Dynamics of Information Systems: Algorithmic Approaches

Author:   Alexey Sorokin ,  Panos M. Pardalos
Publisher:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 2013
Volume:   51
ISBN:  

9781489989406


Pages:   344
Publication Date:   20 August 2015
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Dynamics of Information Systems: Algorithmic Approaches


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Overview

Dynamics of Information Systems: Algorithmic Approaches presents recent developments and results found by participants of the Fourth International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 20-22, 2012. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems.​​​Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: detection of terrorist networks, design of highly efficient businesses, computer networks, quantum entanglement, genome modeling, multi-robotic systems, and industrial and manufacturing safety. The book contains state-of-the-art work on theory and practice relevant to the dynamics of information systems. It covers algorithmic approaches to numerical computations with infinite and infinitesimal numbers; presents important problems arising in service-oriented systems, such as dynamic composition and analysis of modern service-oriented information systems and estimation of customer service times on a rail network from GPS data; addresses the complexity of the problems arising in stochastic and distributed systems; and discusses modulating communication for improving multi-agent learning convergence. Network issues—in particular minimum-risk maximum-clique problems, vulnerability of sensor networks, influence diffusion, community detection, and link prediction in social network analysis, as well as a comparative analysis of algorithms for transmission network expansion planning—are described inlater chapters.

Full Product Details

Author:   Alexey Sorokin ,  Panos M. Pardalos
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 2013
Volume:   51
Dimensions:   Width: 15.50cm , Height: 1.90cm , Length: 23.50cm
Weight:   5.329kg
ISBN:  

9781489989406


ISBN 10:   1489989404
Pages:   344
Publication Date:   20 August 2015
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Numerical computations with infinite and infinitesimal numbers: Theory and applications (Y.D. Sergeyev).- Dynamic Composition and Analysis of modern service-oriented information systems (H. Abdulrab, E. Babkin, and J. Doucy).- Estimating Customer Service Times on a Rail Network from GPS Data (S. Spanton).- A Risk-Averse Game-Theoretic Approach to Distributed Control (K. Pham and M. Pachter).- Static Teams and Stochastic Games (M. Pachter and K. Pham).- A Framework for Coordination in Distributed Stochastic Systems: Output Feedback and Performance Risk Aversion (K. Pham).- Modulating Communication to Improve Multi Agent Learning Convergence (P. Scerri).- Minimum risk maximum clique problem (M. Rysz, P. Krokhmal, and E.L. Pasiliao).- Models for Assessing Vulnerability in Imperfect Sensor Networks (S.B. Sonuç and C. Smith).- Minimum Connected Sensor Cover and Maximum-Lifetime Coverage in Wireless Sensor Networks (L. Wu, W. Wu, K. Xing, P.M. Pardalos, E. Maslov, and D.-Z. Du).- Influence Diffusion, Community Detection and Link Prediction in Social Network Analysis (L. Fan, W. Wu, Z. Lu, W. Xu, and D.-Z. Du).- Comparative analysis of local search strategies for transmission network expansion planning (A. Kammerdiner, A. Fout, and R. Bent).

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