Bharadwaj Veeravalli – författare

Several works on multimedia storage appear in literature today, but very little if any, have been devoted to handling long duration video retrieval, over large scale networks. Distributed retrieval of multimedia documents, especially the long duration documents, is an imperative step in rendering high-quality, high-fidelity, and cost-effective services for network service providers.

Distributed Multimedia Retrieval Strategies for Large Scale Networked Systems presents an up-to-date research status in the domain of distributed video retrieval. This professional book will include several different techniques that are in place for long duration video retrieval. An experimentally tested technology under the JINI platform, demonstrates a practical working system which serves as a feasibility study, as well as the first step in realizing such a technology.

This book presents recent advances on IoT and connected technologies. We are currently in the midst of the Fourth Industrial Revolution, and IoT is having the most significant impact on our society. The recent adoption of a variety of enabling wireless communication technologies like RFID tags, BLE, ZigBee, etc., embedded sensor and actuator nodes, and various protocols like CoAP, MQTT, DNS, etc., has made the Internet of things (IoT) step out of its infancy. Internet of things (IoT) and connecting technologies are already having profound effects on the different parts of society like the government, health care, businesses, and personal lives. 

This book is ideally designed for marketing managers, business professionals, researchers,  academicians, and graduate-level students seeking to learn how IoT and connecting technologies increase the amount of data gained through devices, enhance customer experience, and widen the scope of IoT analytics in enhancing customer marketing outcomes.

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence.

This 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.

This book discusses analysis, design and optimization techniques for streaming multiprocessor systems, while satisfying a given area, performance, and energy budget. The authors describe design flows for both application-specific and general purpose streaming systems.  Coverage also includes the use of machine learning for thermal optimization at run-time, when an application is being executed.  The design flow described in this book extends to thermal and energy optimization with multiple applications running sequentially and concurrently.