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001453808 001__ 1453808
001453808 003__ OCoLC
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001453808 019__ $$a1355567132$$a1356004446$$a1357116391
001453808 020__ $$a9783031180347$$q(electronic bk.)
001453808 020__ $$a3031180348$$q(electronic bk.)
001453808 020__ $$z9783031180330
001453808 020__ $$z303118033X
001453808 0247_ $$a10.1007/978-3-031-18034-7$$2doi
001453808 035__ $$aSP(OCoLC)1357546689
001453808 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dYDX$$dSTF$$dOCLCQ
001453808 049__ $$aISEA
001453808 050_4 $$aQA76.585
001453808 08204 $$a004.6782$$223
001453808 24500 $$aPredictive analytics in cloud, fog, and edge computing :$$bperspectives and practices of Blockchain, IoT, and 5G /$$cHiren Kumar Thakkar, Chinmaya Kumar Dehury, Prasan Kumar Sahoo, Bharadwaj Veeravalli, editors.
001453808 264_1 $$aCham, Switzerland :$$bSpringer,$$c2023.
001453808 300__ $$a1 online resource :$$billustrations (black and white, and color).
001453808 336__ $$atext$$btxt$$2rdacontent
001453808 337__ $$acomputer$$bc$$2rdamedia
001453808 338__ $$aonline resource$$bcr$$2rdacarrier
001453808 5050_ $$aChapter. 1. Collaboration of IoT and Cloud Computing towards Healthcare Security -- Chapter. 2. Robust, Reversible Medical Image Watermarking for Transmission of Medical Images over Cloud in Smart IoT Healthcare -- Chapter. 3.The Role of Blockchain in Cloud Computing -- Chapter. 4. Analysis and Prediction of Plant Growth in a Cloud-based Smart Sensor Controlled Environment -- Chapter. 5. Cloud-based IoT controlled System Model for Plant Disease Monitoring -- Chapter. 6 -- Design and Usage of a Digital E- Pharmacy Application Framework -- Chapter. 7. Serverless Data Pipelines for IoT data analytics: A cloud vendors perspective and solutions -- Chapter. 8. Integration of Predictive Analytics and Cloud Computing for Mental Health Prediction -- Chapter. 9. Impact of 5G technologies on cloud analytics -- Chapter. 10. IoT based ECG-SCG Big Data Analysis Framework for Continuous Cardiac Health Monitoring in Cloud Data Centers -- Chapter. 11. A Workload-aware Data Placement Scheme for Hadoop-enabled MapReduce Cloud Data Center -- Chapter. 12. 5G Enabled Smart City using Cloud Environment.
001453808 506__ $$aAccess limited to authorized users.
001453808 520__ $$aThis book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G. Moreover, the book discusses how the cloud computing is not sufficient and one needs to use fog computing, and edge computing to efficiently process the data generated from IoT, and 5G. Moreover, the book shows how smart city, smart healthcare system, and smart communities are few of the most relevant IoT applications where fog computing plays a significant role. The book discusses the limitation of fog computing and the need for the edge computing to further reduce the network latency to process streaming data from IoT devices. The book also explores power of predictive analytics of Blockchain, IoT, and 5G data in cloud computing with its sister technologies. Since, the amount of resources increases day-by day, artificial intelligence (AI) tools are becoming more popular due to their capability which can be used in solving wide variety of issues, such as minimize the energy consumption of physical servers, optimize the service cost, improve the quality of experience, increase the service availability, efficiently handle the huge data flow, manages the large number of IoT devices, etc.
001453808 588__ $$aDescription based on print version record.
001453808 650_0 $$aCloud computing.
001453808 650_0 $$aEdge computing.
001453808 650_0 $$aBlockchains (Databases)
001453808 650_0 $$aInternet of things.
001453808 650_0 $$a5G mobile communication systems.
001453808 655_0 $$aElectronic books.
001453808 7001_ $$aThakkar, Hiren Kumar,$$eeditor.
001453808 7001_ $$aDehury, Chinmaya Kumar,$$eeditor.
001453808 7001_ $$aSahoo, Prasan Kumar,$$eeditor.
001453808 7001_ $$aVeeravalli, Bharadwaj,$$eeditor.$$1https://isni.org/isni/0000000033022370
001453808 77608 $$iPrint version:$$tPredictive analytics in cloud, fog, and edge computing.$$dCham : Springer, 2022$$z9783031180330$$w(OCoLC)1346945975
001453808 852__ $$bebk
001453808 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-18034-7$$zOnline Access$$91397441.1
001453808 909CO $$ooai:library.usi.edu:1453808$$pGLOBAL_SET
001453808 980__ $$aBIB
001453808 980__ $$aEBOOK
001453808 982__ $$aEbook
001453808 983__ $$aOnline
001453808 994__ $$a92$$bISE