Network Science and Graph Analytics

  Introduction Communication networks form the foundation of modern society by enabling the rapid exchange of information across the globe. From mobile phones and satellite communications to the Internet, cloud computing, and the emerging Internet of Things (IoT), today's interconnected world depends on sophisticated hardware and advanced materials. Among these materials, rare earth minerals play an indispensable role in supporting the performance, reliability, and miniaturization of communication technologies. Rare earth minerals comprise seventeen elements, including the fifteen lanthanides together with scandium and yttrium. These elements possess unique magnetic, optical, electrical, and luminescent properties that make them essential for manufacturing electronic components, fiber-optic communication systems, wireless infrastructure, semiconductors, sensors, and advanced computing devices. Although present in relatively small quantities within communication equipment, their ...

  Introduction Network security has become one of the most critical areas of research in the digital era. As governments, businesses, healthcare organizations, financial institutions, educational establishments, and individuals increasingly depend on interconnected systems, protecting digital infrastructure from cyber threats has become a global priority. Excellence in research in network security represents the pursuit of innovative technologies, scientific methodologies, and practical solutions that safeguard data confidentiality, integrity, and availability. Researchers continuously develop advanced security frameworks to combat evolving cyberattacks while ensuring secure communication across complex networks. Understanding Network Security Network security refers to the collection of technologies, policies, protocols, and practices designed to protect computer networks and sensitive information from unauthorized access, cyberattacks, malware, ransomware, phishing, denial-of-ser...

Wireless communication has transformed the way people connect, communicate, and access information. From the early days of analog mobile phones to today's ultra-fast 5G networks, wireless technology has evolved at an extraordinary pace. It has become the backbone of modern society, supporting everything from smartphones and smart homes to industrial automation and autonomous vehicles. As digital transformation accelerates worldwide, recent advancements in wireless networking are paving the way for faster, more reliable, and more intelligent communication systems. Emerging technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), Wi-Fi 7, satellite internet, edge computing, and the development of sixth-generation (6G) networks promise to redefine the future of wireless connectivity. Evolution of Wireless Networks Wireless communication began with simple radio transmissions and gradually evolved into cellular networks. The progression from 1G to 5G has dramat...

  Introduction In the era of digital connectivity and big data, understanding relationships among entities has become a central challenge in network science and data analytics. Two closely related areas that address this challenge are Link Prediction and Recommender Systems . Both techniques aim to identify potential connections that are not currently observed but are likely to occur in the future. While link prediction focuses on forecasting future or missing relationships in networks, recommender systems utilize similar principles to suggest products, services, information, or social connections to users. The rapid growth of online platforms, social media, e-commerce websites, and digital content repositories has increased the importance of these technologies. Organizations rely on them to improve user experience, enhance engagement, and support decision-making processes. As a result, link prediction and recommender systems have become fundamental components of modern intelligen...

Graph data structures and algorithms form a fundamental pillar of computer science, enabling the modeling and analysis of complex relationships and interconnected systems. A graph is a mathematical representation consisting of a set of vertices (or nodes) and edges (or links) that connect pairs of vertices. This simple yet powerful abstraction is widely used to represent networks such as social connections, transportation systems, communication networks, biological systems, and the structure of the web. Understanding graph data structures and the algorithms that operate on them is essential for solving a wide range of real-world problems efficiently. Fundamentals of Graph Data Structures At its core, a graph is defined as G = (V, E), where V represents the set of vertices and E represents the set of edges. Graphs can be classified based on various properties. For instance, a graph may be directed or undirected. In a directed graph (digraph), edges have a direction, indicating a one-w...