The Experts below are selected from a list of 166134 Experts worldwide ranked by ideXlab platform
Michel Raynal - One of the best experts on this subject based on the ideXlab platform.
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A Look at Basics of Distributed Computing *
2016Co-Authors: Michel RaynalAbstract:This paper presents concepts and basics of Distributed Computing which are important (at least from the author's point of view), and should be known and mastered by Master students and engineers. Those include: (a) a characterization of Distributed Computing (which is too much often confused with parallel Computing); (b) the notion of a synchronous system and its associated notions of a local algorithm and message adversaries; (c) the notion of an asynchronous shared memory system and its associated notions of universality and progress conditions; and (d) the notion of an asynchronous message-passing system with its associated broadcast and agreement abstractions, its impossibility results, and approaches to circumvent them. Hence, the paper can be seen as a guided tour to key elements that constitute basics of Distributed Computing.
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DISC - The 2010 Edsger W. Dijkstra prize in Distributed Computing
Lecture Notes in Computer Science, 2010Co-Authors: Marcos K. Aguilera, Michel RaynalAbstract:The ACM-EATCS Edsger W. Dijkstra Prize in Distributed Computing was created to acknowledge outstanding papers on the principles of Distributed Computing whose significance and impact on the theory or practice of Distributed Computing have been evident for at least a decade.
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FTDCS - Challenges of Future Distributed Computing Systems
2003Co-Authors: Stephen S. Yau, Carl K. Chang, Randy Y. C. Chow, Luca Limoncini, Michel RaynalAbstract:Distributed Computing systems have progressed quickly during the last several years, especially the large expansion of applications and the major impact of internet and wireless technologies on the industry. The research and development in this and other related areas have also grown rapidly worldwide. This panel will address the future direction of Distributed Computing systems, highlighting the major research issues and the challenges of dealing with them in order to meet the increasing demands of better performances and services for various Distributed applications.
Christian Becker - One of the best experts on this subject based on the ideXlab platform.
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tasklets overcoming heterogeneity in Distributed Computing systems
International Conference on Distributed Computing Systems Workshops, 2016Co-Authors: Dominik Schafer, Janick Edinger, Sebastian Vansyckel, Justin Mazzola Paluska, Christian BeckerAbstract:Distributed Computing is a good alternative to expensive supercomputers. There are plenty of frameworks that enable programmers to harvest remote Computing power. However, until today, much computation power in the edges of the Internet remains unused. While idle devices could contribute to a Distributed environment as generic computation resources, computation-intense applications could use this pool of resources to enhance their execution quality. In this paper, we identify heterogeneity as a major burden for Distributed and edge Computing. Heterogeneity is present in multiple forms. We draw our vision of a comprehensive Distributed Computing system and show where existing frameworks fall short in dealing with the heterogeneity of Distributed Computing. Afterwards, we present the Tasklet system, our approach for a Distributed Computing framework. Tasklets are fine-grained computation units that can be issued for remote and local execution. We tackle the different dimensions of heterogeneity and show how to make use of available computation power in edge resources. In our prototype, we use middleware and virtualization technologies as well as a host language concept.
Costin Badica - One of the best experts on this subject based on the ideXlab platform.
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Intelligent Distributed Computing XIII
2019Co-Authors: Igor Kotenko, Costin Badica, Vasily Desnistky, Didier El Baz, Mirjana IvanovicAbstract:This book gathers research contributions on recent advances in intelligent and Distributed Computing. A major focus is placed on new techniques and applications for several highly demanded research directions: Internet of Things, Cloud Computing and Big Data, Data Mining and Machine Learning, Multi-agent and Service-Based Distributed Systems, Distributed Algorithms and Optimization, Modeling Operational Processes, Social Network Analysis and Inappropriate Content Counteraction, Cyber-Physical Security and Safety, Intelligent Distributed Decision Support Systems, Intelligent Human-Machine Interfaces, Visual Analytics and others. The book represents the peer-reviewed proceedings of the 13th International Symposium on Intelligent Distributed Computing (IDC 2019), which was held in St. Petersburg, Russia, from October 7 to 9, 2019.
