This book studies algorithmic issues associated with cooperative execution of multiple independent tasks by distributed computing agents including partitionable networks. It provides the most significant algorithmic solution developed and available today for do-all computing for distributed systems (including partitionable networks), and is the first monograph that deals with do-all computing for distributed systems. Recent results have shed light on the understanding of how adversity affects efficiency, by presenting failure-sensitive upper and lower bounds for Do-All in several models for computation. The ability to cooperatively perform a collection of tasks is key to solving a broad array of computation problems ranging from distributed search to distributed simulation and multi-agent collaboration which is introduced within this book.
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Antonio Fernández Anta is a Research Professor at IMDEA Networks. Previously he was on the faculty of the Universidad Rey Juan Carlos (URJC) and the Universidad Politecnica de Madrid (UPM), where he received an award for his research productivity. He was a postdoc at MIT from 1995 to 1997, and spent sabbatical years at Bell Labs Murray Hill and MIT Media Lab. He was awarded the Premio Nacional de Informatica "Aritmel" in 2019 and has been a Mercator Fellow of the SFB MAKI in Germany since 2018. He has more than 25 years of research experience, and more than 200 scientific publications. He was the Chair of the Steering Committee of DISC and has served in the TPC of numerous conferences and workshops. He received his MSc and PhD from the University of SW Louisiana in 1992 and 1994, respectively. He completed his undergraduate studies at the UPM, having received awards at the university and national level for his academic performance. He is a Senior Member of ACM and IEEE.
The ability to cooperatively perform a collection of tasks in a distributed system is key to solving a broad array of computation problems ranging from distributed search, to distributed simulation, and multi-agent collaboration. Practical solutions to such cooperation problems must effectively marshal the available computing resources in performing large sets of tasks. This is challenging due to the failures and asynchrony of the involved processors, and due to the delays and connectivity failures in the underlying network.
Do-All Computing in Distributed Systems: Cooperation in the Presence of Adversity is the first book that presents an in depth study of cooperation problems, abstracted in terms of the Do-All problem, where a collection of processors cooperatively perform a collection of independent tasks in the presence of adversity.
This book presents several significant advances in algorithms designed to solve the Do-All problem in distributed message-passing settings under various models of adversity, including processor crashes, asynchrony, message delays, network partitions, and malicious processor behaviors. Upper and lower bounds are presented, demonstrating the extent to which efficiency can be combined with fault-tolerance. This book contains the recent advances in the principles of efficient and fault-tolerant cooperative computing, narrowing the gap between abstract models of dependable network computing and realistic distributed systems.
Do-All Computing in Distributed Systems: Cooperation in the Presence of Adversity is structured to meet the needs of a professional audience composed of researchers and practitioners in industry. This volume is also suitable as a reference or secondary text for advanced-level students in computer science and engineering.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Do-All Computing for Distributed Systems: Cooperation in the Presence of Adversity studies algorithmic issues associated with cooperative execution of multiple independent tasks by distributed computing agents including partitionable networks.Recent results have shed light on the understanding of how adversity affects efficiency, by presenting failure-sensitive upper and lower bounds for Do-All in several models for computation. The ability to cooperatively perform a collection of tasks is key to solving a broad array of computation problems ranging from distributed search to distributed simulation and multi-agent collaboration which is introduced within this book.Do-All Computing for Distributed Systems: Cooperation in the Presence of Adversityis structured to meet the needs of a professional audience composed of researchers and practitioners in industry. This volume is also suitable for graduate-level students in computer science. Artikel-Nr. 9781441940438
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