000 08832nam a2200805 i 4500
001 9780750355933
003 IOP
005 20251030124830.0
006 m eo d
007 cr cn |||m|||a
008 240715s2024 enka fob 000 0 eng d
020 _a9780750355933
_qebook
020 _a9780750355926
_qmobi
020 _z9780750355919
_qprint
020 _z9780750355940
_qmyPrint
024 7 _a10.1088/978-0-7503-5593-3
_2doi
035 _a(CaBNVSL)thg00083956
035 _a(OCoLC)1446520278
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aQA76.583
_b.B464 2024eb
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
100 1 _aBenedict, Shajulin,
_eauthor.
_997032
245 1 _aEdge intelligence :
_bdeep learning-enabled edge computing /
_cShajulin Benedict.
246 3 _aDeep learning-enabled edge computing.
264 1 _aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :
_bIOP Publishing,
_c[2024]
300 _a1 online resource (various pagings) :
_billustrations (some color).
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
490 1 _a[IOP release $release]
490 1 _aIOP series in next generation computing
490 1 _aIOP ebooks. [2024 collection]
500 _a"Version: 20240601"--Title page verso.
504 _aIncludes bibliographical references.
505 _apart I. Introduction. 1. Edge intelligence -- 1.1. Edge computing -- 1.2. History of edge computing -- 1.3. Edge intelligence -- 1.4. Advantages : edge intelligence -- 1.5. Challenges : edge intelligence -- 1.6. Applications -- 1.7. The need for this book -- 1.8. Potential readers -- 1.9. Organization of the book
505 8 _a2. Edge computing architectures -- 2.1. Internet of Things -- 2.2. IoT-enabled components -- 2.3. Learning techniques : machine learning -- 2.4. Learning techniques : deep learning -- 2.5. Edge-AI architectures -- 2.6. Conclusion
505 8 _a3. Edge OS and programming models -- 3.1. Operating systems -- 3.2. Objectives of OS in edge devices (Edge OS) -- 3.3. Taxonomy of OS : toward edge -- 3.4. Edge OS : examples -- 3.5. Process states in edge-OS -- 3.6. FreeRTOS : OS for embedded devices -- 3.7. Conclusion
505 8 _apart II. Learning techniques. 4. Edge intelligence : learning techniques -- 4.1. Edge intelligence : a need -- 4.2. Federated learning -- 4.3. DNN splitting -- 4.4. Transfer learning -- 4.5. Gossip learning -- 4.6. Conclusion
505 8 _a5. Inference/prediction techniques -- 5.1. Learning stages -- 5.2. Inference knowledge levels -- 5.3. Distributed inferences -- 5.4. Distributed inferences : implementation strategies -- 5.5. Interactive versus batched inferences -- 5.6. Partitioning distributed inferences -- 5.7. Accelerating distributed inferences : strategies -- 5.8. Conclusion
505 8 _a6. Edge resources and accelerators -- 6.1. Edge resources : basics -- 6.2. Micro-controller-level devices : an edge? -- 6.3. Micro-processor-level devices : general purpose -- 6.4. GPUs, TPUs, and FPGAs : special purpose -- 6.5. SoC, SoM, system-on-board -- 6.6. Edge accelerators -- 6.7. Commercial edge accelerators -- 6.8. Examples and use-cases -- 6.9. Conclusion
505 8 _a7. Performance analysis of edge-enabled applications -- 7.1. Performance concerns -- 7.2. Model-specific performance concerns -- 7.3. Architecture-specific performance concerns -- 7.4. Algorithm-specific performance concerns -- 7.5. Data-specific performance concerns -- 7.6. Performance monitoring : a need -- 7.7. Performance monitoring : metrics -- 7.8. Energy-efficiency methods -- 7.9. Carbon efficiency methods -- 7.10. Workload scheduling and performance impacts -- 7.11. Performance monitoring tools -- 7.12. Cloud/fog/edge-level performance monitoring -- 7.13. Conclusion
505 8 _a8. Security in edge-AI systems -- 8.1. Existing security challenges -- 8.2. Security attacks in edge-AI -- 8.3. Data-specific vulnerabilities -- 8.4. Security architectures in edge-AI -- 8.5. Preventing security breaches : strategies -- 8.6. Tools and solutions -- 8.7. Conclusion
505 8 _apart III. Tools and solutions. 9. Frameworks : edge-AI platforms -- 9.1. Essential characteristics -- 9.2. Types of framework -- 9.3. Resource-allocation frameworks -- 9.4. Cloud-specific frameworks -- 9.5. Application-specific frameworks -- 9.6. Distributed federated learning frameworks -- 9.7. Conclusion
