Articles de revista
http://hdl.handle.net/2117/3645
2018-02-23T07:09:39ZEnhanced DC-Link Capacitor Voltage Balancing Control of DC-AC Multilevel Multileg Converters
http://hdl.handle.net/2117/28072
Enhanced DC-Link Capacitor Voltage Balancing Control of DC-AC Multilevel Multileg Converters
Busquets Monge, Sergio; Maheshwari, RamKrishan; Nicolás Apruzzese, Joan; Lupón Roses, Emilio; Munk Nielsen, Stig; Bordonau Farrerons, José
This paper presents a capacitor voltage balancing control applicable to any multilevel dc-ac converter formed by a single set of series-connected capacitors implementing the dc link and semiconductor devices, such as the diode-clamped topology. The control is defined for any number of dc-link voltage levels and converter legs (for single-phase and multiphase systems), guaranteeing the capacitor voltage control for any modulation index value and load (from idle mode to full power). The associated control loop small-signal transfer function is presented, from which optimum compensator design guidelines are derived. The improvement in control performance is verified through simulation and experiments comparing with a previous balancing control strategy in a four-level three-phase dc-ac conversion system. The satisfactory control performance is also verified through simulation in a four-level five-phase dc-ac conversion system.
2015-05-27T15:54:29ZBusquets Monge, SergioMaheshwari, RamKrishanNicolás Apruzzese, JoanLupón Roses, EmilioMunk Nielsen, StigBordonau Farrerons, JoséThis paper presents a capacitor voltage balancing control applicable to any multilevel dc-ac converter formed by a single set of series-connected capacitors implementing the dc link and semiconductor devices, such as the diode-clamped topology. The control is defined for any number of dc-link voltage levels and converter legs (for single-phase and multiphase systems), guaranteeing the capacitor voltage control for any modulation index value and load (from idle mode to full power). The associated control loop small-signal transfer function is presented, from which optimum compensator design guidelines are derived. The improvement in control performance is verified through simulation and experiments comparing with a previous balancing control strategy in a four-level three-phase dc-ac conversion system. The satisfactory control performance is also verified through simulation in a four-level five-phase dc-ac conversion system.Improving security in cache memory by power efficient scrambling technique
http://hdl.handle.net/2117/28039
Improving security in cache memory by power efficient scrambling technique
Neagu, Madalin; Miclea, Liviu; Manich Bou, Salvador
The last decade has recorded an increase in security protocols for integrated circuits and memory systems, because of device specific attacks such as side-channel monitoring and cold boot and also because sensitive information is stored in such devices. The scope of this study is to propose new security measures which can be applied in memory systems, in order to make the stored data unusable, if retrieved successfully by any type of attack. The security technique uses interleaved scrambling vectors to scramble the data retained in a memory system and employs several dissemination rules. The proposed technique is investigated and assessed from several perspectives, such as power consumption, time performance and area overhead.
2015-05-25T17:05:40ZNeagu, MadalinMiclea, LiviuManich Bou, SalvadorThe last decade has recorded an increase in security protocols for integrated circuits and memory systems, because of device specific attacks such as side-channel monitoring and cold boot and also because sensitive information is stored in such devices. The scope of this study is to propose new security measures which can be applied in memory systems, in order to make the stored data unusable, if retrieved successfully by any type of attack. The security technique uses interleaved scrambling vectors to scramble the data retained in a memory system and employs several dissemination rules. The proposed technique is investigated and assessed from several perspectives, such as power consumption, time performance and area overhead.SRAM cell stability metric under transient voltage noise
http://hdl.handle.net/2117/25228
SRAM cell stability metric under transient voltage noise
Vatajelu, Elena Ioana; Gómez Pau, Álvaro; Renovell, Michel; Figueras Pàmies, Joan
2015-01-12T16:17:26ZVatajelu, Elena IoanaGómez Pau, ÁlvaroRenovell, MichelFigueras Pàmies, JoanTransient analysis of rewarded continuous time Markov models by regenerative randomization with Laplace transform inversion
http://hdl.handle.net/2117/24862
Transient analysis of rewarded continuous time Markov models by regenerative randomization with Laplace transform inversion
Carrasco, Juan A.
In this paper we develop a variant, regenerative randomization with Laplace transform inversion, of a previously proposed method (the regenerative randomization method) for the transient analysis of rewarded continuous time Markov models. Those models find applications in dependability and performability analysis of computer and telecommunication systems. The variant differs from regenerative randomization in that the truncated transformed model obtained in that method is solved using a Laplace transform inversion algorithm instead of standard randomization. As regenerative randomization, the variant requires the selection of a regenerative state on which the performance of the method depends. For a class of models, class C’, including typical failure/repair models, a natural selection for the regenerative state exists and, with that selection, theoretical results are available assessing the performance of the method in terms of “visible” characteristics. Using dependability class C’ models of moderate size of a RAID 5 architecture we compare the performance of the variant with those of regenerative randomization and randomization with steady-state detection for irreducible models, and with those of regenerative randomization and standard randomization for models with absorbing states. For irreducible models, the new variant seems to be about as fast as randomization with steady-state detection for models which are not too small when the initial probability distribution is concentrated in the regenerative state, and significantly faster than regenerative randomization when the model is stiff and not very large. For stiff models with absorbing states, the new variant is much faster than standard randomization and significantly faster than regenerative randomization when the model is not very large. In addition, the variant seems to be able to achieve stringent accuracy levels safely.
