# Network Diffusion Algorithms and Simulators in IoT and Space IoT: A Systematic Review
## 1 Introduction  
As the Internet of Things (IoT) continues to expand rapidly across various industries, gaining insights into how information spreads within these networks has become increasingly important [1]. Network diffusion algorithms and simulators serve as powerful tools for analyzing the propagation of data, malware, and other forms of communication within IoT systems [2, 3]. In the context of Space IoT, where device heterogeneity, dynamic topologies, and large-scale networks pose unique challenges, the demand for robust and scalable diffusion models is even more pronounced.  
Recent advancements in IoT applications have pushed the boundaries of what these technologies can achieve, particularly in domains involving drones and satellites. Drones are increasingly used for tasks such as surveillance, delivery, and environmental monitoring, requiring real-time communication and coordination within IoT networks. Satellite-based IoT systems are enhancing connectivity in areas where terrestrial networks are unavailable, such as remote regions, oceans, and deserts. By leveraging Low Earth Orbit (LEO)satellites, IoT devices can maintain consistent communication over vast distances, enabling applications in environmental monitoring, disaster management, and global logistics. These advancements address critical challenges in the IoT, including ensuring reliable communication over long distances, optimizing energy usage, and managing complex network topologies.  
This paper presents a systematic literature review (SLR) focusing on network diffusion algorithms and simulators utilized in IoT and Space IoT studies. By examining research published between 2013 and 2024, this review identifies key diffusion algorithms, including epidemic, cascading, and threshold-based models, and evaluates the performance of widely used network simulators, such as NS-3, Cooja, and OMNeT++ [4, 5, 6]. Additionally, the metrics used to assess these algorithms and simulators, such as scalability, energy efficiency, latency, and packet delivery ratio, are explored.  
The objective is to provide researchers and practitioners with a comprehensive analysis of the tools and methodologies used in studying network diffusion in IoT environments. By highlighting the strengths and limitations of various algorithms and simulators, this review aims to guide the selection of appropriate tools for simulating and evaluating IoT and Space IoT systems.  
This paper makes several significant contributions. It presents a comprehensive systematic literature review of network diffusion algorithms, simulators, and topologies within IoT and Space IoT, encompassing research from 2013 to 2024. Unlike previous surveys, this study is the first to integrate all three aspects--diffusion algorithms, network simulators, and network topologies--into a single, cohesive framework. By adhering to the PRISMA methodology, it ensures a rigorous and transparent selection process, addressing gaps left by earlier reviews. The study categorizes and examines key diffusion models, including epidemic, cascading, and threshold-based approaches, assessing their effectiveness across diverse IoT and Space IoT environments. Additionally, it evaluates widely used network simulators, such as NS-3, Cooja, and OMNeT++, analyzing their capabilities, scalability, and suitability for different network scenarios. Beyond this, the review identifies essential performance metrics--including scalability, energy efficiency, latency, and packet delivery ratio--providing valuable insights into the strengths and limitations of various diffusion models and simulators. Finally, the study outlines open challenges and future research directions, underscoring the need for more adaptable and resource-efficient models to meet the evolving demands of IoT and Space IoT systems.