This chapter discusses the emerging paradigm of edge computing and its potential to optimize performance and enhance user experience in modern computing systems. The chapter begins by introducing the concept of edge computing, its definition, and its various applications. It then highlights the key benefits of edge computing. The chapter also delves into the various architectures and models of edge computing. It examines the challenges associated with edge computing, such as resource constraints, security, and privacy issues. The authors then provide an overview of the technologies and tools used in edge computing. They discuss how these technologies can be used to optimize performance and enhance user experience in edge computing systems. The chapter also presents several use cases and real-world applications of edge computing, including smart homes, autonomous vehicles, and healthcare systems. The authors examine the benefits and challenges of using edge computing in these domains and provide insights into how to optimize performance and enhance user experience.
TopIntroduction
Edge computing involves processing and analyzing data closer to where the data is actually originated. This is in contrast to using data from a cloud server. Hence, with edge computing, we basically deal with the distributed data rather than centralized one. It makes it a distributed computing paradigm. The term “edge” refers to the outer layer of an organization's network where data is generated, and the processing and analysis of that data occurs. Edge computing aims to reduce data processing time and bandwidth requirements by moving data processing closer to where the data is generated.
Traditional cloud computing models rely on data being sent to centralized data centers for processing and analysis, which can create latency and bandwidth issues, particularly in the case of large-scale data sets or real-time data streams. Edge computing addresses these challenges by performing data processing and analysis at the edge of the network, where the data is generated, without the need for data to be sent to a centralized location.
Edge computing has emerged as a result of the increasing demand for real-time, high-performance, and low-latency processing of data generated by Internet of Things (IoT) devices, autonomous systems, and other emerging technologies. By processing data closer to the source of data generation, edge computing offers several advantages over traditional cloud computing models, including reduced latency, improved data security, and enhanced reliability.
In fact, edge computing represents a significant shift in the way organizations process and analyze data, and it has the potential to transform industries ranging from healthcare to manufacturing to transportation.