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020 _a9781447150077
_9978-1-4471-5007-7
024 7 _a10.1007/978-1-4471-5007-7
_2doi
035 _ato000483477
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA76.758
072 7 _aUMZ
_2bicssc
072 7 _aUL
_2bicssc
072 7 _aCOM051230
_2bisacsh
082 0 4 _a005.1
_223
100 1 _aLalanda, Philippe.
_eauthor.
_9413733
245 1 0 _aAutonomic Computing
_h[electronic resource] :
_bPrinciples, Design and Implementation /
_cby Philippe Lalanda, Julie A. McCann, Ada Diaconescu.
260 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2013.
300 _aXV, 288 p. 88 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aUndergraduate Topics in Computer Science,
_x1863-7310
505 0 _aSoftware Engineering to Autonomic Computing -- Autonomic Systems -- Sources of Inspiration for Autonomic Computing -- Autonomic Computing Architectures -- The Monitoring Function -- The Adaptation Function -- The Decision Function -- Evaluation Issues -- Autonomic Mediation in Cilia -- Future of Autonomic Computing and Conclusions -- Learning Environment.
520 _aAutonomic computing is changing the way software systems are being developed, introducing the goal of self-managed computing systems with minimal need for human input. This easy-to-follow, classroom-tested textbook/reference provides a practical perspective on autonomic computing. Through the combined use of examples and hands-on projects, the book enables the reader to rapidly gain an understanding of the theories, models, design principles and challenges of this subject while building upon their current knowledge; thus reinforcing the concepts of autonomic computing and self-management. Topics and features: Provides a structured and comprehensive introduction to autonomic computing with a software engineering perspective Supported by a downloadable learning environment and source code that allows students to develop, execute, and test autonomic applications at an associated website Presents the latest information on techniques implementing self-monitoring, self-knowledge, decision-making and self-adaptation Discusses the challenges to evaluating an autonomic system, aiding the reader in designing tests and metrics that can be used to compare autonomic computing systems Reviews the most relevant sources of inspiration for autonomic computing, with pointers towards more extensive specialty literature Ideal for a 10-week lecture programme This concise primer and practical guide will be of great use to students, researchers and practitioners alike, demonstrating how to better architect robust yet flexible software systems capable of meeting the computing demands for today and in the future.
650 0 _aComputer Science.
_9155490
650 0 _aComputer system performance.
_9303225
650 0 _aSoftware engineering.
_9566225
650 0 _aArtificial intelligence.
_9274099
650 1 4 _aComputer Science.
_9155490
650 2 4 _aSoftware Engineering/Programming and Operating Systems.
_9303115
650 2 4 _aArtificial Intelligence (incl. Robotics).
_9274102
650 2 4 _aSystem Performance and Evaluation.
_9303229
700 1 _aMcCann, Julie A.
_eauthor.
_9413734
700 1 _aDiaconescu, Ada.
_eauthor.
_9413735
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aUndergraduate Topics in Computer Science,
_9318115
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-5007-7
912 _aZDB-2-SCS
999 _c356313