NDLI: Connecting several stability criteria for iISS networks and their application to a network computing model

Content Provider	IEEE Xplore Digital Library
Author	Ito, H.
Copyright Year	2011
Description	Author affiliation: Department of Systems Design and Informatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka 820-8502, Japan (Ito, H.)
Abstract	Employing the framework of integral input-to-state stability (iISS), this paper studies the problem of verifying stability of dynamical networks. The iISS we impose on the subsystems encompasses a wider variety of nonlinearities than input-to-state stability (ISS) which has been studied extensively in the literature. To go beyond the ISS results, this paper investigates a simultaneous small-gain criterion, a topological separation criterion and a spectral radius formula in view of necessity and suffiency for the stability of the iISS network, and they are related to each other. This work aims at unifying conceivable stability criteria into a single methodology in the iISS formulation which includes ISS as a special case. For illustration, this paper examines the dynamics of network computing for resource utilization. Based on a fluid flow model, the proposed iISS methodology provides us with qualitative and quantitative information on the computing speed, the communication overhead, the number of nodes and the interconnection structure for achieving successful workload distribution across multiple computers.
Starting Page	6072
Ending Page	6078
File Size	254050
Page Count	7
File Format	PDF
ISBN	9781612848006
ISSN	07431546
e-ISBN	9781612848013
e-ISBN	9781612847993
DOI	10.1109/CDC.2011.6160261
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stability criteria Nickel Vectors Computers Computational modeling Lyapunov methods
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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