Due to increase in demand for reconfigurability in embedded systems, real-time task scheduling is challenged by non-negligible reconfiguration overheads. If such overheads are not considered, tasks may not be schedula...
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ISBN:
(纸本)9783981080162
Due to increase in demand for reconfigurability in embedded systems, real-time task scheduling is challenged by non-negligible reconfiguration overheads. If such overheads are not considered, tasks may not be schedulable under given deadlines, and hence, affecting the quality of service. We introduce the problem of real-time periodic task scheduling under transition overhead on heterogeneous reconfigurable systems. We formulate the problem as a network flow problem and provide a mixed integer linear programming solution. We compare our proposed solution with optimal scheduling under maximum fixed transition overhead. We deployed our method on task scheduling for multiple communication protocols on reconfigurable FPGA-like systems. Results show that our proposed scheduling improves the task schedulability by 24.2% in comparison with non-preemptive EDF and by 17.5% in comparison with maximum-transition-overhead scheduling.
Hydrogen energy, as a clean energy source, is increasingly being applied to port operations. However, previous studies on hydrogen energy applications have largely overlooked the impact of hydrogen energy safety on sy...
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ISBN:
(数字)9798331523527
ISBN:
(纸本)9798331523534
Hydrogen energy, as a clean energy source, is increasingly being applied to port operations. However, previous studies on hydrogen energy applications have largely overlooked the impact of hydrogen energy safety on system design. This paper introduces prospect theory in the context of hydrogen-containing ports and proposes a safety dissatisfaction model for port operators based on this theory, which innovatively incorporates their considerations of hydrogen energy safety into the analytical framework. An optimization model of port integrated energy system based on hydrogen safety is developed and formulated as a mixed-integerlinearprogramming problem. The optimization model effectively reduces the operation cost and operator dissatisfaction level of the port through the simulation of a large port example, which validates the effectiveness of the proposed model.
Heat removal and power density distribution delivery have become two major reliability concerns in 3D stacked technology. In this paper, we propose a thermal-driven 3D floor-planner. Our contributions include: (1) a n...
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Heat removal and power density distribution delivery have become two major reliability concerns in 3D stacked technology. In this paper, we propose a thermal-driven 3D floor-planner. Our contributions include: (1) a novel multi-objective formulation to consider the thermal and performance constraints in the optimization approach; (2) an efficient mixed integer linear programming (MILP) representation of the floorplanning model; and (3) a smooth integration of the MILP model with an accurate thermal modelling of the architecture. The experimental work is conducted for two realistic many-core single-chip architectures: an homogeneous system resembling Intel's SCC, and an improved heterogeneous setup. The results show promising improvements of the mean, peak temperature and the thermal gradient, with a reduced overhead in the wire length of the system.
This paper presents the implementation of the energy storage for unit commitment and dispatch of conventional power plants. The optimization employs mixed integer linear programming. The simulations with different sce...
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This paper presents the implementation of the energy storage for unit commitment and dispatch of conventional power plants. The optimization employs mixed integer linear programming. The simulations with different scenarios have been carried out to demonstrate the effectiveness of the approach applied. The results obtained indicated that start-up energy of conventional power plants may impose the specific operation of energy storage systems. Cost benefits of energy storage implementation are also demonstrated.
This paper proposes an aggregated energy management of multiple factories that purchased green energy collectively. These factories purchase green energy collectively to get a better price. The green energy is procure...
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ISBN:
(数字)9798350355185
ISBN:
(纸本)9798350355192
This paper proposes an aggregated energy management of multiple factories that purchased green energy collectively. These factories purchase green energy collectively to get a better price. The green energy is procured for each time step throughout the consumption day in a day ahead manner. On the consumption day, the green energy provider feeds green energy into the power grid at each time step, following the quantities that were purchased for those specific time intervals. The aggregated energy management system optimally dispatches the electrical power of the factories in an aggregated manner based on the purchased green energy profiles to maximize the consumption of the purchased green energy. A mixed integer linear programming (MILP) formulation is developed to carry out the aggregated energy management. To overcome the high computation time associated with conventional MILP, a linearprogramming relaxation technique is employed. This technique relaxes the binary variables, allowing them to take any value between 0 and 1, which enables the optimization problem to be solved in a very short time. After solving the optimization problem, the values of the variables are corrected back to binary values using a delicate method to ensure the feasibility of the solution.
