65,748 research outputs found

    A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks

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    Cell Switch-Off (CSO) is recognized as a promising approach to reduce the energy consumption in next-generation cellular networks. However, CSO poses serious challenges not only from the resource allocation perspective but also from the implementation point of view. Indeed, CSO represents a difficult optimization problem due to its NP-complete nature. Moreover, there are a number of important practical limitations in the implementation of CSO schemes, such as the need for minimizing the real-time complexity and the number of on-off/off-on transitions and CSO-induced handovers. This article introduces a novel approach to CSO based on multiobjective optimization that makes use of the statistical description of the service demand (known by operators). In addition, downlink and uplink coverage criteria are included and a comparative analysis between different models to characterize intercell interference is also presented to shed light on their impact on CSO. The framework distinguishes itself from other proposals in two ways: 1) The number of on-off/off-on transitions as well as handovers are minimized, and 2) the computationally-heavy part of the algorithm is executed offline, which makes its implementation feasible. The results show that the proposed scheme achieves substantial energy savings in small cell deployments where service demand is not uniformly distributed, without compromising the Quality-of-Service (QoS) or requiring heavy real-time processing

    A Novel Fuzzy Logic Based Adaptive Supertwisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

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    This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness of the proposed controller over the first order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on a DC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desired transient response without causing chattering and error under steady-state conditions. The proposed controller is able to give robust performance in terms of rejection to input voltage variations and load variations.Comment: 14 page

    An Evolutionary Algorithm to Optimize Log/Restore Operations within Optimistic Simulation Platforms

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    In this work we address state recoverability in advanced optimistic simulation systems by proposing an evolutionary algorithm to optimize at run-time the parameters associated with state log/restore activities. Optimization takes place by adaptively selecting for each simulation object both (i) the best suited log mode (incremental vs non-incremental) and (ii) the corresponding optimal value of the log interval. Our performance optimization approach allows to indirectly cope with hidden effects (e.g., locality) as well as cross-object effects due to the variation of log/restore parameters for different simulation objects (e.g., rollback thrashing). Both of them are not captured by literature solutions based on analytical models of the overhead associated with log/restore tasks. More in detail, our evolutionary algorithm dynamically adjusts the log/restore parameters of distinct simulation objects as a whole, towards a well suited configuration. In such a way, we prevent negative effects on performance due to the biasing of the optimization towards individual simulation objects, which may cause reduced gains (or even decrease) in performance just due to the aforementioned hidden and/or cross-object phenomena. We also present an application-transparent implementation of the evolutionary algorithm within the ROme OpTimistic Simulator (ROOT-Sim), namely an open source, general purpose simulation environment designed according to the optimistic synchronization paradigm

    Comparative analysis of neutronics/thermal-hydraulics multi-scale coupling for LWR analysis

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    The aim of the research described in this paper is to perform consistent comparative analyses of two different approaches for coupling of two-scale, two-physics phenomena in reactor core calculations. The physical phenomena of interest are the neutronics and the thermal-hydraulics core behaviors and their interactions, while the spatial scales are the “global” (assembly/channel-wise) and the “local” (pin/sub-channel-wise). The objective is three-fold: qualification of coupled code systems by consistent step-by-step cross-comparison (in order to understand the prediction deviations in both neutronics and thermal-hydraulics parameters); assessment of fine scale (local/subchannel-wise) thermal-hydraulic effects; and evaluation of the impact of on-line modeling of interactions of the two spatial scales. The reported work is within the cooperation between the Universidad Politécnica de Madrid (UPM), Spain and the Pennsylvania State University (PSU), USA. The paper first presents the two multi-scale coupled code systems followed by cross-comparisons for steady state calculations. Selected results are discussed to highlight some of the issues involved in comparative analysis of coupled multi-scale simulations. The transient comparisons are subject of future work and publications
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