Edge intelligence : from theory to practice / Javid Taheri, Schahram Dustdar, Albert Zomaya, Shuiguang Deng.
Taheri, Javid, author.; Dustdar, Schahram, author.; Zomaya, Albert Y., author.; Deng, Shuiguang, author.
2023
QA76.583
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Edge intelligence : from theory to practice / Javid Taheri, Schahram Dustdar, Albert Zomaya, Shuiguang Deng.
Author Taheri, Javid, author.
ISBN 9783031221552 (electronic bk.)
3031221559 (electronic bk.)
3031221540
9783031221545
DOI https://doi.org/10.1007/978-3-031-22155-2
Published Cham, Switzerland : Springer, 2023.
Language English
Description 1 online resource (243 pages) : illustrations (black and white, and color).
Item Number 10.1007/978-3-031-22155-2 doi
Call Number QA76.583
Dewey Decimal Classification 004.6
Summary This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Dustdar, Schahram, author.
Zomaya, Albert Y., author.
Deng, Shuiguang, author.
Available in Other Form EDGE INTELLIGENCE.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
1. Distributed Computing Continuum Systems
2. Containerized Edge Computing Platforms
3. AI/ML for Service Life Cycle at Edge
4. AI/ML for Computation Offloading
5. AI/ML Data Pipelines for Edge-Cloud Architectures
6. AI/ML on Edge
7. AI/ML for Service-Level Objectives.

Browse Subjects

Show more subjects...

Statistics

from
to
Export