Optimization of coverage for georeferenced zones

En este artículo se presenta un análisis de las redes alámbricas e inalámbricas en los métodos tradicionalmente utilizados al aire libre, consideraremos la optimización en función de la capacidad, la cobertura e interferencia de un escenario georreferenciado; nos basaremos en el uso de algoritmos que nos ayudarán a la simulación de la conexión más óptima, el cual nos permitirá tener un nuevo análisis del escenario y ser capaz de ahorrar en los presupuestos de los equipos, conexiones y tiempo de instalación, así podemos garantizar la cobertura total para los usuarios. El cual el instalador tendrá la posibilidad de ver la conexión más adecuada para su escenario. El resultado del algoritmo presentado en una gráfica se podrá visualizar tanto la capacidad como la cobertura de la red de comunicación. Empezaremos con una cobertura mínima hasta llegar a la cobertura total de todos los usuarios.This article presents an analysis of the wired and wireless networks in the methods traditionally used outdoors, we will consider the optimization based on the capacity, coverage and interference of a georeferenced scenario; we will be based on the use of algorithms that will help us to simulate the optimal connection, which will allow us to have a new analysis of the scenario and be able to save on equipment budgets, connections and installation time, so we can guarantee the total coverage for users. The installer will have the possibility to see the most suitable connection for your scenario. The result of the algorithm presented in a graph will be able to visualize both the capacity and the coverage of the communication network. We will begin with a minimum coverage until we reach the total coverage of all users

Enabling Technology in Optical Fiber Communications: From Device, System to Networking

This book explores the enabling technology in optical fiber communications. It focuses on the state-of-the-art advances from fundamental theories, devices, and subsystems to networking applications as well as future perspectives of optical fiber communications. The topics cover include integrated photonics, fiber optics, fiber and free-space optical communications, and optical networking

Energy and performance-optimized scheduling of tasks in distributed cloud and edge computing systems

Infrastructure resources in distributed cloud data centers (CDCs) are shared by heterogeneous applications in a high-performance and cost-effective way. Edge computing has emerged as a new paradigm to provide access to computing capacities in end devices. Yet it suffers from such problems as load imbalance, long scheduling time, and limited power of its edge nodes. Therefore, intelligent task scheduling in CDCs and edge nodes is critically important to construct energy-efficient cloud and edge computing systems. Current approaches cannot smartly minimize the total cost of CDCs, maximize their profit and improve quality of service (QoS) of tasks because of aperiodic arrival and heterogeneity of tasks. This dissertation proposes a class of energy and performance-optimized scheduling algorithms built on top of several intelligent optimization algorithms. This dissertation includes two parts, including background work, i.e., Chapters 3–6, and new contributions, i.e., Chapters 7–11. 1) Background work of this dissertation. Chapter 3 proposes a spatial task scheduling and resource optimization method to minimize the total cost of CDCs where bandwidth prices of Internet service providers, power grid prices, and renewable energy all vary with locations. Chapter 4 presents a geography-aware task scheduling approach by considering spatial variations in CDCs to maximize the profit of their providers by intelligently scheduling tasks. Chapter 5 presents a spatio-temporal task scheduling algorithm to minimize energy cost by scheduling heterogeneous tasks among CDCs while meeting their delay constraints. Chapter 6 gives a temporal scheduling algorithm considering temporal variations of revenue, electricity prices, green energy and prices of public clouds. 2) Contributions of this dissertation. Chapter 7 proposes a multi-objective optimization method for CDCs to maximize their profit, and minimize the average loss possibility of tasks by determining task allocation among Internet service providers, and task service rates of each CDC. A simulated annealing-based bi-objective differential evolution algorithm is proposed to obtain an approximate Pareto optimal set. A knee solution is selected to schedule tasks in a high-profit and high-quality-of-service way. Chapter 8 formulates a bi-objective constrained optimization problem, and designs a novel optimization method to cope with energy cost reduction and QoS improvement. It jointly minimizes both energy cost of CDCs, and average response time of all tasks by intelligently allocating tasks among CDCs and changing task service rate of each CDC. Chapter 9 formulates a constrained bi-objective optimization problem for joint optimization of revenue and energy cost of CDCs. It is solved with an improved multi-objective evolutionary algorithm based on decomposition. It determines a high-quality trade-off between revenue maximization and energy cost minimization by considering CDCs’ spatial differences in energy cost while meeting tasks’ delay constraints. Chapter 10 proposes a simulated annealing-based bees algorithm to find a close-to-optimal solution. Then, a fine-grained spatial task scheduling algorithm is designed to minimize energy cost of CDCs by allocating tasks among multiple green clouds, and specifies running speeds of their servers. Chapter 11 proposes a profit-maximized collaborative computation offloading and resource allocation algorithm to maximize the profit of systems and guarantee that response time limits of tasks are met in cloud-edge computing systems. A single-objective constrained optimization problem is solved by a proposed simulated annealing-based migrating birds optimization. This dissertation evaluates these algorithms, models and software with real-life data and proves that they improve scheduling precision and cost-effectiveness of distributed cloud and edge computing systems

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Optimising BFWA networks

Broadband Fixed Wireless Access (BFWA) networks are an attractive alternative to cable-based technologies, in offering low-cost, high-speed data services, telephony and video-on-demand to residential and business users. However, in order to compete successfully with available alternative telecommunications solutions, the planning and design of efficient networks is crucial. This thesis presents two tools that enable the planning and evaluation of BFWA networks. AgentOpt is a network design and optimisation tool. A detailed account of the novel scheme, using the principles of emergent, selforganising systems, which AgentOpt employs for finding profit-optimal networks is given. The use of two distinct types of agent entity allows the multi-objective profit/coverage nature of the network planning problem to be satisfied. AgentOpt networks are compared with designs produced by other methods to establish to what extent this decentralised agent approach can optimise BFWA networks. The Network Validation Tool (NVT) analyses the network designs produced by AgentOpt and other automatic cell planning tools (ACPs). This is achieved through simulating the subscription take-up of the potential users in the network. By repetition of this process, statistical data about the various design configurations of the network is produced. This allows a planning engineer to compare and contrast network solutions that may differ in design but perform similarly in terms of expected profit. In this work the NVT is used to formulate some general guidelines about the best-practice use of ACPs

Advances in Intelligent Vehicle Control

This book is a printed edition of the Special Issue Advances in Intelligent Vehicle Control that was published in the journal Sensors. It presents a collection of eleven papers that covers a range of topics, such as the development of intelligent control algorithms for active safety systems, smart sensors, and intelligent and efficient driving. The contributions presented in these papers can serve as useful tools for researchers who are interested in new vehicle technology and in the improvement of vehicle control systems

A metaheuristic bandwidth allocation scheme for FiWi networks using Ant Colony Optimization

Optical-wireless access networks constitute a quite attractive solution to meet the ever-increasing bandwidth requirements of end-users, offering significant benefits such as ubiquitous coverage in the wireless domain and huge bandwidth in the optical domain. However, converging optical and wireless networking technologies, with Passive Optical Networks (PONs) and 4G wireless standards, such as the Worldwide Interoperability for Microwave Access (WiMAX) and the Long Term Evolution (LTE), entails major challenges that need to be addressed. In this context, designing an efficient and fair bandwidth distribution with Quality of Service (QoS) support is a difficult task due to the interdependence of resource allocation process to both optical and wireless domains. Specifically, the bandwidth distribution in the optical domain has to be aware of the mobile user heterogeneity in the wireless domain, while in the wireless domain the allocation process depends on the optical transmission grant opportunities. In this work a metaheuristic approach to govern the bandwidth allocation in modern Fiber Wireless (FiWi) networks is proposed. The Ant Colony Optimization (ACO) method is effectively employed in order to optimize the bandwidth report process of Mobile Subscribers (MSs). Simulation results reveal the effectiveness of the proposed approach in terms of latency and network throughput