Performance Evaluation and Benchmarking for the Era of Cloud(s)

Performance Evaluation and Benchmarking for the Era of Cloud(s)
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.

Performance Evaluation and Benchmarking

Performance Evaluation and Benchmarking
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.

Performance Evaluation and Benchmarking for the Analytics Era

Performance Evaluation and Benchmarking for the Analytics Era
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.

Machine Learning Techniques and Analytics for Cloud Security

Machine Learning Techniques and Analytics for Cloud Security
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.

Performance Evaluation and Benchmarking

Performance Evaluation and Benchmarking
Author: Raghunath Nambiar
Publisher: Springer
Total Pages: 244
Release: 2011-01-19
Genre: Computers
ISBN: 3642182062

This book constitutes the proceedings of the Second Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2010, held in conjunction with the 36th International Conference on Very Large Data Bases, VLDB 2010, in Singapore, September 13-17, 2010. The 14 full papers and two keynote papers were carefully selected and reviewed from numerous submissions. This book considers issues such as appliance; business intelligence; cloud computing; complex event processing; database optimizations; data compression; energy and space efficiency, green computing; hardware innovations; high speed data generation; hybrid workloads; very large memory systems; and virtualization.

Systems Performance

Systems Performance
Author: Brendan Gregg
Publisher: Pearson Education
Total Pages: 777
Release: 2014
Genre: Business & Economics
ISBN: 0133390098

The Complete Guide to Optimizing Systems Performance Written by the winner of the 2013 LISA Award for Outstanding Achievement in System Administration Large-scale enterprise, cloud, and virtualized computing systems have introduced serious performance challenges. Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most complex environments. Systems Performance: Enterprise and the Cloud focuses on Linux(R) and Unix(R) performance, while illuminating performance issues that are relevant to all operating systems. You'll gain deep insight into how systems work and perform, and learn methodologies for analyzing and improving system and application performance. Gregg presents examples from bare-metal systems and virtualized cloud tenants running Linux-based Ubuntu(R), Fedora(R), CentOS, and the illumos-based Joyent(R) SmartOS(TM) and OmniTI OmniOS(R). He systematically covers modern systems performance, including the "traditional" analysis of CPUs, memory, disks, and networks, and new areas including cloud computing and dynamic tracing. This book also helps you identify and fix the "unknown unknowns" of complex performance: bottlenecks that emerge from elements and interactions you were not aware of. The text concludes with a detailed case study, showing how a real cloud customer issue was analyzed from start to finish. Coverage includes - Modern performance analysis and tuning: terminology, concepts, models, methods, and techniques - Dynamic tracing techniques and tools, including examples of DTrace, SystemTap, and perf - Kernel internals: uncovering what the OS is doing - Using system observability tools, interfaces, and frameworks - Understanding and monitoring application performance - Optimizing CPUs: processors, cores, hardware threads, caches, interconnects, and kernel scheduling - Memory optimization: virtual memory, paging, swapping, memory architectures, busses, address spaces, and allocators - File system I/O, including caching - Storage devices/controllers, disk I/O workloads, RAID, and kernel I/O - Network-related performance issues: protocols, sockets, interfaces, and physical connections - Performance implications of OS and hardware-based virtualization, and new issues encountered with cloud computing - Benchmarking: getting accurate results and avoiding common mistakes This guide is indispensable for anyone who operates enterprise or cloud environments: system, network, database, and web admins; developers; and other professionals. For students and others new to optimization, it also provides exercises reflecting Gregg's extensive instructional experience.

Fog and Edge Computing

Fog and Edge Computing
Author: Rajkumar Buyya
Publisher: John Wiley & Sons
Total Pages: 512
Release: 2019-01-30
Genre: Technology & Engineering
ISBN: 1119524989

A comprehensive guide to Fog and Edge applications, architectures, and technologies Recent years have seen the explosive growth of the Internet of Things (IoT): the internet-connected network of devices that includes everything from personal electronics and home appliances to automobiles and industrial machinery. Responding to the ever-increasing bandwidth demands of the IoT, Fog and Edge computing concepts have developed to collect, analyze, and process data more efficiently than traditional cloud architecture. Fog and Edge Computing: Principles and Paradigms provides a comprehensive overview of the state-of-the-art applications and architectures driving this dynamic field of computing while highlighting potential research directions and emerging technologies. Exploring topics such as developing scalable architectures, moving from closed systems to open systems, and ethical issues rising from data sensing, this timely book addresses both the challenges and opportunities that Fog and Edge computing presents. Contributions from leading IoT experts discuss federating Edge resources, middleware design issues, data management and predictive analysis, smart transportation and surveillance applications, and more. A coordinated and integrated presentation of topics helps readers gain thorough knowledge of the foundations, applications, and issues that are central to Fog and Edge computing. This valuable resource: Provides insights on transitioning from current Cloud-centric and 4G/5G wireless environments to Fog Computing Examines methods to optimize virtualized, pooled, and shared resources Identifies potential technical challenges and offers suggestions for possible solutions Discusses major components of Fog and Edge computing architectures such as middleware, interaction protocols, and autonomic management Includes access to a website portal for advanced online resources Fog and Edge Computing: Principles and Paradigms is an essential source of up-to-date information for systems architects, developers, researchers, and advanced undergraduate and graduate students in fields of computer science and engineering.

Selected Topics in Performance Evaluation and Benchmarking

Selected Topics in Performance Evaluation and Benchmarking
Author: Raghunath Nambiar
Publisher: Springer
Total Pages: 222
Release: 2013-02-05
Genre: Computers
ISBN: 3642367275

This book constitutes the refereed proceedings of the 4th TPC Technology Conference, TPCTC 2012, held in Istanbul, Turkey, in August 2012. It contains 10 selected peer-reviewed papers, 2 invited talks, a report from the TPC Public Relations Committee, and a report from the workshop on Big Data Benchmarking, WBDB 2012. The papers present novel ideas and methodologies in performance evaluation, measurement, and characterization.

Cloud Computing and Big Data

Cloud Computing and Big Data
Author: Marcelo Naiouf
Publisher: Springer
Total Pages: 161
Release: 2019-07-26
Genre: Computers
ISBN: 3030277135

This book constitutes the revised selected papers of the 7th International Conference on Cloud Computing and Big Data, JCC&BD 2019, held in La Plata, Buenos Aires, Argentina, in June 2019. The 12 full papers presented were carefully reviewed and selected from a total of 31 submissions. They are dealing with such topics as cloud computing and HPC; Big Data and data intelligence; mobile computing.

Benchmarking, Measuring, and Optimizing

Benchmarking, Measuring, and Optimizing
Author: Chen Zheng
Publisher: Springer Nature
Total Pages: 268
Release: 2019-10-15
Genre: Computers
ISBN: 3030328139

This book constitutes the refereed proceedings of the First International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018, held in Seattle, WA, USA, in December 2018. The 20 full papers presented were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections named: AI Benchmarking; Cloud; Big Data; Modelling and Prediction; and Algorithm and Implementations.