2014-11-27T09:40:31ZCarrasco, Juan A.In this paper we develop a variant, regenerative randomization with Laplace transform inversion, of a previously proposed method (the regenerative randomization method) for the transient analysis of rewarded continuous time Markov models. Those models find applications in dependability and performability analysis of computer and telecommunication systems. The variant differs from regenerative randomization in that the truncated transformed model obtained in that method is solved using a Laplace transform inversion algorithm instead of standard randomization. As regenerative randomization, the variant requires the selection of a regenerative state on which the performance of the method depends. For a class of models, class C’, including typical failure/repair models, a natural selection for the regenerative state exists and, with that selection, theoretical results are available assessing the performance of the method in terms of “visible” characteristics. Using dependability class C’ models of moderate size of a RAID 5 architecture we compare the performance of the variant with those of regenerative randomization and randomization with steady-state detection for irreducible models, and with those of regenerative randomization and standard randomization for models with absorbing states. For irreducible models, the new variant seems to be about as fast as randomization with steady-state detection for models which are not too small when the initial probability distribution is concentrated in the regenerative state, and significantly faster than regenerative randomization when the model is stiff and not very large. For stiff models with absorbing states, the new variant is much faster than standard randomization and significantly faster than regenerative randomization when the model is not very large. In addition, the variant seems to be able to achieve stringent accuracy levels safely.Regenerative randomization: theory and application examples
http://hdl.handle.net/2117/23553
Regenerative randomization: theory and application examples
Carrasco, Juan A.; Calderón Alvarez, Angel
Randomization is a popular method for the transient solution of continuous-time Markov models. Its primary advantages over other methods (i.e., ODE solvers) are robustness and ease of implementation. It is however well-known that the performance of the method deteriorates with the
2014-07-18T09:02:02ZCarrasco, Juan A.Calderón Alvarez, AngelRandomization is a popular method for the transient solution of continuous-time Markov models. Its primary advantages over other methods (i.e., ODE solvers) are robustness and ease of implementation. It is however well-known that the performance of the method deteriorates with theEvaluation of safety-oriented two-version architectures
http://hdl.handle.net/2117/23547
Evaluation of safety-oriented two-version architectures
Carrasco, Juan A.; Figueras Pàmies, Joan; Kuntzman, A
A Markov model taking into account physical and design faults for a two-version architecture oriented to safety-related applications is developed. Only a probabilistic knowledge of the initial state of the versions in relation to the presence of design faults is assumed. The model can be split into two submodels accounting separately for physical and design faults, and a closed form expression for the unsafety of the system is obtained. The parameter estimation problem is discussed and a method to predict the probability distribution of the number of related design faults at the beginning of the operational life of the system is proposed. The method uses a pool model to process fault-occurrence data collected during a “face-to-face” debugging of the two versions. It has by nature a limited capability for proving version diversity, but it is shown that the limit is of the order of the diversity reported by recent experiments on real software. Finally, the impact of version correction during operation is shown to be negligible for critical applications.
2014-07-18T07:48:02ZCarrasco, Juan A.Figueras Pàmies, JoanKuntzman, AA Markov model taking into account physical and design faults for a two-version architecture oriented to safety-related applications is developed. Only a probabilistic knowledge of the initial state of the versions in relation to the presence of design faults is assumed. The model can be split into two submodels accounting separately for physical and design faults, and a closed form expression for the unsafety of the system is obtained. The parameter estimation problem is discussed and a method to predict the probability distribution of the number of related design faults at the beginning of the operational life of the system is proposed. The method uses a pool model to process fault-occurrence data collected during a “face-to-face” debugging of the two versions. It has by nature a limited capability for proving version diversity, but it is shown that the limit is of the order of the diversity reported by recent experiments on real software. Finally, the impact of version correction during operation is shown to be negligible for critical applications.Corrigendum: "Transient Analysis of Rewarded Continuous Time Markov Models by Regenerative Randomization with Laplace Transform Inversion"
http://hdl.handle.net/2117/23426
Corrigendum: "Transient Analysis of Rewarded Continuous Time Markov Models by Regenerative Randomization with Laplace Transform Inversion"
Carrasco, Juan A.
Clarifications regarding paper with same title and authors published in the same journal.
