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"Network management systems"
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Terraform : up and running : writing infrastructure as code
\"Terraform has become a key player in the DevOps world for defining, launching, and managing infrastructure as code (IaC) across a variety of cloud and virtualization platforms, including AWS, Google Cloud, Azure, and more. This hands-on second edition, expanded and thoroughly updated for Terraform version 0.12 and beyond, shows you the fastest way to get up and running. Gruntwork cofounder Yevgeniy (Jim) Brikman walks you through dozens of code examples that demonstrate how to use Terraform's simple, declarative programming language for deploying and managing infrastructure with a few commands. Veteran sysadmins, DevOps engineers, and novice developers will quickly go from Terraform basics to running a full stack that can support a massive amount of traffic and a large team of developers. Explore changes from Terraform 0.9 through 0.12, including backends, workspaces, and first-class expressions. Learn how to write production-grade Terraform modules. Dive into manual and automated testing for Terraform code. Compare Terraform to Chef, Puppet, Ansible, CloudFormation, and Salt Stack. Deploy server clusters, load balancers, and databases. Use Terraform to manage the state of your infrastructure. Create reusable infrastructure with Terraform modules. Use advanced Terraform syntax to achieve zero-downtime deployment.\" - back cover.
Book
Method and Algorithm for Topology Automatic Discovery in Complicated Passive Optical Network Architecture
Passive Optical Network (PON) plays an important role in optical access network due to its characteristics of resources saving and network protocol transparency. In the process of running and operating a PON system, a reliable network management system (NMS) is necessary. In order to acquisition the management object, NMS should perform topology automatic discovery process with the help of embedded software. Aiming at various types of the convergence network’s topology and the complicated architecture, this article proposes a topology automatic discovery algorithm to promote the network management. We have designed and verified the automatic discovery method on our simulation platform with SNMP-Agent-enabled OLTs.
Journal Article
Green and software-defined wireless networks : from theory to practice
\"Understand the fundamental theory and practical design aspects of green and soft wireless communications networks with this expert text. It provides comprehensive and unified coverage of 5G physical layer design, as well as design of the higher and radio access layers and the core network, drawing on viewpoints from both academia and industry. Get to grips with the theory through authoritative discussion of information-theoretical results, and learn about fundamental green design trade-offs, software-defined network architectures, and energy-efficient radio resource management strategies. Applications of wireless big data and artificial intelligence to wireless network design are included, providing an excellent design reference, and real-world examples of employment in software-defined 5G networks and energy-saving solutions from wireless communications companies and cellular operators help to connect theory with practice. This is an essential text for graduate students, professionals and researchers\"-- Provided by publisher.
Book
Blockchain-Based Malicious Behaviour Management Scheme for Smart Grids
The smart grid optimises energy transmission efficiency and provides practical solutions for energy saving and life convenience. Along with a decentralised, transparent and fair trading model, the smart grid attracts many users to participate. In recent years, many researchers have contributed to the development of smart grids in terms of network and information security so that the security, reliability and stability of smart grid systems can be guaranteed. However, our investigation reveals various malicious behaviours during smart grid transactions and operations, such as electricity theft, erroneous data injection, and distributed denial of service (DDoS). These malicious behaviours threaten the interests of honest suppliers and consumers. While the existing literature has employed machine learning and other methods to detect and defend against malicious behaviour, these defence mechanisms do not impose any penalties on the attackers. This paper proposes a management scheme that can handle different types of malicious behaviour in the smart grid. The scheme uses a consortium blockchain combined with the best–worst multi-criteria decision method (BWM) to accurately quantify and manage malicious behaviour. Smart contracts are used to implement a penalty mechanism that applies appropriate penalties to different malicious users. Through a detailed description of the proposed algorithm, logic model and data structure, we show the principles and workflow of this scheme for dealing with malicious behaviour. We analysed the system’s security attributes and tested the system’s performance. The results indicate that the system meets the security attributes of confidentiality and integrity. The performance results are similar to the benchmark results, demonstrating the feasibility and stability of the system.
