Textbook in PDF format

This book examines whether the integration of edge intelligence (EI) and blockchain (BC) can open up new horizons for providing ubiquitous intelligent services. Accordingly, the authors conduct a summarization of the recent research efforts on the existing works for EI and BC, further painting a comprehensive picture of the limitation of EI and why BC could benefit EI. To examine how to integrate EI and BC, the authors discuss the BC-driven EI and tailoring BC to EI, including an overview, motivations, and integrated frameworks. Finally, some challenges and future directions are explored. The book explores the technologies associated with the integrated system between EI and BC, and further bridges the gap between immature BC and EI-amicable BC. Along with the wave of informatization technology, an unprecedented booming era of Artificial Intelligence (AI) has emerged. Meanwhile, with the proliferation of wireless communication, immense volumes of data are generated by mega-scale terminals instead of traditional cloud datacenters. Driving by these trends, Edge Intelligence (EI) has elicited escalating attention. Instead of entirely relying on the cloud, EI makes the most of the widespread edge resources to gain AI insight. It is yet facing critical challenges in its decentralized management and security, limiting its capabilities to support services with numerous requirements. In this monograph, the blockchain (BC) has been seen as a promising solution to tackle the above issues, further support EI. There are a lot of definitions of EI. In general, EI is derived from the combination of EC and AI, which could be explained in two dimensions that are AI in Edge and AI for Edge. AI in Edge means putting AI applications as close as possible to the end-users by making full use of the superiority of EC architecture. EI combines AI technology with EC technology, making the AI algorithm run on the device that can perform EC. This has the advantage of processing data in real-time without having to connect to a cloud platform. Explores the integration of edge intelligence (EI) and blockchain (BC), including their integrated motivations, frameworks and challenges; Presents how BC-driven EI can realize computing-power management, data administration, and model optimization; Describes how to tailor BC to better support EI, including flexible consensus protocol, effective incentive mechanism, intellectuality smart contract, and scalable BC system tailoring; Presents some key research challenges and future directions for the integrated system