Self-Driving Networks

This chapter presents a new vision of network operations, the self-driving network, that takes automation to the next level. This is not a description of existing work; rather, it is a challenge to dramatically rethink how we manage networks (or rather, how we do not manage networks). It draws upon an analogy with the development of self-driving cars and presents motivations for this effort. It then describes the technologies needed to implement this and an overall architecture of the system. As this endeavor will cause a major shift in network management, the chapter offers an evolutionary path to the end goal. Some of the consequences and human impacts of such a system are touched upon. The chapter concludes with some research topics and a final message. Key takeaways are that machine learning and feedback loops are fundamental to the solution; a key outcome is to build systems that are adaptive and predictive, for the benefit of users.

Veracity Assessment of Multimedia Facebook Posts for Infodemic Symptom Detection using Bi-modal Unsupervised Machine Learning Approach

Ascertaining the truthfulness and trustworthiness of information posted on social media has been challenging with the proliferation of unsubstantiated, misleading, and inciting news, with different intents by purveyors. Unlike the traditional media with some level of regulations, user-generated posts on social networks does not pass through censorships in order to establish the truism of news items hence the need to be cautious of posted information on the networks. The lingering issue of recent suspension of Twitter microblogging site by the Nigerian government and the consequent decision to regulate social network operations in the country similarly centers on the subject of social media dependability for legitimate social engagements by millions of savvy Nigerian users. Whereas existing models in literature have proposed state-of-the-arts, this study seeks to improve on obtainable studies with a bi-modal machine learning methodology that indicate symptoms of infodemic social media posts. Using a multimedia facebook corpus, an unsupervised natural language processor, Inception v3 model, coupled with a hierarchical clustering network, is deployed for the duo of image and text sentiment analytics. Experimental result uniquely identified infodemic tendencies in facebook text-corpus and efficiently differentiates image-corpus into respective clusters through the Euclidian distance metrics. The most infodemic post returned a -0.9719 compound score while the most positive post returns 0.9488. Veracity assessment of polarized opinions expressed in negative clusters reveals that provocative, derogatory, obnoxious, etc. indicate propensity for infodemic tendencies. Keywords: Fake news. Facebook. Social media. Sentiment Analysis. Infodemic

GPF: A Green Power Forwarding Technique for Energy-Efficient Network Operations

The energy consumption of network infrastructures is increasing; therefore, research efforts designed to diminish this growing carbon footprint are necessary. Building on prior work, which determined a difference in the energy consumption of network hardware based on their forwarding configurations and developed a real-time network energy monitoring tool, this research proposes a novel technique to incorporate individual device energy efficiency into network routing decisions. A new routing metric and algorithm are presented to select the lowest-power, least-congested paths between destinations, known as Green Power Forwarding (GPF). In addition, a network dial is developed to enhance GPF by allowing network administrators to tune the network to optimally operate between energy savings and network performance. To ensure the scope of this research for industry adoption, implementation details for different generations of networking infrastructure (past, present, and future) are also discussed. The experiment results indicate that significant energy and, in turn, cost savings can be achieved by employing the proposed GPF technique without a reduction in network performance. The future directions for this research include developing dynamically-tuning network dial modes and extending the principles to inter-domain routing.

An Algorithm for Improving Email Security on the Android Operating System in the Industry 4.0 Era

The world is attesting a tremendous change today, which is remarkably coined as industry 4.0. With several technologies shaping industry 4.0 epoch, notably, its cybersecurity entails the security of communication and network operations activities. The most common form of communication in organisations and business today is electronic mails (email). One of the major threats to email communication is the lack of confidentiality for emails accessed via Android mobile devices due to the weaknesses of the Android operating system (OS) platform. In this study, an algorithm was designed and implemented on an Android application that allows an email sender to compose an email and set the time the email stays in the receiver inbox before it automatically wipes off. Primary data were collected from email users using tightly structured questionnaires and respondents comprised of those with email technical background and typical email users, while secondary data from scholarly journals and articles informed the study design. The designed algorithm was tested and evaluated through expert opinion. The result of the study indicates that the autowipe algorithm addresses the confidentiality issues and threats on Android email clients.

Increased Resilience Using Close Loop Renewable Microgrids in the Surabaya Distribution System as a Self-Healing Application

Distribution system reconfiguration has two main objectives, namely as optimization of network operations and as system recovery in case of disturbances. It is necessary to consider the reconfiguration process and the process of using Distributed Generation (DG) or microgrid as an additional supply to reduce the possibility of failure, loss of power, or a voltage drop. Therefore the first step in research This results in the candidate bus 14 and bus 52 on the Mulyosari feeder which must be reconfigured by cutting off the flow at L13 and L50 because the losses on both buses are the worst with a value of 0.01370MW and 0.00900MW using the calculation algorithm of Binary Particle Swarm Optimization (BPSO) to predict the location of possible failures and the placement DG, and selected on bus 29 and bus 45 which were injected DG with a PV capacity of 15 kW each, after the self-healing was applied to the system, power flow analysis was carried out, and get good results g is very satisfactory with the total losses in the system decreased from 0.363MW to 0.116MW from this study we can conclude that self-healing can only be done if the distribution system is a complex radial.

Network Amelioration, AI Automation and Future Integration in Wireless Networks

The deployment of 5G mobile communication networks is just getting started right now. There are numerous technologies available today, each capable of fulfilling activities such as enabling voice traffic via voice over IP (VoIP), providing broadband data access in mobile environments, and so on. However, there is a pressing need to implement technology that can bring all of these systems together into a single unified system. Because it is all about smoothly integrating terminals, networks, and applications, 8G presents a solution to this dilemma. In this work, an attempt is made to provide a study of various cellular technologies, such as 4G, 5G, 6G, 7G, and FG, as well as a detailed comparison between them. With the introduction of network virtualization and the implementation of 5G/IoT, mobile networks will become more complicated and offer more diverse services. This raises concerns about a considerable increase in the workload of network operations. Meanwhile, artificial intelligence (AI) is advancing rapidly and is projected to alleviate human resource shortages in a variety of industries. Similarly, the mobile industry is gaining traction in the application of artificial intelligence (AI) to network operations in order to improve the efficiency of mobile network operations. This paper will address the idea of using AI technology to network operations and will give various use examples to demonstrate that AI-driven network operations have a bright future. Keywords: 5G & 6G networks, Artificial Intelligence, Next generation network, Future Advancement.

A Unique Unified Wind Speed Approach to Decision-Making for Dispersed Locations

The repercussions of high levels of environmental pollution coupled with the low reserves and increased costs of traditional energy sources have led to the widespread adaptation of wind energy worldwide. However, the expanded use of wind energy is accompanied by major challenges for electric grid operators due to the difficulty of controlling and forecasting the production of wind energy. The development of methods for addressing these problems has therefore attracted the interest of numerous researchers. This paper presents an innovative method for assessing wind speed in different and widely spaced locations. The new method uses wind speed data from multiple sites as a single package that preserves the characteristics of the correlations among those sites. Powerful Waikato Environment for Knowledge Analysis (Weka) machine learning software has been employed for supporting data preprocessing, clustering, classification, visualization, and feature selection and for using a standard algorithm to construct decision trees according to a training set. The resultant arrangement of the sites according to likely wind energy productivity facilitates enhanced decisions related to the potential for the effective operation of wind energy farms at the sites. The proposed method is anticipated to provide network operators with an understanding of the possible productivity of each site, thus facilitating their optimal management of network operations. The results are also expected to benefit investors interested in establishing profitable projects at those locations.