6,942 research outputs found

    Energy Efficient Policies, Scheduling, and Design for Sustainable Manufacturing Systems

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    Climate mitigation, more stringent regulations, rising energy costs, and sustainable manufacturing are pushing researchers to focus on energy efficiency, energy flexibility, and implementation of renewable energy sources in manufacturing systems. This thesis aims to analyze the main works proposed regarding these hot topics, and to fill the gaps in the literature. First, a detailed literature review is proposed. Works regarding energy efficiency in different manufacturing levels, in the assembly line, energy saving policies, and the implementation of renewable energy sources are analyzed. Then, trying to fill the gaps in the literature, different topics are analyzed more in depth. In the single machine context, a mathematical model aiming to align the manufacturing power required to a renewable energy supply in order to obtain the maximum profit is developed. The model is applied to a single work center powered by the electric grid and by a photovoltaic system; afterwards, energy storage is also added to the power system. Analyzing the job shop context, switch off policies implementing workload approach and scheduling considering variable speed of the machines and power constraints are proposed. The direct and indirect workloads of the machines are considered to support the switch on/off decisions. A simulation model is developed to test the proposed policies compared to others presented in the literature. Regarding the job shop scheduling, a fixed and variable power constraints are considered, assuming the minimization of the makespan as the objective function. Studying the factory level, a mathematical model to design a flow line considering the possibility of using switch-off policies is developed. The design model for production lines includes a targeted imbalance among the workstations to allow for defined idle time. Finally, the main findings, results, and the future directions and challenges are presented

    Exploring performance and power properties of modern multicore chips via simple machine models

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    Modern multicore chips show complex behavior with respect to performance and power. Starting with the Intel Sandy Bridge processor, it has become possible to directly measure the power dissipation of a CPU chip and correlate this data with the performance properties of the running code. Going beyond a simple bottleneck analysis, we employ the recently published Execution-Cache-Memory (ECM) model to describe the single- and multi-core performance of streaming kernels. The model refines the well-known roofline model, since it can predict the scaling and the saturation behavior of bandwidth-limited loop kernels on a multicore chip. The saturation point is especially relevant for considerations of energy consumption. From power dissipation measurements of benchmark programs with vastly different requirements to the hardware, we derive a simple, phenomenological power model for the Sandy Bridge processor. Together with the ECM model, we are able to explain many peculiarities in the performance and power behavior of multicore processors, and derive guidelines for energy-efficient execution of parallel programs. Finally, we show that the ECM and power models can be successfully used to describe the scaling and power behavior of a lattice-Boltzmann flow solver code.Comment: 23 pages, 10 figures. Typos corrected, DOI adde

    Driving Energy System Transformation with "Vehicle-to-Grid" Power

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    Today's electricity and transport systems face a number of challenges related to reliability, security and environmental sustainability. New technologies may provide a means by which to overcome some of these challenges, yet many such technologies are confronted with substantial technical or commercial hurdles. This report explores one promising technology, "Vehicle-to-Grid" (V2G) power generation, whereby parked Electric-Drive Vehicles (EDVs) are used to provide electricity to the grid. EDVs comprise battery-electric (BEV), hybrid-electric (HEV) and fuel cell-electric (FCEV) vehicles. V2G power generation may be attractive because, on one hand, vehicles are parked on average 96% of their lifetime (and thus available for other uses) and, on the other, the power capacity of the global automobile fleet greatly exceeds installed conventional electricity generation capacity. We examine the potential of V2G power generation, firstly, from the EDV's owner perspective and, secondly, in the energy market place. Our results confirm that EDVs have some potential market value, considering our assumptions that are based on the CAISO Californian power market. To complement and extend the previous analysis, we compared the full economic costs of EDVs providing V2G power generation and mobility services with conventional solutions: power generated by gas turbine or coal-fired power plants; and mobility provided by conventional gasoline internal combustion engine vehicles (ICEVs). Our analysis indicates that although conventional systems generally remain competitive under today's market conditions, the complementary use of EDVs for energy and mobility may be competitive in specific power markets and under certain conditions. We explore the conditions under which V2G systems could be more competitive with a sensitivity analysis of the potential impact of technology and resource costs and infrastructure requirements. In addition, we analyse the impact of a climate policy on the competitiveness of alternatives. These results suggest that only carbon taxes up to $650/tonne of Carbon would have significant impacts on the ranking position of V2G technologies, although we explored only a limited set of scenarios and thus results should be envisaged with cautio

    Design and Implementation of High QoS 3D-NoC using Modified Double Particle Swarm Optimization on FPGA

