Autonomic Computing and Networking by Radu Calinescu (auth.), Yan Zhang, Laurence Tianruo Yang,

By Radu Calinescu (auth.), Yan Zhang, Laurence Tianruo Yang, Mieso K. Denko (eds.)

Autonomic Computing and Networking serves as a technical advisor and reference fabric for engineers, scientists, practitioners, and researchers via delivering them with cutting-edge examine actions and destiny possibilities and tendencies. The contributions made by means of famous researchers from academia and contain cutting-edge architectures, protocols, applied sciences, and purposes in pervasive computing and instant networking. specifically, the publication covers current and rising communications and computing types, layout architectures, cellular and instant functions, know-how and study matters in autonomic computing platforms and communications.

Important beneficial properties include:

  • A entire reference on autonomic computing and networking,
  • State-of-the-art concepts utilized in the field,
  • Illustrative figures allowing effortless interpreting, and
  • Emerging traits and open learn difficulties and matters.

The fabric is prepared into sections: autonomic computing and autonomic networking. With a complete of eighteen chapters, every one part includes 9 chapters addressing present and rising architectures, protocols, and purposes.

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Extra resources for Autonomic Computing and Networking

Sample text

A survey of autonomic communications. ACM Transactions on Autonomous and Adaptive Systems, 1(2):223–259, December 2006. General-Purpose Autonomic Computing 29 10. D. Gracanin et al. Towards a model-driven architecture for autonomic systems. In Proc. 11th IEEE Intl. Conf. Engineering of Computer-Based Systems, pages 500–505, 2004. 11. B. Haverkort et al. On the use of model checking techniques for dependability evaluation. In Proc. 19th IEEE Symp. Reliable Distributed Systems, pages 228–237, October 2000.

Com opts to serve only textual content during such peak times in lieu of providing its customers zero service. com system administrators (sys-admins) adapt the system using two actions: adjust the server pool size or switch content mode. When the system comes under high load, the sys-admins may increase the server pool size until a cost-determined maximum is reached, at which point the sys-admin switches the servers to serve textual content. If the system load drops, the sys-admin may switch the servers back to multimedia mode to make customers happy, in combination with reducing the pool size to reduce operating cost.

We, among others, use a system’s software architecture as the external model for dynamic adaptation [19, 39]. The architecture of a software system is an abstract representation of the system as a composition of computational elements and their interconnections [44]. 1 Nodes in the graph, termed components, represent the principal computational elements and data stores of the system: clients, servers, databases, user interfaces, etc. Arcs, termed connectors, represent the pathways of interaction between the components.

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