505 8 _a10. Orchestration platforms : computing continuum -- 10.1. Orchestration and integration -- 10.2. Algorithmic/application orchestration -- 10.3. Workload orchestration -- 10.4. Hierarchical versus non-hierarchical orchestration -- 10.5. Adaptiveness in orchestration -- 10.6. Automation in orchestration -- 10.7. Metric-oriented orchestration -- 10.8. Orchestration frameworks -- 10.9. Integration platforms
505 8 _apart IV. Applications. 11. Edge-AI applications -- 11.1. Applications -- 11.2. Edge-AI for healthcare -- 11.3. Industrial applications using edge-AI -- 11.4. Edge-AI for agriculture -- 11.5. Edge-AI for forensics -- 11.6. Edge-AI for mobility/logistics -- 11.7. Conclusion
505 8 _a12. Business opportunities using edge-AI -- 12.1. Digital business -- 12.2. Economic impacting factors -- 12.3. Business opportunities : edge-AI platforms -- 12.4. Cost models -- 12.5. Economic simulators for FaaS implementation -- 12.6. Conclusion
505 8 _a13. Challenges and future directions -- 13.1. Edge-AI challenges.
506 _aFull-text restricted to subscribers or individual document purchasers.
520 3 _aEdge Intelligence: deep learning-enabled edge computing is a book that targets researchers and practitioners who are interested in applying intelligence without compromising data privacy. The book reveals the existing edge-AI techniques and forecasts future edge-AI integration methods. The book delves into edge computing architectures after describing relevant basic technologies such as IoT, cloud computing, and other security-related architectures. The book starts with an explanation of all relevant basic technologies. It offers a smooth transition from the basics to insightful practical sessions for practitioners. The ideas of providing innovative ideas and applications in the later part of the book can enthuse researchers and developers to engage themselves in innovating newer products with the application of edge intelligence. Part of IOP Series in Next Generation Computing.
521 _aAcademic and commercial researchers.
530 _aAlso available in print.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
545 _aShajulin Benedict graduated in 2001 from Manonmaniam Sunderanar University, India, with Distinction. In 2004, he received an M.E Degree in Digital Communication and Computer Networking from A.K.C.E, Anna University, Chennai. He is the University second rank holder for his masters. He did his PhD degree in the area of Grid scheduling under Anna University, Chennai (Supervisor--Dr. V Vasudevan, Director, Software Technologies Group of TIFAC Core in Network Engineering). He was affiliated to the same group and published more papers in international journals. He served as Professor at SXCCE Research Centre of Anna University-Chennai. Later, he visited TUM Germany for teaching Cloud Computing as Guest Professor of TUM Germany. Now, he works at the Indian Institute of Information Technology Kottayam, Kerala, India, an institute of national importance of India. He serves as Director/PI/Representative Officer of AIC-IIIT Kottayam (Sec.8 Company) for nourishing young entrepreneurs of India. He is also working as a Guest Professor of TUM Germany. His research interests include HPC/Cloud/Grid scheduling, performance analysis of parallel applications (including exa-scale), cloud computing, IIoT, blockchain, parallel compilers, and so forth. His webpage can be found at: sbenedictglobal.com.
588 _aTitle from PDF title page (viewed on July 15, 2024).
650 _aEdge computing.
_997033
650 _aArtificial intelligence.
_958441
650 7 _aArtificial intelligence.
_2bicssc
_958441
650 7 _aCOMPUTERS / Artificial Intelligence / General.
_2bisacsh
710 2 _aInstitute of Physics (Great Britain),
_epublisher.
_917702
776 8 _iPrint version:
_z9780750355919
_z9780750355940
830 0 _aIOP (Series).
_pRelease 24.
830 _aIOP series in next generation computing.
_996544
830 _aIOP ebooks.
_p2024 collection.
856 4 _uhttps://iopscience.iop.org/book/mono/978-0-7503-5593-3
942 _cE-Books
999 _c68491
_d68491