Performance Evaluation And Benchmarking For The Era Of Artificial Intelligence
Download Performance Evaluation And Benchmarking For The Era Of Artificial Intelligence full books in PDF, epub, and Kindle. Read online free Performance Evaluation And Benchmarking For The Era Of Artificial Intelligence ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Raghunath Nambiar |
| Publisher | : Springer |
| Total Pages | : 168 |
| Release | : 2019-01-29 |
| Genre | : Computers |
| ISBN | : 303011404X |
This book constitutes the thoroughly refereed post-conference proceedings of the 10th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2018, held in conjunction with the 44th International Conference on Very Large Databases (VLDB 2018) in August 2018. The 10 papers presented were carefully reviewed and selected from numerous submissions. The TPC encourages researchers and industry experts to present and debate novel ideas and methodologies in performance evaluation, measurement, and characterization.
| Author | : Raghunath Nambiar |
| Publisher | : Springer Nature |
| Total Pages | : 177 |
| Release | : 2020-07-29 |
| Genre | : Computers |
| ISBN | : 3030550249 |
This book constitutes the refereed post-conference proceedings of the 11th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2019, held in conjunction with the 45th International Conference on Very Large Databases (VLDB 2019) in August 2019. The 11 papers presented were carefully reviewed and focus on topics such as blockchain; big data and analytics; complex event processing; database Optimizations; data Integration; disaster tolerance and recovery; artificial Intelligence; emerging storage technologies (NVMe, 3D XPoint Memory etc.); hybrid workloads; energy and space efficiency; in-memory databases; internet of things; virtualization; enhancements to TPC workloads; lessons learned in practice using TPC workloads; collection and interpretation of performance data in public cloud environments.
| Author | : Raghunath Nambiar |
| Publisher | : Springer Nature |
| Total Pages | : 159 |
| Release | : |
| Genre | : |
| ISBN | : 3031680316 |
| Author | : Raghunath Nambiar |
| Publisher | : Springer Nature |
| Total Pages | : 124 |
| Release | : 2021-08-03 |
| Genre | : Computers |
| ISBN | : 3030849244 |
This book constitutes the refereed post-conference proceedings of the 12th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2020, held in August 2020.The 8 papers presented were carefully reviewed and cover the following topics: testing ACID compliance in the LDBC social network benchmark; experimental performance evaluation of stream processing engines made easy; revisiting issues in benchmarking metric selection; performance evaluation for digital transformation; experimental comparison of relational and NoSQL document systems; a framework for supporting repetition and evaluation in the process of cloud-based DBMS performance benchmarking; benchmarking AI inference; a domain independent benchmark evolution model for the transaction processing performance council.
| Author | : Raghunath Nambiar |
| Publisher | : Springer |
| Total Pages | : 198 |
| Release | : 2018-01-02 |
| Genre | : Computers |
| ISBN | : 3319724010 |
This book constitutes the thoroughly refereed post-conference proceedings of the 8th TPC Technology Conference, on Performance Evaluation and Benchmarking, TPCTC 2017, held in conjunction with the43rd International Conference on Very Large Databases (VLDB 2017) in August/September 2017. The 12 papers presented were carefully reviewed and selected from numeroussubmissions. The TPC remains committed to developing new benchmark standards to keep pace with these rapid changes in technology.
| Author | : Rajdeep Chakraborty |
| Publisher | : John Wiley & Sons |
| Total Pages | : 484 |
| Release | : 2021-12-21 |
| Genre | : Computers |
| ISBN | : 1119762251 |
MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.
| Author | : Punit Gupta |
| Publisher | : CRC Press |
| Total Pages | : 253 |
| Release | : 2024-03-22 |
| Genre | : Computers |
| ISBN | : 1003859038 |
In recent years, soft computing techniques have emerged as a successful tool to understand and analyze the collective behavior of service- oriented computing software. Algorithms and mechanisms of self- organization of complex natural systems have been used to solve problems, particularly in complex systems, which are adaptive, ever- evolving, and distributed in nature across the globe. What fits more perfectly into this scenario other than the rapidly developing era of Fog, IoT, and Edge computing environment? Service- oriented computing can be enhanced with soft computing techniques embedded inside the Cloud, Fog, and IoT systems. Soft Computing Principles and Integration for Real-Time Service-Oriented Computing explores soft computing techniques that have wide application in interdisciplinary areas. These soft computing techniques provide an optimal solution to the optimization problem using single or multiple objectives.The book focuses on basic design principles and analysis of soft computing techniques. It discusses how soft computing techniques can be used to improve quality-of-service in serviceoriented architectures. The book also covers applications and integration of soft computing techniques with a service- oriented computing paradigm. Highlights of the book include: A general introduction to soft computing An extensive literature study of soft computing techniques and emerging trends Soft computing techniques based on the principles of artificial intelligence, fuzzy logic, and neural networks The implementation of SOC with a focus on service composition and orchestration, quality of service (QoS) considerations, security and privacy concerns, governance challenges, and the integration of legacy systems The applications of soft computing in adaptive service composition, intelligent service recommendation, fault detection and diagnosis, SLA management, and security Such principles underlying SOC as loose coupling, reusability, interoperability, and abstraction An IoT based framework for real time data collection and analysis using soft computing
| Author | : M. Villaret |
| Publisher | : IOS Press |
| Total Pages | : 486 |
| Release | : 2021-10-14 |
| Genre | : Computers |
| ISBN | : 1643682113 |
Artificial intelligence has become an indispensible part of our lives in recent years, affecting all aspects from business and leisure to transport and health care. This book presents the proceedings of the 23rd edition of the International Conference of the Catalan Association for Artificial Intelligence (CCIA), an annual event that serves as a meeting point for researchers in Artificial Intelligence in the area of the Catalan speaking territories and from around the world. The 2021 edition was held online as a virtual conference from 20 - 22 October 2021 due to the COVID-19 pandemic. The book contains 42 long papers and 9 short papers, carefully reviewed and selected. The papers cover all aspects of artificial intelligence and are divided under six section headings: combinatorial problem solving and logics for artificial intelligence; sentiment analysis and tekst analysis; data science and decision support systems; machine learning; computer vision; and explainability and argumentation. Abstracts of the 2 invited talks delivered at the conference by Prof. Patty Kostkova and Prof. João Marques-Silva are also included. Offering a state of the art overview of the subject from a regional perspective, the book will be of interest to all those working in the field of artificial intelligence.
| Author | : Abdalmuttaleb M.A Musleh Al-Sartawi |
| Publisher | : Springer Nature |
| Total Pages | : 536 |
| Release | : 2021-05-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3030772462 |
This book brings together intelligence systems and the Internet of Things, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI and IoT to develop future strategies and to achieve sustainability goals. EAMMIS 2021 was organized by the Bridges Foundation in cooperation with the Istanbul Medeniyet University, Istanbul, Turkey, on March 19–20, 2021. EAMMIS 2021 theme was Artificial Intelligence Systems and the Internet of Things in the digital era. The papers presented at the conference provide a holistic view of AI education, MIS, cybersecurity, blockchain, Internet of Ideas (IoI), and knowledge management.
| Author | : Management Association, Information Resources |
| Publisher | : IGI Global |
| Total Pages | : 2253 |
| Release | : 2020-11-27 |
| Genre | : Computers |
| ISBN | : 1799877485 |
As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.
