Dependability Differentiation in Cloud Services

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Details

As cloud computing is becoming more mature and pervasive, almost all types of services are being deployed in clouds. This has also widened the spectrum of cloud users which encompasses from domestic users to large companies. One of the main concerns of large companies outsourcing their IT functions to clouds is the availability of their functions. On the other hand, availability requirements for domestic users are not very strict. This requires the cloud service providers to guarantee different dependability levels for different users and services. In this book, different types of services are identified and grouped together both according to their deployment nature and their target users. Also a range of techniques for guaranteeing dependability in the cloud environment are identified and classified. In order to quantify dependability provided by different techniques, a cloud system is modeled. Two different levels of dependability differentiation, namely; differentiation depending upon the state of standby replica and differentiation depending upon the spatial separation of active and standby replicas are considered, modeled and studied.

Autorentext

The author has completed B.Sc. (Telecommunications Engineering) and M.Sc. (Telematics) from University of Dar es Salaam (2007) and Norwegian University of Science and Technology-NTNU (2011) respectively. Currently he is pursuing his PhD (Telematics) at NTNU in the field of Real-Time Internet and transient queues.

Weitere Informationen

  • Allgemeine Informationen
    • Sprache Englisch
    • Anzahl Seiten 172
    • Herausgeber LAP LAMBERT Academic Publishing
    • Gewicht 274g
    • Untertitel Analytical and Simulation Study of Differentiated Dependability
    • Autor Ameen Chilwan
    • Titel Dependability Differentiation in Cloud Services
    • Veröffentlichung 04.10.2012
    • ISBN 3659252387
    • Format Kartonierter Einband
    • EAN 9783659252389
    • Jahr 2012
    • Größe H220mm x B150mm x T11mm
    • GTIN 09783659252389

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