• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1721-1730
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• 2007

SThis paper proposes a new dispatch scheduling algorithm in interconnected regional system operations. The dispatch scheduling formulated as mixed integer non-linear programming (MINLP) problem can efficiently be computed by generalized Benders decomposition (GBD) algorithm. GBD guarantees adequate computation speed and solution convergency since it decomposes a primal problem into a master problem and subproblems for simplicity. In addition, the inter-temporal optimal power flow (OPF) subproblem of the dispatch scheduling problem is comprised of various variables and constraints considering time-continuity and it makes the inter-temporal OPF complex due to increased dimensions of the optimization problem. In this paper, regional decomposition technique based on auxiliary problem principle (APP) algorithm is introduced to obtain efficient inter-temporal OPF solution through the parallel implementation. In addition, it can find the most economic dispatch schedule incorporating power transaction without private information open. Therefore, it can be expanded as an efficient dispatch scheduling model for interconnected system operation.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.36-44
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• 2014

Exploiting the energy-delay tradeoff for energy saving is critical for developing green wireless communication systems. In this paper, we investigate the delay-constrained energy-efficient packet transmission. We aim to minimize the energy consumption of multiple randomly arrived packets in an additive white Gaussian noise channel subject to individual packet delay constraints, by taking into account the practical on-off circuit power consumption at the transmitter. First, we consider the offline case, by assuming that the full packet arrival information is known a priori at the transmitter, and formulate the energy minimization problem as a non-convex optimization problem. By exploiting the specific problem structure, we propose an efficient scheduling algorithm to obtain the globally optimal solution. It is shown that the optimal solution consists of two types of scheduling intervals, namely "selected-off" and "always-on" intervals, which correspond to bits-per-joule energy efficiency maximization and "lazy scheduling" rate allocation, respectively. Next, we consider the practical online case where only causal packet arrival information is available. Inspired by the optimal offline solution, we propose a new online scheme. It is shown by simulations that the proposed online scheme has a comparable performance with the optimal offline one and outperforms the design without considering on-off circuit power as well as the other heuristically designed online schemes.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1721-1723
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• 2002

In 3rd-generation mobile communication systems providing packet service, optimal scheduling algorithms we needed to increase service efficiency. In this paper, three scheduling algorithms (SP, EDF, and RPQ) which have been studied in the field of computer networks are applied with transmit power constraint to an interference-limited CDMA system, proving to be efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1892-1912
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• 2022

With the massive demand and growth of cloud computing, virtualization plays an important role in providing services to end-users efficiently. However, with the increase in services over Cloud Computing, it is becoming more challenging to manage and run multiple Virtual Machines (VMs) in Cloud Computing because of excessive power consumption. It is thus important to overcome these challenges by adopting an efficient technique to manage and monitor the status of VMs in a cloud environment. Reduction of power/energy consumption can be done by managing VMs more effectively in the datacenters of the cloud environment by switching between the active and inactive states of a VM. As a result, energy consumption reduces carbon emissions, leading to green cloud computing. The proposed Efficient Dynamic VM Scheduling approach minimizes Service Level Agreement (SLA) violations and manages VM migration by lowering the energy consumption effectively along with the balanced load. In the proposed work, VM Scheduling for Efficient Dynamically Migrated VM (VMS-EDMVM) approach first detects the over-utilized host using the Modified Weighted Linear Regression (MWLR) algorithm and along with the dynamic utilization model for an underutilized host. Maximum Power Reduction and Reduced Time (MPRRT) approach has been developed for the VM selection followed by a two-phase Best-Fit CPU, BW (BFCB) VM Scheduling mechanism which is simulated in CloudSim based on the adaptive utilization threshold base. The proposed work achieved a Power consumption of 108.45 kWh, and the total SLA violation was 0.1%. The VM migration count was reduced to 2,202 times, revealing better performance as compared to other methods mentioned in this paper.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4A
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• pp.393-401
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• 2006

Energy consumption is an important design parameter for battery-operated embedded systems. Dynamic power management is one of the most well-known low-power design techniques. This paper proposes an online realtime scheduling algorithm, which we call energy-aware realtime scheduling using slack stealing (EARSS). The proposed algorithm gives the highest priority to the task with the largest degree of device overlap when the slack time exists. Scheduling result enables an efficient power management by reducing the number of state transitions. Experimental results show that the proposed algorithm can save the energy by 23% on average compared to the DPM-enabled system scheduled by the EDF algorithm.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.25-33
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• 2014

This paper proposes a power-efficient scheduling scheme that stochastically minimizes the power consumption of real-time tasks while meeting their deadlines on multicore processors. In the proposed scheme, uncertain computation amounts of given tasks are translated into probabilistic computation amounts based on their past completion amounts, and the mean power consumption of the translated probabilistic computation amounts is minimized with a finite set of discrete clock frequencies. Also, when system load is low, the proposed scheme activates a part of all available cores with unused cores powered off, considering the leakage power consumption of cores. Evaluation shows that the scheme saves up to 69% power consumption of the previous method.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1329-1339
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• 2017

This paper presents the power scheduling of a multi-microgrid (MMG) system using an optimization technique called particle swarm optimization (PSO). The PSO technique has been shown to be most effective at solving the various problems of the economic dispatch (ED) in a power system. In addition, a new MMG system configuration is proposed in this paper, through which the optimal power flow is achieved. Both optimization and power trading methods within an MMG are studied. The results of implementing PSO in an MMG system for optimal power flow and cost minimization are obtained and compared with another attractive and efficient optimization technique called the genetic algorithm (GA). The comparison between these two effective methods provides very competitive results, and their operating costs also appear to be comparable. Finally, in this study, power scheduling and a power trading method are obtained using the MATLAB program.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1423-1435
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• 2010

Building wireless sensor networks requires a constituting sensor node to consider the following limited hardware resources: a small battery lifetime limiting available power supply for the sensor node, a low-power microprocessor with a low-performance computing capability, and scarce memory resources. Despite such limited hardware resources of the sensor node, the sensor node platform needs to activate real-time sensing, guarantee the real-time processing of sensing data, and exchange data between individual sensor nodes concurrently. Therefore, in this paper, we propose an energy-efficient real-time task scheduling technique for battery-powered wireless sensor nodes. The proposed energy-efficient task scheduling technique controls the microprocessor's operating frequency and reduces the power consumption of a task by exploiting the slack time of the task when the actual execution time of the task can be less than its worst case execution time. The outcomes from experiments showed that the proposed scheduling technique yielded efficient performance in terms of guaranteeing the completion of real-time tasks within their deadlines and aiming to provide low power consumption.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.37-42
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• 2016

We investigate multi user joint rate scheduling and power allocation problem for a delay sensitive CDMA systems. First, we characterize the existing two user joint rate scheduling and power allocation. We then extend the problem to the case of the multi user systems. In general, there is no simple optimum solution for the multi user scheduling problem. To that end, we propose a sub optimum solution, termed 'virtual user approach'. We show the performance of the virtual user approach to verify the benefit of complexity.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2135-2141
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• 2015

Power line communication (PLC) is one of the major communication technologies in smart grid since it combines good communication capability with easy and simple deployment. As a power network can be modeled as a graph, we propose a vertex coloring based slot reuse scheduling in the time division multiple access (TDMA) period for PLCs. Our objective is to minimize the number of assigned time slots, while satisfying the quality of service (QoS) requirement of each station. Since the scheduling problem is NP-hard, we propose an efficient heuristic scheduling, which consists of repeated vertex coloring and slot reuse improvement algorithms. The simulation results confirm that the proposed algorithm significantly reduces the total number of time slots.