國立高雄大學圖資館 |

登入

回首頁

Edge intelligencefrom theory to practice /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Edge intelligenceby Javid Taheri ... [et al.].
其他題名:	from theory to practice /
其他作者:	Taheri, Javid.
出版者:	Cham :Springer International Publishing :2023.
面頁冊數:	1 online resource (xiv, 247 p.) :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Edge computing.
電子資源:	https://doi.org/10.1007/978-3-031-22155-2
ISBN:	9783031221552$q(electronic bk.)

Edge intelligencefrom theory to practice /
Edge intelligencefrom theory to practice /[electronic resource] :by Javid Taheri ... [et al.]. - Cham :Springer International Publishing :2023. - 1 online resource (xiv, 247 p.) :ill., digital ;24 cm.

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.

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.

ISBN: 9783031221552$q(electronic bk.)

Standard No.: 10.1007/978-3-031-22155-2doiSubjects--Topical Terms:

875964
Edge computing.

LC Class. No.: QA76.583

Dewey Class. No.: 004.6

Edge intelligencefrom theory to practice /
LDR:03041nmm a2200325 a 4500 001 637592
003 DE-He213
005 20230513230342.0
006 m d
007 cr nn 008maaau
008 230921s2023 sz s 0 eng d
020 $a 9783031221552$q(electronic bk.)
020 $a 9783031221545$q(paper)
024 7 $a 10.1007/978-3-031-22155-2 $2 doi
035 $a 978-3-031-22155-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.583
072 7 $a UKN $2 bicssc
072 7 $a COM075000 $2 bisacsh
072 7 $a UKN $2 thema
082 0 4 $a 004.6 $2 23
090 $a QA76.583 $b .E23 2023
245 0 0 $a Edge intelligence $h [electronic resource] : $b from theory to practice / $c by Javid Taheri ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a 1 online resource (xiv, 247 p.) : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Edge computing. $3 875964
650 0 $a Artificial intelligence. $3 194058
650 1 4 $a Computer Communication Networks. $3 218087
650 2 4 $a Software Engineering. $3 274511
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a System Performance and Evaluation. $3 273898
700 1 $a Taheri, Javid. $3 944085
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-22155-2
950 $a Computer Science (SpringerNature-11645)