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By João Ferreira, João Leitão, Luis Rodrigues (auth.), Athanasius V. Vasilakos, Roberto Beraldi, Roy Friedman, Marco Mamei (eds.)

This e-book constitutes the completely refereed post-conference court cases of the thirs foreign ICST convention on Autonomic Computing and communique structures, Autonomics 2009, held in Cyprus Univesity of know-how, Limassol, Cyprus, in September 2009.

The eleven revised complete papers out of 26 submitted and hosted five invited talks, overlaying numerous points of autonomic computing together with software, middelware, networking protocols and evaluation.

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Additional info for Autonomic Computing and Communications Systems: Third International ICST Conference, Autonomics 2009, Limassol, Cyprus, September 9-11, 2009, Revised Selected Papers

Example text

Notice that we only need the last values of the transformed system, instead of all the ones computed in the first part. Discussion. We discuss the features of each algorithm to define the best parallelization schemas. In this paper we focus on context events including the state of the used computing resources and their associated performance. g. sensor data) influencing the version selection policy (demanded to future work). The performance features of the described algorithms can be characterized as following: – Number of steps: The first algorithm performs q−1 = log2 (N −1)−1 steps during the transformation part and q = log2 (N − 1) in the resolution one.

During the execution the context logic of a ParMod, or the control logic of other modules, can notify one or more events. g the parallelism degree of a parallel computation as described in [19]). The control logic of an ASSISTANT ParMod can be described as a graph (see Fig. 6(b)(right)): nodes are operations of the ParMod and arcs are events (or their combinations with logical expressions on the actual ParMod state). Semantically a ParMod control logic is a sequential automaton: this is done to avoid nondeterministic behaviors.

For this example, there are 24 different schedules, but only two of them, namely {a, b, a, b} and {b, a, b, a} allow all the receiver nodes reconstruct the event. 125. This result shows the weakness of naive random dissemination. R ANDOM D ISSEMINATION WITH N ETWORK C ODING . The second random solution leverages linear network coding, where we can show that we can achieve forwarding probability pF ≈ 1 while maintaining the cost of forwarding practically the same as with the informed dissemination.

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