Skip to main content
main-content

2022 | Buch

Integrating Edge Intelligence and Blockchain

What, Why, and How

verfasst von: Xiaofei Wang, Chao Qiu, Xiaoxu Ren, Zehui Xiong, Victor C. M. Leung, Dusit Niyato

Verlag: Springer International Publishing

Buchreihe: Wireless Networks

share
TEILEN
insite
SUCHEN

Über dieses Buch

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.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.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
Abstract
Along with the wave of informatization technology, a booming era of artificial intelligence (AI) has emerged. In specific, with the proliferation of wireless communication, immense volumes of data are generated by mega-scale terminal devices instead of traditional cloud datacenters. According to the prediction by Ericsson (IoT connections outlook: NB-IoT and CAT-M technologies will account for close to 45 percent of cellular IoT connections in 2024. [Online]. Available: https://​www.​ericsson.​com/​en/​mobilityreport/​reports/​june-2019/​iot-connections-outlook ) and international data corporation (IDC) (Ericsson, Cisco Annual Internet Report (2018–2023). er[Online]. Available: https://​www.​cisco.​com/​c/​en/​us/​solutions/​collateral/​executive-perspectives/​annual-internet-report/​white-paper-c11-741490.​pdf ), internet of things (IoT) devices will generate 45% of the 40 zettabytes (ZB) global Internet data in 2024, while there will be 5.3 billion total Internet users and 29.3 billion networked devices by 2023. Nevertheless, global devices transferring extremely vast data to cloud datacenters will demand high bandwidth and powerful computational resources (Heintz et al. (Optimizing grouped aggregation in geo-distributed streaming analytics, in Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing, HPDC, ed. by T. Kielmann, D. Hildebrand, M. Taufer (2015), pp. 133–144)), thus creating a bottleneck on the restricted network transmission capabilities, computing power of computing infrastructures, strict delay requirements, etc. Edge intelligence (EI), as a complementary processing architecture by combining edge computing (EC) (Shi et al. (IEEE Int Things J 3(5):637–646, 2016)) and AI, pushes the AI frontier from the cloud to the network edge to open the path for low latency and critical-computation (Li et al. (Edge intelligence: On-demand deep learning model co-inference with device-edge synergy, in Proceedings of the 2018 Workshop on Mobile Edge Communications (MECOMM@SIGCOMM) (2018), pp. 31–36) ).
Xiaofei Wang, Chao Qiu, Xiaoxu Ren, Zehui Xiong, Victor C. M. Leung, Dusit Niyato
Chapter 2. Overview of Edge Intelligence and Blockchain
Abstract
In this chapter, we introduce and explain the basic aspects in EI and BC such as the concept, architecture, background, characteristics, classification, working principle, development, and application. From these aspects, it can be conscious of the motivation and necessity of integration of EI and BC.
Xiaofei Wang, Chao Qiu, Xiaoxu Ren, Zehui Xiong, Victor C. M. Leung, Dusit Niyato
Chapter 3. Motivations for Integrating Edge Intelligence with Blockchain
Abstract
As shown in Fig. 3.1, the limitations of EI and the complementary advantages of BC are painfully clear. Spontaneously, the appearance of BC-assisted EI would be expected to pave the way for the development of emerging intelligent services. In this chapter, we first discuss the limitations of EI. Then, we elaborate the benefits of BC in EI.
Xiaofei Wang, Chao Qiu, Xiaoxu Ren, Zehui Xiong, Victor C. M. Leung, Dusit Niyato
Chapter 4. Blockchain Driven Edge Intelligence
Abstract
BC-driven EI focuses on addressing the challenges of EI as described in Chap. 4. In this chapter, we present the EI benefits that can be realized with the assistance of BC, including computing-power management, data administration and model optimization.
Xiaofei Wang, Chao Qiu, Xiaoxu Ren, Zehui Xiong, Victor C. M. Leung, Dusit Niyato
Chapter 5. Tailoring Blockchain to Edge Intelligence
Abstract
Despite the great remarkably benefits brought by BC to edge EI, BC is still in the initial stage, and also facing critical challenges. To bring the gap between immature BC and EI amicable BC, it is necessary to acclimatize BC to EI. In this chapter, we probe into how to tailor BC to EI. from four perspectives, including flexible consensus protocol, effective incentive mechanism, intellectuality smart contract, and scalability.
Xiaofei Wang, Chao Qiu, Xiaoxu Ren, Zehui Xiong, Victor C. M. Leung, Dusit Niyato
Chapter 6. Research Challenges and Future Directions
Abstract
Although EI has promising prospects with the help of BC, there still exists lots of ongoing challenges that need to be considered in future research, which is quite important. In order to identify unresolved issues, understand existing challenges, and circumvent potential misleading directions, in this chapter we discuss open issues separately, including comprehensive architecture, quantization intelligence and trading intelligence.
Xiaofei Wang, Chao Qiu, Xiaoxu Ren, Zehui Xiong, Victor C. M. Leung, Dusit Niyato
Backmatter
Metadaten
Titel
Integrating Edge Intelligence and Blockchain
verfasst von
Xiaofei Wang
Chao Qiu
Xiaoxu Ren
Zehui Xiong
Victor C. M. Leung
Dusit Niyato
Copyright-Jahr
2022
Electronic ISBN
978-3-031-10186-1
Print ISBN
978-3-031-10185-4
DOI
https://doi.org/10.1007/978-3-031-10186-1