios with different subareas and user distributions and show that the desired network quality-of-service (QoS) targets are always reached, even for large-scale problems.