Sharma Chakravarthy – författare

Traditional database management systems, widely used today, are not well-suited for a class of emerging applications, such as computer network management, homeland security, sensor computing, and environmental monitoring. These applications need to continuously process large amounts of data coming in the form of a stream, and meet stringent response time requirements. Support for handling QoS metrics, such as response time, memory usage, and throughput, is central to any system proposed for the above applications. Stream Data Processing: A Quality of Service Perspective (Modeling, Scheduling, Load Shedding, and Complex Event Processing), presents a new paradigm suitable for stream and complex event processing. This book covers a broad range of topics in stream data processing and includes detailed technical discussions of a number of proposed techniques. This volume is intended as a textbook for graduate courses and as a reference book for researchers, advanced-level students in CS, and IT practitioners.

In recent years, a new class of applications has come to the forefront { p- marily due to the advancement in our ability to collect data from multitudes of devices, and process them e ciently. These include homeland security - plications, sensor/pervasive computing applications, various kinds of mo- toring applications, and even traditional applications belonging to nancial, computer network management, and telecommunication domains. These - plications need to process data continuously (and as long as data is available) from one or more sources. The sequence of data items continuously gen- ated by sources is termed a data stream. Because of the possible never-ending nature of a data stream, the amount of data to be processed is likely to be unbounded. In addition, timely detection of interesting changes or patterns or aggregations over incoming data is critical for many of these applications. Furthermore, the data arrival rates may uctuate over a period of time and may be bursty at times. For most of these applications, Quality of Service (or QoS) requirements, such as response time, memory usage, and throughput are extremely important. These application requirements make it infeasible to simply load the incoming data streams into a persistent store and process them e ectively using currently available database management techniques.

This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019. The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions.

This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019.The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions.

This book constitutes the refereed proceedings of the 41st International Conference on Conceptual Modeling, ER 2022, held in Hyderabad, India, in October 2022. The 19 full and 11 short papers were carefully reviewed and selected from 82 submissions. The papers are organzed in the following topical sections: ​foundations of conceptual modeling; ontologies and their applications; applications of conceptual modeling; data modeling and analysis; business process; quality and performance; security, privacy and risk management; goals and requirements.

This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017. The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions.