Optimization for Edge Computing

This book chapter addresses the dynamic environment of edge computing’s imperative optimization area. Understanding the aims and methods of optimization is essential given the spread of edge devices and the complexity nature of applications. Task offloading, edge caching, network optimization, resource allocation, and privacy-aware optimization are just a few of the optimization strategies covered in this chapter. In-depth information on the particular difficulties and potential solutions for using these methods in edge computing settings is provided in each subsection. The chapter also examines the complex issues of edge optimization in situations with heterogeneous devices and the idea of edge node clustering for improving system performance. The chapter also discusses assessment and performance analysis tools to guarantee the viability and efficacy of certain optimization measures. It goes through how important tools for profiling, benchmarking, tracing, containerization, and the newly developed field of edge analytics are for determining how efficient and effective edge computing systems are. By the end of this chapter, readers will have a thorough grasp of the complex field of edge computing optimization, enabling them to create and put into use edge systems that are very effective and quick.