With the intriguing development of technologies in several industries along with the advent of accrescent and ubiquitous computational resources, it creates an ample number of opportunities to develop innovative intelligence technologies in order to solve the wide range of uncertainties, imprecision, and vagueness issues in various real-life problems. Hybridizing modern computational intelligence with traditional computing methods has attracted researchers and academicians to focus on developing innovative AI techniques using data science. International Conference on Data Science and Artificial Intelligence (ICDSAI) 2022, organized on April 23-24, 2022 by the Indian Institute of Technology, Patna at NITIE Mumbai (India) in collaboration with the International Association of Academicians (IAASSE) USA collected scientific and technical contributions with respect to models, tools, technologies, and applications in the field of modern Artificial Intelligence and Data Science, covering the entire range of concepts from theory to practice, including case studies, works-in-progress, and conceptual explorations.

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.

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.

N etwork-based computing domain unifies all best research efforts presented from single computer systems to networked systems to render overwhelming computational power for several modern day applications. Although this power is expected to grow with respect to time due to tech nological advancements, application requirements impose a continuous thrust on network utilization and on the resources to deliver supreme quality of service. Strictly speaking, network-based computing dornain has no confined scope and each element offers considerable challenges. Any modern day networked application strongly thrives on efficient data storage and management system, which is essentially a Database System. There have been nurnber of books-to-date in this domain that discuss fundamental principles of designing a database systern. Research in this dornain is now far matured and rnany researchers are venturing in this dornain continuously due to a wide variety of challenges posed. In this book, our dornain of interest is in exposing the underlying key challenges in designing algorithms to handle unpredictable requests that arrive at a Distributed Database System(DDBS) and evaluating their performance. These requests are otherwise called as on-line requests arriving at a system to process. Transactions in an on-line Banking service, Airline Reservation systern, Video-on-Demand systern, etc, are few examples of on-line requests."

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. 6th International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2021, was a platform to discuss and feature research on topics such as augmented reality, sensor networks, and wearable technology. 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.

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.

N etwork-based computing domain unifies all best research efforts presented from single computer systems to networked systems to render overwhelming computational power for several modern day applications. Although this power is expected to grow with respect to time due to tech nological advancements, application requirements impose a continuous thrust on network utilization and on the resources to deliver supreme quality of service. Strictly speaking, network-based computing dornain has no confined scope and each element offers considerable challenges. Any modern day networked application strongly thrives on efficient data storage and management system, which is essentially a Database System. There have been nurnber of books-to-date in this domain that discuss fundamental principles of designing a database systern. Research in this dornain is now far matured and rnany researchers are venturing in this dornain continuously due to a wide variety of challenges posed. In this book, our dornain of interest is in exposing the underlying key challenges in designing algorithms to handle unpredictable requests that arrive at a Distributed Database System(DDBS) and evaluating their performance. These requests are otherwise called as on-line requests arriving at a system to process. Transactions in an on-line Banking service, Airline Reservation systern, Video-on-Demand systern, etc, are few examples of on-line requests."

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. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.

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. 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.