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    One technique to overcome the exponential growth bottleneck is to increase the number of cores on a processor, although having too many cores might cause issues including chip overheating and communication blockage. The problem of the communication bottleneck on the chip is presently effectively resolved by networks-on-chip (NoC). A 3D stack of chips is now possible, thanks to recent developments in IC manufacturing techniques, enabling to reduce of chip area while increasing chip throughput and reducing power consumption. The automated process associated with mapping applications to form three-dimensional NoC architectures is a significant new path in 3D NoC research. This work proposes a 3D NoC partitioning approach that can identify the 3D NoC region that has to be mapped. A double particle swarm optimization (DPSO) inspired algorithmic technique, which may combine the characteristics having neighbourhood search and genetic architectures, also addresses the challenge of a particle swarm algorithm descending into local optimal solutions. Experimental evidence supports the claim that this hybrid optimization algorithm based on Double Particle Swarm Optimisation outperforms the conventional heuristic technique in terms of output rate and loss in energy. The findings demonstrate that in a network of the same size, the newly introduced router delivers the lowest loss on the longest path.  Three factors, namely energy, latency or delay, and throughput, are compared between the suggested 3D mesh ONoC and its 2D version. When comparing power consumption between 3D ONoC and its electronic and 2D equivalents, which both have 512 IP cores, it may save roughly 79.9% of the energy used by the electronic counterpart and 24.3% of the energy used by the latter. The network efficiency of the 3D mesh ONoC is simulated by DPSO in a variety of configurations. The outcomes also demonstrate an increase in performance over the 2D ONoC. As a flexible communication solution, Network-On-Chips (NoCs) have been frequently employed in the development of multiprocessor system-on-chips (MPSoCs). By outsourcing their communication activities, NoCs permit on-chip Intellectual Property (IP) cores to communicate with one another and function at a better level. The important components in assigning application duties, distributing the work to the IPs, and coordinating communication among them are mapping and scheduling methods. This study aims to present an entirely advanced form of research in the area of 3D NoC mapping and scheduling applications, grouping the results according to various parameters and offering several suggestions for further research

    EUROPEAN CONFERENCE ON QUEUEING THEORY 2016

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    International audienceThis booklet contains the proceedings of the second European Conference in Queueing Theory (ECQT) that was held from the 18th to the 20th of July 2016 at the engineering school ENSEEIHT, Toulouse, France. ECQT is a biannual event where scientists and technicians in queueing theory and related areas get together to promote research, encourage interaction and exchange ideas. The spirit of the conference is to be a queueing event organized from within Europe, but open to participants from all over the world. The technical program of the 2016 edition consisted of 112 presentations organized in 29 sessions covering all trends in queueing theory, including the development of the theory, methodology advances, computational aspects and applications. Another exciting feature of ECQT2016 was the institution of the Takács Award for outstanding PhD thesis on "Queueing Theory and its Applications"

    Modelling and performability evaluation of Wireless Sensor Networks

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    This thesis presents generic analytical models of homogeneous clustered Wireless Sensor Networks (WSNs) with a centrally located Cluster Head (CH) coordinating cluster communication with the sink directly or through other intermediate nodes. The focus is to integrate performance and availability studies of WSNs in the presence of sensor nodes and channel failures and repair/replacement. The main purpose is to enhance improvement of WSN Quality of Service (QoS). Other research works also considered in this thesis include modelling of packet arrival distribution at the CH and intermediate nodes, and modelling of energy consumption at the sensor nodes. An investigation and critical analysis of wireless sensor network architectures, energy conservation techniques and QoS requirements are performed in order to improve performance and availability of the network. Existing techniques used for performance evaluation of single and multi-server systems with several operative states are investigated and analysed in details. To begin with, existing approaches for independent (pure) performance modelling are critically analysed with highlights on merits and drawbacks. Similarly, pure availability modelling approaches are also analysed. Considering that pure performance models tend to be too optimistic and pure availability models are too conservative, performability, which is the integration of performance and availability studies is used for the evaluation of the WSN models developed in this study. Two-dimensional Markov state space representations of the systems are used for performability modelling. Following critical analysis of the existing solution techniques, spectral expansion method and system of simultaneous linear equations are developed and used to solving the proposed models. To validate the results obtained with the two techniques, a discrete event simulation tool is explored. In this research, open queuing networks are used to model the behaviour of the CH when subjected to streams of traffic from cluster nodes in addition to dynamics of operating in the various states. The research begins with a model of a CH with an infinite queue capacity subject to failures and repair/replacement. The model is developed progressively to consider bounded queue capacity systems, channel failures and sleep scheduling mechanisms for performability evaluation of WSNs. Using the developed models, various performance measures of the considered system including mean queue length, throughput, response time and blocking probability are evaluated. Finally, energy models considering mean power consumption in each of the possible operative states is developed. The resulting models are in turn employed for the evaluation of energy saving for the proposed case study model. Numerical solutions and discussions are presented for all the queuing models developed. Simulation is also performed in order to validate the accuracy of the results obtained. In order to address issues of performance and availability of WSNs, current research present independent performance and availability studies. The concerns resulting from such studies have therefore remained unresolved over the years hence persistence poor system performance. The novelty of this research is a proposed integrated performance and availability modelling approach for WSNs meant to address challenges of independent studies. In addition, a novel methodology for modelling and evaluation of power consumption is also offered. Proposed model results provide remarkable improvement on system performance and availability in addition to providing tools for further optimisation studies. A significant power saving is also observed from the proposed model results. In order to improve QoS for WSN, it is possible to improve the proposed models by incorporating priority queuing in a mixed traffic environment. A model of multi-server system is also appropriate for addressing traffic routing. It is also possible to extend the proposed energy model to consider other sleep scheduling mechanisms other than On-demand proposed herein. Analysis and classification of possible arrival distribution of WSN packets for various application environments would be a great idea for enabling robust scientific research
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