2014-07-08T10:05:11ZCarrasco, Juan A.Clarifications regarding paper with same title and authors published in the same journal.Corrections on “Failure Transition Distance-Based Importance Sampling Schemes for the Simulation of Repairable Fault-Tolerant Computer Systems"
http://hdl.handle.net/2117/23425
Corrections on “Failure Transition Distance-Based Importance Sampling Schemes for the Simulation of Repairable Fault-Tolerant Computer Systems"
Carrasco, Juan A.
Various corrections to the above titled paper (ibid., vol. 55, no. 2, pp. 207-236) are presented. The corrections do not propagate to any other part of the paper and do not affect the correctness of the experimental results reported in the paper.
2014-07-08T10:01:13ZCarrasco, Juan A.Various corrections to the above titled paper (ibid., vol. 55, no. 2, pp. 207-236) are presented. The corrections do not propagate to any other part of the paper and do not affect the correctness of the experimental results reported in the paper.Transient analysis of Markov models of fault-tolerant systems with deferred repair using split regenerative randomization
http://hdl.handle.net/2117/23392
Transient analysis of Markov models of fault-tolerant systems with deferred repair using split regenerative randomization
Carrasco, Juan A.; Temsamani, Jamal
The (standard) randomization method is an attractive alternative for the transient analysis of continuous time Markov models. The main advantages of the method are numerical stability, well-controlled computation error, and ability to specify the computation error in advance. However, the fact that the method can be computationally very expensive limits its applicability. In this paper, we develop a new method called split regenerative randomization, which, having the same good properties as standard randomization, can be significantly more efficient. The method covers reliability-like models with a particular but quite general structure and requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, model class C_2, including typical failure/repair reliability-like models with exponential failure and repair time distributions and deferred repair, natural selections are available for both the subset of states and the regenerative state and,
for those natural selections, theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. Those results can be used to anticipate when the method can be expected to be competitive. We illustrate the application of the method using a large class C_2 model and show that for models in that class the method can indeed be significantly more efficient than previously available randomization-based methods
2014-07-03T06:38:15ZCarrasco, Juan A.Temsamani, JamalThe (standard) randomization method is an attractive alternative for the transient analysis of continuous time Markov models. The main advantages of the method are numerical stability, well-controlled computation error, and ability to specify the computation error in advance. However, the fact that the method can be computationally very expensive limits its applicability. In this paper, we develop a new method called split regenerative randomization, which, having the same good properties as standard randomization, can be significantly more efficient. The method covers reliability-like models with a particular but quite general structure and requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, model class C_2, including typical failure/repair reliability-like models with exponential failure and repair time distributions and deferred repair, natural selections are available for both the subset of states and the regenerative state and,
for those natural selections, theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. Those results can be used to anticipate when the method can be expected to be competitive. We illustrate the application of the method using a large class C_2 model and show that for models in that class the method can indeed be significantly more efficient than previously available randomization-based methodsA Numerical method for the evaluation of the distribution of cumulative reward till exit of a Subset of transient states of a Markov reward model
http://hdl.handle.net/2117/23376
A Numerical method for the evaluation of the distribution of cumulative reward till exit of a Subset of transient states of a Markov reward model
Carrasco, Juan A.; Suñé, Víctor
Markov reward models have interesting modeling applications, particularly those addressing fault-tolerant hardware/software systems. In this paper, we consider a Markov reward model with a reward structure including only reward rates associated with states, in which both positive and negative reward rates are present and null reward rates are allowed, and develop a numerical method to compute the distribution function of the cumulative reward till exit of a subset
of transient states of the model. The method combines a model transformation step with the solution of the transformed model using a randomization construction with two randomization rates. The method introduces a truncation error, but that error is strictly bounded from above by a user-specified error control parameter. Further, the method is numerically stable and takes advantage of the sparsity of the infinitesimal generator of the transformed model. Using a Markov
reward model of a fault-tolerant hardware/software system, we illustrate the application of the method and analyze its computational cost. Also, we compare the computational cost of the method with that of the (only) previously available method for the problem. Our numerical experiments seem to indicate that the new method can be efficient and that for medium-size and large models can be substantially faster than the previously available method.
2014-07-02T08:08:06ZCarrasco, Juan A.Suñé, VíctorMarkov reward models have interesting modeling applications, particularly those addressing fault-tolerant hardware/software systems. In this paper, we consider a Markov reward model with a reward structure including only reward rates associated with states, in which both positive and negative reward rates are present and null reward rates are allowed, and develop a numerical method to compute the distribution function of the cumulative reward till exit of a subset
of transient states of the model. The method combines a model transformation step with the solution of the transformed model using a randomization construction with two randomization rates. The method introduces a truncation error, but that error is strictly bounded from above by a user-specified error control parameter. Further, the method is numerically stable and takes advantage of the sparsity of the infinitesimal generator of the transformed model. Using a Markov
reward model of a fault-tolerant hardware/software system, we illustrate the application of the method and analyze its computational cost. Also, we compare the computational cost of the method with that of the (only) previously available method for the problem. Our numerical experiments seem to indicate that the new method can be efficient and that for medium-size and large models can be substantially faster than the previously available method.