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This book constitutes the proceedings of the 17th International Symposium on Applied Reconfigurable Computing, ARC 2021, held as a virtual event, in June 2021. The 14 full papers and 11 short presentations presented in this volume were carefully reviewed and selected from 40 submissions. The papers cover a broad spectrum of applications of reconfigurable computing, from driving assistance, data and graph processing acceleration, computer security to the societal relevant topic of supporting early diagnosis of Covid infectious conditions.
This book constitutes the refereed proceedings of the 14th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2018, held in Poznań, Poland, in September 2018, during the IFIP World Computer Congress. It consists of 38 carefully reviewed papers selected from 102 submissions. The papers are organized in topical sections, namely big data and cloud computing; architectures, structures and algorithms for efficient data processing; artificial intelligence, data mining and knowledge discovery; text mining, natural language processing, ontologies and semantic web; image analysis and multimedia mining.
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Sixth International Conference on Data Management, Analytics and Innovation (ICDMAI 2022), held virtually during January 14–16, 2022. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
This book constitutes the proceedings of the 22nd European Conference on Advances in Databases and Information Systems, ADBIS 2018, held in Budapest, Hungary, in September 2018. The 17 regular papers presented together with two invited papers were carefully selected and reviewed from numerous submissions. The papers are organized in topical sections such as information extraction and integration; data mining and knowledge discovery; indexing, query processing and optimization; data quality and data cleansing; distributed data platforms, including cloud data systems, key-value stores, and big data systems; and streaming data analysis; web, XML and semi-structured databases.
This two-volume set, LNCS 12858 and 12859, constitutes the thoroughly refereed proceedings of the 5th International Joint Conference, APWeb-WAIM 2021, held in Guangzhou, China, in August 2021. The 44 full papers presented together with 24 short papers, and 6 demonstration papers were carefully reviewed and selected from 184 submissions. The papers are organized around the following topics: Graph Mining; Data Mining; Data Management; Topic Model and Language Model Learning; Text Analysis; Text Classification; Machine Learning; Knowledge Graph; Emerging Data Processing Techniques; Information Extraction and Retrieval; Recommender System; Spatial and Spatio-Temporal Databases; and Demo.
This book introduces readers to emerging persistent memory (PM) technologies that promise the performance of dynamic random-access memory (DRAM) with the durability of traditional storage media, such as hard disks and solid-state drives (SSDs). Persistent memories (PMs), such as Intel's Optane DC persistent memories, are commercially available today. Unlike traditional storage devices, PMs can be accessed over a byte-addressable load-store interface with access latency that is comparable to DRAM. Unfortunately, existing hardware and software systems are ill-equipped to fully avail the potential of these byte-addressable memory technologies as they have been designed to access traditional storage media over a block-based interface. Several mechanisms have been explored in the research literature over the past decade to design hardware and software systems that provide high-performance access to PMs. Because PMs are durable, they can retain data across failures, such as power failures and program crashes. Upon a failure, recovery mechanisms may inspect PM data, reconstruct state and resume program execution. Correct recovery of data requires that operations to the PM are properly ordered during normal program execution. Memory persistency models define the order in which memory operations are performed at the PM. Much like memory consistency models, memory persistency models may be relaxed to improve application performance. Several proposals have emerged recently to design memory persistency models for hardware and software systems and for high-level programming languages. These proposals differ in several key aspects; they relax PM ordering constraints, introduce varying programmability burden, and introduce differing granularity of failure atomicity for PM operations. This primer provides a detailed overview of the various classes of the memory persistency models, their implementations in hardware, programming languages and software systems proposed in the recent research literature, and the PM ordering techniques employed by modern processors.
This book contains selected papers from the 7th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016, and the 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, held in New Dehli, India, in September 2016. The joint Workshops were co-located with VLDB 2016. The 9 papers presented were carefully reviewed and selected from 18 submissions. They investigate opportunities in accelerating analytics/data management systems and workloads (including traditional OLTP, data warehousing/OLAP, ETL streaming/real-time, business analytics, and XML/RDF processing) running memory-only environments, using processors (e.g. commodity and specialized multi-core, GPUs and FPGAs, storage systems (e.g. storage-class memories like SSDs and phase-change memory), and hybrid programming models like CUDA, OpenCL, and Open ACC. The papers also explore the interplay between overall system design, core algorithms, query optimization strategies, programming approaches, performance modeling and evaluation, from the perspective of data management applications.
The book is a collection of best selected research papers presented at the Third World Conference on Internet of Things: Applications & Future (ITAF 2023) organized by Global Knowledge Research Foundation in Cairo during February 4–5, 2023. It includes innovative works from researchers, leading innovators, business executives, and industry professionals to examine the latest advances and applications for commercial and industrial end users across sectors within the emerging Internet of things ecosphere. It shares state-of-the-art as well as emerging topics related to Internet of things such as big data research, emerging services and analytics, Internet of things (IoT) fundamentals, electronic computation and analysis, big data for multi-discipline services, security, privacy and trust, IoT technologies, and open and cloud technologies.
This book focuses on online transaction processing indexes designed for scalable, byte-addressable non-volatile memory (NVM) and provides a systematic review and summary of the fundamental principles and techniques as well as an outlook on the future of this research area. In this book, the authors divide the development of NVM indexes into three “eras”— pre-Optane, Optane and post-Optane—based on when the first major scalable NVM device (Optane) became commercially available and when it was announced to be discontinued. The book will analyze the reasons for the slow adoption of NVM and give an outlook for indexing techniques in the post-Optane era. The book assumes only basic undergraduate-level understanding on indexing (e.g., B+-trees, hash tables) and database systems in general. It is otherwise self-contained with the necessary background information, including an introduction to NVM hardware and software/programming issues, a detailed description of different indexes in highly concurrent systems for non-experts and new researchers to get started in this area.