NDLI: Self-organizing autonomic computing systems

Content Provider	IEEE Xplore Digital Library
Author	Solomon, B. Ionescu, D. Litoiu, M. Iszlai, G.
Copyright Year	2011
Description	Author affiliation: IBM Center for Advanced Studies, Toronto, Ontario, Canada (Iszlai, G.) \|\| York University, Toronto, Ontario, Canada (Litoiu, M.) \|\| NCCT Lab, University of Ottawa, Ontario, Canada (Solomon, B.; Ionescu, D.)
Abstract	Recently a great deal of research has been under-taken in the area of automating the enterprise IT Infrastructure. For enterprises with a large number of computers the IT Infrastructure operation represents a considerable amount of the enterprise budget. Autonomic Computing Systems are systems which were created for minimizing this budget component. They were meant to correct and optimize the IT infrastructure's own self-functioning by executing corrective operations without any need for human interventions. In most cases, where autonomic computing systems have been developed, this was achieved by the addition of external global controllers monitoring the sub-systems of the enterprise IT Infrastructure, determining where changes should be made and applying appropriate commands to implement these changes. Self-Organizing systems on the other hand are systems which reach a global desired state without the use of a central authority which in certain case is the human operator. This paper introduces a general architecture and appropriate algorithms for a self-organizing system which automates a cluster of servers and which maintains an equal desired response time across all the servers. The self-organizing control applies either in the case of homogeneous servers or heterogeneous ones. Furthermore, a simple controller can be built to add or remove servers from the cluster where the controller is itself a peer in the self-organizing system. Simulation data for an autonomic computing system made out of a few cluster servers which are controlled by a self-organizing controller is presented.
Starting Page	99
Ending Page	104
File Size	348405
Page Count	6
File Format	PDF
ISBN	9781457718427
e-ISBN	9781457718410
DOI	10.1109/LINDI.2011.6031128
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-25
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptation models Computational modeling Computer architecture Data models Servers Time factors Kalman filters
Content Type	Text
Resource Type	Article

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