## 6 Edge Computing  
### Cloud Computing and Edge Computing  
Cloud computing is a revolutionary technology that has revolutionized how individuals and businesses access, store, and process data. It is the practice of storing, managing, and processing data using a network of servers hosted on the Internet instead of local servers or personal devices. The concept of cloud computing has acquired immense popularity due to its numerous advantages, such as increased scalability, lower costs, and greater flexibility [55]. The activity of processing and analyzing data closer to the source of creation, often on or near the device or sensor that gathers the data, is referred to as edge computing. This method minimizes latency and bandwidth by allowing for real-time analysis and reaction and eliminating the need to transport all data to the cloud for processing. Edge computing is appropriate for applications requiring rapid decisions or minimal latency, such as driverless cars, industrial automation, and remote monitoring. Edge computing and cloud computing are two complementary technologies that work together to provide efficient and effective computing solutions [56]. On the other hand, cloud computing is a centralized strategy that incorporates the storage, administration, and processing of data on distant servers accessible over the Internet. The cloud provides enormous storage capacity, scalability, and computing power, making it ideal for large-scale data processing, analytics, and complicated computing activities. Without depending on local infrastructure, cloud computing enables enterprises to store and access data and applications from anywhere at any time. Edge computing and cloud computing display constructive interaction. Edge computing offloads specific processing work from the cloud by analyzing data and making decisions on edge devices. It aids in the reduction in network congestion, the reduction in dependency on cloud services, and the improvement in reaction times and performance. Edge computing may filter and prioritize data before delivering it to the cloud, minimizing the quantity of raw data delivered while maximizing cloud resource use. Cloud computing, in exchange, offers a centralized infrastructure that supports edge devices, allowing them to use increased computational capabilities, machine learning techniques, and access to huge quantities of historical data saved in the cloud. Cloud computing simplifies edge device administration, monitoring, upgrades, and software deployment [57; 58]. Distributed edge computing is a promising approach for next-generation networks (NGNs) to achieve the ultimate demands of such networks [56]. Multiple-access edge computing (MEC) represents a common form of the distributed edge paradigm, which provides computing services at the edge of the radio access network. The local servers at the edge contain the capabilities of the remote cloud at various scales. Fog computing is another model of distributed edge computing, which provides less capable servers than MEC but with closer distances to end users and higher deployment flexibility. The two edge computing models meet modern communication networks' latency, availability, reliability, and energy requirements, including smart city applications and ultra-reliable low-latency