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Intelligent Distributed Computing VII - Intelligent Distributed Computing VII
Studies in Computational Intelligence, 2014Co-Authors: Filip Zavoral, Jason J. Jung, Costin BadicaAbstract:This book represents the combined peer-reviewed proceedings of the Seventh International Symposium on Intelligent Distributed Computing - IDC-2013, of the Second Workshop on Agents for Clouds - A4C-2013, of the Fifth International Workshop on Multi-Agent Systems Technology and Semantics - MASTS-2013, and of the International Workshop on Intelligent Robots - iR-2013. All the events were held in Prague, Czech Republic during September 4-6, 2013. The 41 contributions published in this book address many topics related to theory and applications of intelligent Distributed Computing and multi-agent systems, including: agent-based data processing, ambient intelligence, bio-informatics, collaborative systems, cryptography and security, Distributed algorithms, grid and cloud Computing, information extraction, intelligent robotics, knowledge management, linked data, mobile agents, ontologies, pervasive Computing, self-organizing systems, peer-to-peer Computing, social networks and trust, and swarm intelligence.
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Intelligent Distributed Computing V - Intelligent Distributed Computing V
Studies in Computational Intelligence, 2012Co-Authors: F.m. Brazier, Kees Nieuwenhuis, Gregor Pavlin, Martijn Warnier, Costin BadicaAbstract:This book represents the combined peer-reviewed proceedings of the Fifth International Symposium on Intelligent Distributed Computing -- IDC 2011 and of the Third International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS 2011. Both events were held in Delft, The Netherlands during October 5-7, 2011. The 33 contributions published in this book address many topics related to theory and applications of intelligent Distributed Computing and multi-agent systems, including: adaptive and autonomous Distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud Computing, coalition formation, decision support systems, Distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and Distributed computational intelligence, parallel evolutionary Computing, trust metrics and security, scheduling in Distributed heterogenous Computing environments, semantic Web service composition, social simulation, and software agents for WSNs
Dominik Schafer - One of the best experts on this subject based on the ideXlab platform.
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tasklets overcoming heterogeneity in Distributed Computing systems
International Conference on Distributed Computing Systems Workshops, 2016Co-Authors: Dominik Schafer, Janick Edinger, Sebastian Vansyckel, Justin Mazzola Paluska, Christian BeckerAbstract:Distributed Computing is a good alternative to expensive supercomputers. There are plenty of frameworks that enable programmers to harvest remote Computing power. However, until today, much computation power in the edges of the Internet remains unused. While idle devices could contribute to a Distributed environment as generic computation resources, computation-intense applications could use this pool of resources to enhance their execution quality. In this paper, we identify heterogeneity as a major burden for Distributed and edge Computing. Heterogeneity is present in multiple forms. We draw our vision of a comprehensive Distributed Computing system and show where existing frameworks fall short in dealing with the heterogeneity of Distributed Computing. Afterwards, we present the Tasklet system, our approach for a Distributed Computing framework. Tasklets are fine-grained computation units that can be issued for remote and local execution. We tackle the different dimensions of heterogeneity and show how to make use of available computation power in edge resources. In our prototype, we use middleware and virtualization technologies as well as a host language concept.
Alina Sîrbu - One of the best experts on this subject based on the ideXlab platform.
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ICDCS - Cognified Distributed Computing
2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), 2018Co-Authors: Ozalp Babaoglu, Alina SîrbuAbstract:Cognification – the act of transforming ordinary objects or processes into their intelligent counterparts through Data Science and Artificial Intelligence – is a disruptive technology that has been revolutionizing disparate fields ranging from corporate law to medical diagnosis. Easy access to massive data sets, data analytics tools and High-Performance Computing (HPC) have been fueling this revolution. In many ways, cognification is similar to the electrification revolution that took place more than a century ago when electricity became a ubiquitous commodity that could be accessed with ease from anywhere in order to transform mechanical processes into their electrical counterparts. In this paper, we consider two particular forms of Distributed Computing – Data Centers and HPC systems – and argue that they are ripe for cognification of their entire ecosystem, ranging from top-level applications down to low-level resource and power management services. We present our vision for what "Cognified Distributed Computing" might look like and outline some of the challenges that need to be addressed and new technologies that need to be developed in order to make it a reality. In particular, we examine the role cognification can play in tackling power consumption, resiliency and management problems in these systems. We describe intelligent software-based solutions to these problems powered by on-line predictive models built from streamed real-time data. While we cast the problem and our solutions in the context of large Data Centers and HPC systems, we believe our approach to be applicable to Distributed Computing in general. We believe that the traditional systems research agenda has much to gain by crossing discipline boundaries to include ideas and techniques from Data Science, Machine Learning and Artificial Intelligence.