Journal Article
Deep Learning with Graph Convolutional Networks: An Overview and Latest Applications in Computational Intelligence
Convolutional neural networks (CNNs) have received widespread attention due to their powerful modeling capabilities and have been successfully applied in natural language processing, image recognition, and other fields. On the other hand, traditional CNN can only deal with Euclidean spatial data. In contrast, many real-life scenarios, such as transportation networks, social networks, reference networks, and so on, exist in graph data. The creation of graph convolution operators and graph pooling is at the heart of migrating CNN to graph data analysis and processing. With the advancement of the Internet and technology, graph convolution network (GCN), as an innovative technology in artificial intelligence (AI), has received more and more attention. GCN has been widely used in different fields such as image processing, intelligent recommender system, knowledge-based graph, and other areas due to their excellent characteristics in processing non-European spatial data. At the same time, communication networks have also embraced AI technology in recent years, and AI serves as the brain of the future network and realizes the comprehensive intelligence of the future grid. Many complex communication network problems can be abstracted as graph-based optimization problems and solved by GCN, thus overcoming the limitations of traditional methods. This survey briefly describes the definition of graph-based machine learning, introduces different types of graph networks, summarizes the application of GCN in various research fields, analyzes the research status, and gives the future research direction.
Journal Article
A Survey on Machine-Learning Techniques for UAV-Based Communications
Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless communication networks. Their adoption in various communication-based applications is expected to improve coverage and spectral efficiency, as compared to traditional ground-based solutions. However, this new degree of freedom that will be included in the network will also add new challenges. In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes. In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such as channel modeling, resource management, positioning, and security.
Journal Article
An overview on integrated localization and communication towards 6G
while the fifth generation (5G) cellular system is being deployed worldwide, researchers have started the investigation of the sixth generation (6G) mobile communication networks. Although the essential requirements and key usage scenarios of 6G are yet to be defined, it is believed that 6G should be able to provide intelligent and ubiquitous wireless connectivity with Terabits per second (Tbps) data rate and sub-millisecond (sub-ms) latency over three-dimensional (3D) network coverage. To achieve such goals, acquiring accurate location information of the mobile terminals is becoming extremely useful, not only for location-based services but also for improving wireless communication performance in various ways such as channel estimation, beam alignment, medium access control, routing, and network optimization. On the other hand, the advancement of communication technologies also brings new opportunities to greatly improve the localization performance, as exemplified by the anticipated centimeter-level localization accuracy in 6G by extremely large-scale multiple-input multiple-output (MIMO) and millimeter wave (mmWave) technologies. In this regard, a unified study on integrated localization and communication (ILAC) is necessary to unlock the full potential of wireless networks for dual purposes. While there are extensive studies on wireless localization or communications separately, the research on ILAC is still in its infancy. Therefore, this article aims to give a tutorial overview on ILAC towards 6G wireless networks. After a holistic survey on wireless localization basics, we present the state-of-the-art results on how wireless localization and communication inter-play with each other in various network layers, together with the main architectures and techniques for localization and communication co-design in current two-dimensional (2D) and future 3D networks with aerial-ground integration. Finally, we outline some promising future research directions for ILAC.
Journal Article
A Smart Waste Management Solution Geared towards Citizens
Global industry is undergoing major transformations with the genesis of a new paradigm known as the Internet of Things (IoT) with its underlying technologies. Many company leaders are investing more effort and money in transforming their services to capitalize on the benefits provided by the IoT. Thereby, the decision makers in public waste management do not want to be outdone, and it is challenging to provide an efficient and real-time waste management system. This paper proposes a solution (hardware, software, and communications) that aims to optimize waste management and include a citizen in the process. The system follows an IoT-based approach where the discarded waste from the smart bin is continuously monitored by sensors that inform the filling level of each compartment, in real-time. These data are stored and processed in an IoT middleware providing information for collection with optimized routes and generating important statistical data for monitoring the waste collection accurately in terms of resource management and the provided services for the community. Citizens can easily access information about the public waste bins through the Web or a mobile application. The creation of the real prototype of the smart container, the development of the waste management application and a real-scale experiment use case for evaluation, demonstration, and validation show that the proposed system can efficiently change the way people deal with their garbage and optimize economic and material resources.
Journal Article
Utilization of 5G Technologies in IoT Applications: Current Limitations by Interference and Network Optimization Difficulties—A Review
5G (fifth-generation technology) technologies are becoming more mainstream thanks to great efforts from telecommunication companies, research facilities, and governments. This technology is often associated with the Internet of Things to improve the quality of life for citizens by automating and gathering data recollection processes. This paper presents the 5G and IoT technologies, explaining common architectures, typical IoT implementations, and recurring problems. This work also presents a detailed and explained overview of interference in general wireless applications, interference unique to 5G and IoT, and possible optimization techniques to overcome these challenges. This manuscript highlights the importance of addressing interference and optimizing network performance in 5G networks to ensure reliable and efficient connectivity for IoT devices, which is essential for adequately functioning business processes. This insight can be helpful for businesses that rely on these technologies to improve their productivity, reduce downtime, and enhance customer satisfaction. We also highlight the potential of the convergence of networks and services in increasing the availability and speed of access to the internet, enabling a range of new and innovative applications and services.
Journal Article