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EN
We present in this paper a novel distributed solution to a security-aware job scheduling problem in cloud computing infrastructures. We assume that the assignment of the available resources is governed exclusively by the specialized brokers assigned to individual users submitting their jobs to the system. The goal of this scheme is allocating a limited quantity of resources to a specific number of jobs minimizing their execution failure probability and total completion time. Our approach is based on the Pareto dominance relationship and implemented at an individual user level. To select the best scheduling strategies from the resulting Pareto frontiers and construct a global scheduling solution, we developed a decision-making mechanism based on the game-theoretic model of Spatial Prisoner's Dilemma, realized by selfish agents operating in the two-dimensional cellular automata space. Their behavior is conditioned by the objectives of the various entities involved in the scheduling process and driven towards a Nash equilibrium solution by the employed social welfare criteria. The performance of the scheduler applied is verified by a number of numerical experiments. The related results show the effectiveness and scalability of the scheme in the presence of a large number of jobs and resources involved in the scheduling process.
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An object-based model for convective cold pool dynamics

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EN
A simple model of the organization of atmospheric moist convection by cold outflows is presented. The model consists of two layers: a lower layer where instability gradually builds up, and an upper layer where instability is rapidly released. Its formulation is inspired by Abelian sandpile models: instability and convection are both represented in terms of particles that are coupled to a lattice grid. An excess of particles in the lower layer triggers a particle release into the upper (cloud) layer. Particles in the upper layer also induce particle movement in the lower layer: this reverse coupling represents the effect of precipitation and the associated cold outflows. The model shows two behavioral regimes. Activity is scattered when the reverse coupling is weak, but when it is strong, convection forms cellular patterns. Though this model does not contain a detailed representation of physical processes in convection, it captures some key dynamical features of precipitating convection seen in satellite observations and LES studies. These include the formation of open cells, temporal oscillations in convective intensity, hysteresis, and the effect of precipitation on the scale of convection. We argue that an object-based representation of convection may be able to capture properties of convective organization that are missing in traditional parameterizations.
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