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The adaptive resource management framework implemented in the European ACTORS project is presented. A resource manager has been developed that collaborates with a new Linux scheduler providing support for hard constant bandwidth server reservations, in order to adapt applications to changes in resource availability and to adapt the resource allocation to changes in application requirements. The fo
Shadowing from vehicles can degrade the performance of vehicle-to-vehicle (V2V) communication systems significantly. It is thus important to characterize and model the influence of common shadowing objects like cars properly. For multilink systems it is essential to model the joint effects on the different links. However, the multilink shadowing effects in V2V channels are not yet well understood.
This paper presents an architecture of an auto-correlator for Orthogonal Frequency Division Multiplexing systems. The received signal is quantized to only the sign-bit, which dramatically simplifies the frequency offset estimation. Hardware cost is reduced under the assumption that synchronization during acquisition does not have to be very accurate, but sufficient for coarse estimation. The archi
Self-adaptation enables software to execute successfully in dynamic, unpredictable, and uncertain environments. Control theory provides a broad set of mathematically grounded techniques for adapting the behavior of dynamic systems. While it has been applied to specific software control problems, it has proved difficult to define methodologies allowing non-experts to systematically apply control te
The design of a controller for glycemia regulation, either in open or in closed-‐loop, relies on models able to describe the effects of a meal intake and an insulin injection on blood glucose dynamics. The purpose of this study was therefore to propose a physiological relevant yet parsimonious model for carbohydrate action on fasting blood glucose in T1DM patients when no insulin is taken.
The pathloss exponent and the variance of the large-scale fading are two parameters that are of great importance when modeling or characterizing wireless propagation channels. The pathloss is typically modeled using a single-slope log-distance power law model, whereas the large-scale fading is modeled using a log-normal distribution. In practice, the received signal is affected by noise and it mig
A number of techniques have been proposed to provide run- time performance guarantees while minimizing power consumption. One drawback of existing approaches is that they work only on a fixed set of components (or actuators) that must be specified at design time. If new components become available, these management systems must be redesigned and reimplemented. In this paper, we propose PTRADE, a n
It has been shown that optimal controller synthesis for positive systems can be formulated as a linear program. Leveraging these results, we propose a scalable iterative algorithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model. We achieve the desired feedback structure by augmenting the optimization problems w
The problem of resource management in a sys- tem of a-priori unknown software components executing on nondeterministic hardware is considered. The approach uses on-line parameter estimation to address uncertainties and combines this with a convex optimization-based control scheme able to handle overload situations. An algorithm to solve the optimization in real-time is presented together with perf
For interconnected systems and systems of large size, aggregating information of subsystems studied individually is useful for addressing the overall stability. In the Lyapunov- based analysis, summation and maximization of separately constructed functions are two typical approaches in such a philosophy. This paper focuses on monotone systems which are common in control applications and elucidates
This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding convergence to action profiles which are not Nash equilibria may not be trivial, unless the step-size sequence is appropriately tailored to the specifics of the game. In this paper, we sides
We consider a class of weak feedback polynomials for LFSRs in the nonlinear combiner. When feedback taps are located in small groups, a distinguishing attack can sometimes be improved considerably, compared to the common attack that uses low weight multiples. This class of weak polynomials was introduced in 2004 and the main property of the attack is that the noise variables are represented as vec
