By Radu Calinescu (auth.), Yan Zhang, Laurence Tianruo Yang, Mieso K. Denko (eds.)
Autonomic Computing and Networking serves as a technical consultant and reference fabric for engineers, scientists, practitioners, and researchers through supplying them with state of the art learn actions and destiny possibilities and tendencies. The contributions made by way of favorite researchers from academia and comprise cutting-edge architectures, protocols, applied sciences, and functions in pervasive computing and instant networking. specifically, the booklet covers latest and rising communications and computing types, layout architectures, cellular and instant purposes, know-how and examine matters in autonomic computing structures and communications.
Important good points include:
- A finished reference on autonomic computing and networking,
- State-of-the-art ideas utilized in the field,
- Illustrative figures permitting effortless analyzing, and
- Emerging developments and open study difficulties and matters.
The fabric is equipped into sections: autonomic computing and autonomic networking. With a complete of eighteen chapters, each one part includes 9 chapters addressing latest and rising architectures, protocols, and purposes.
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Additional info for Autonomic Computing and Networking
Reliable Distributed Systems, pages 228–237, October 2000. 12. M. Hinchey et al. Modeling for NASA autonomous nano-technology swarm missions and model-driven autonomic computing. In Proc. 21st Intl. Conf. Advanced Networking and Applications, pages 250–257, 2007. 13. G. Hinchey and R. Sterritt. Self-managing software. Computer, 39(2):107–109, Feb. 2006. 14. A. Hinton et al. PRISM: A tool for automatic verification of probabilistic systems. In H. Hermanns and J. Palsberg, editors, Proc. 12th Intl.
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. 12. M. Hinchey et al. Modeling for NASA autonomous nano-technology swarm missions and model-driven autonomic computing.
The author is grateful to Marta Kwiatkowska, David Parker, Gethin Norman and Mark Kattenbelt for insightful discussions during the integration of the PRISM probabilistic model checker with the autonomic policy engine. References 1. J. Arwe et al. 0, March 2007. org/ Submission/2007/SUBM-sml-20070321. 2. C. M. Bishop. Pattern Recognition and Machine Learning. Springer, 2007. 3. E. Bruneton et al. The Fractal component model and its support in Java. Softw. Pract. , 36:1257–1284, 2006. 4. R. Calinescu.