By splitting unit commitment into a coupling problem and individual unit commitment subproblems, Lagrangian relaxation is very effective in decreasing the solving time of large scale problems. Consequently, unit commi...
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By splitting unit commitment into a coupling problem and individual unit commitment subproblems, Lagrangian relaxation is very effective in decreasing the solving time of large scale problems. Consequently, unit commitment subproblems should be solved equally fast. If they have been originally formulated in mixed-integerlinearprogramming, performance advantages can be expected by replacing it with dynamic programming. However, it has not been reported whether a one-to-one reformulation is feasible. We suggest approaches to choose states for dynamic programming that replicate equal solutions as well as measures to reduce memory requirements. Results of the two subproblem models differ only fractionally and for explicable reasons. Subproblem computation time has been reduced by up to 100 times at modest memory requirements.
In this study,a developed inexact community-scale energy model has been developed for planning renewable energy management systems under *** allows uncertainties presented as both probability distributions and interva...
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In this study,a developed inexact community-scale energy model has been developed for planning renewable energy management systems under *** allows uncertainties presented as both probability distributions and interval values to be incorporated with in a general optimization *** method is based on an integration of the existing possibility degree method for interval numbers,the satisfaction degree method for stochastic variables and mixed integer linear programming *** can also facilitate capacityexpansion planning for energy-production facilities within a multi-period and multi-option *** in energy management systems can be systematically reflected,thus applicability of the modeling process can be highly *** model has then been applied to a case of long-term renewable energy management planning for three *** solutions for the planning of energy management systems have been generated.
We consider the reconfiguration problem in multi- fiber WDM optical networks. In a network with evolving traffic, the virtual topology may not remain optimal, leading to degradation of network performance. However, ad...
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We consider the reconfiguration problem in multi- fiber WDM optical networks. In a network with evolving traffic, the virtual topology may not remain optimal, leading to degradation of network performance. However, adapting the virtual topology to the changing traffic may lead to service disruption. This optimization problem hence captures the trade-off between network performance and number of reconfigurations applied to the virtual topology. This trade-off is considered via a multi- metrics approach. The above problem is solved through a mixed integer linear programming (MILP) formulation with a multivariate objective function. However the problem is NP-hard and such an approach is unable to solve large problem instances in a reasonable time. Therefore we propose a simulated annealing (SA) based heuristic approach for solving problems of higher complexity. We compare the performance and the computation time of solving the MILP model and the heuristic approach considering different test instances. We can find near optimal solutions for instances of medium complexity using the MILP model. The SA scheme can be used as a heuristic to arrive at near optimal solutions when the run-time of the MILP becomes practically infeasible. It also appears that the trade-off's involved in the reconfiguration problem cannot be left aside, as a little flexibility with respect to one metric allows to drastically improve the quality of the solution with respect to other metrics.
The problem of aggregating large data files from distributed databases and address the corresponding challenges involved from a network architecture perspective is considered. We model this problem as one of identifyi...
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The problem of aggregating large data files from distributed databases and address the corresponding challenges involved from a network architecture perspective is considered. We model this problem as one of identifying a time-path schedule (TPS) in a graph representation of the network. We prove that the TPS problem (TPSP) is NP-complete. We then propose a mixed integer linear programming (MILP)-based approach and three heuristics longest-file-first (LFF), disjoint-paths (DP), and most-distant-file-first (MDFF) - to solve TPSP.
This paper addresses the scheduling problem in port of Tripoli-Lebanon for a single quay crane with multiple yard trucks, all containers that will be unloaded from the vessel are in the same bay. The objective is to r...
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This paper addresses the scheduling problem in port of Tripoli-Lebanon for a single quay crane with multiple yard trucks, all containers that will be unloaded from the vessel are in the same bay. The objective is to reduce the completion time of all containers from the vessel to their store location, we used a mixed integer linear programming and a dynamic programming algorithm to solve the problem. Finally, we have compared and validated our results on real instances from the port.
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