• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.421-436
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• 1999

It is discussed how to locate idle vehicles of AGVS considering dynamically changing situation. Several positioning methods are suggested including static positioning, dynamic positioning with time-independent pickup probabilities, dynamic positioning with time-dependent pickup probabilities, and dynamic positioning with a look-ahead capability. These positioning strategies are compared with each other by a simulation experiment.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.7
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• pp.283-292
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• 2013

In order to ensure high performance, all the servers in an existing server cluster are always On regardless of number of real-time requests. They ensure QoS, but waste server power if some of them are idle. To save energy consumed by servers, the server power mode control was developed by shutdowning a server when a server is not needed. There are two types of server power mode control depending on when a server is actually turned off if the server is selected to be off: static or dynamic. In a static mode, the server power is actually turned off after a fixed time delay from the time of the server selection. In a dynamic mode, server power is actually turned off if all the services served in the server are done. This corresponds to a turn off after a variable time delay. The static mdoe has disadvantages. It takes much time to find an optimal shutdown time manually through repeated experiments. In this paper, we propose a dynamic shutdown method to overcome the disadvantages of static shutdown. The proposed method allows to guarantee user QoS with good power-saving because it automatically approaches an optimal shutdown time. We performed experiments using 30 PCs cluster. Experimental results show that the proposed dynamic shutdown method is almost same as the best static shutdown in terms of power saving, but better than the best static shutdown in terms of QoS.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.971-976
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• 2014

In this paper, we proposed a low power algorithm using state transition ready method. The proposed algorithm defined a sleep state, a idle state and a run state for the task. A state transition occurring at the time due to the delay time created in order to reduce the power consumption state in the middle of each inserted into the ready state. The ready state considering a power consumption and a delay time in state transition. A scheduling step of performing the steps in excess of the increasing problems have the delay time is long. The power consumption increased for the operation step increase. A state transition from a sleep state with the longest delay time in operating state occurs when the state is switched by the time delay caused by the increase in operating time reduces the overall power consumption reduced. Experiments [6] were compared with the results of the power consumption. The experimental results [6] is reduced power consumption than the efficiency of the algorithm has been demonstrated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.5
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• pp.361-367
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• 2014

In this paper, task scheduling and load balancing methods of multifrontal solution methods of finite element structural analysis in a modern multicore machine are introduced. Many structural analysis problems have generally irregular grid and many kinds of properties and materials. These irregularities and heterogeneities lead to bottleneck of parallelization and cause idle time to analysis. Therefore, task scheduling and load balancing are desired to reduce inefficiency. Several kinds of multithreaded parallelization methods are presented and comparison between static and dynamic task scheduling are shown. To reduce the idle time caused by irregular partitioned subdomains, computational load balancing methods, Balancing all tasks and minmax task pairing balancing, are invented. Theoretical and actual elapsed time are shown and the reason of their performance gap are discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.253-256
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• 2000

In general, Automated Storage/Retrieval Systems (AS/RS ) have racks of equal sized cells to utilize the concept of unit-load. Most of the techniques for the performance estimation of a unit-load AS/RS are a static model or computer simulation. Especially, their models were developed under assumption that the Storage/Retrieval (S/R) machine performs only single command (SC) or dual command (DC). In reality, defending on the operating policy and the status of the system at a particular time, the S/B machine performs a SC or a DC, or becomes .: idle. In order to resolve these weak points, we propose a stochastic model for the performance estimation of unit-load AS/RS by using a single-server queueing model. Expected numbers of waiting storage and retrieval commands are found

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2101-2119
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• 2013

The spectrum allocation is an attractive issue for mobile cognitive radio (CR) network. However, the time-varying characteristic of the spectrum allocation is not fully investigated. Thus, this paper originally deduces the probabilities of spectrum availability and interference constrain in theory under the mobile environment. Then, we propose a prediction mechanism of the time-varying available spectrum lists and the dynamic interference topologies. By considering the node mobility and primary users' (PUs') activity, the mechanism is capable of overcoming the static shortcomings of traditional model. Based on the mechanism, two prediction-based spectrum allocation algorithms, prediction greedy algorithm (PGA) and prediction fairness algorithm (PFA), are presented to enhance the spectrum utilization and improve the fairness. Moreover, new utility functions are redefined to measure the effectiveness of different schemes in the mobile CR network. Simulation results show that PGA gets more average effective spectrums than the traditional schemes, when the mean idle time of PUs is high. And PFA could achieve good system fairness performance, especially when the speeds of cognitive nodes are high.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.59-62
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• 2000

Many of the previous researchers have been studied for the performance estimation of an AS/RS with a static model or computer simulation. Especially, they assumes that the storage/retrieval (S/R) machine performs either only single command (SC) or dual command (DC) and their requests are known in advance. However, the S/R machine performs a SC or a DC. or both or becomes idle according to the operating policy and the status of system at an arbitrary point of time. In this paper, we propose a stochastic model for the performance estimation of a unit-load AS/RS by using a M/G/1 queueing model with a single-server and two queues. Expected numbers of waiting storage and retrieval commands, and the waiting time in queues for the storage and retrieval commands are found

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.111-117
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• 2001

Most of the techniques for the performance estimation of unit-load AS/RS are a static model or computer simulation. Especially, their models have been developed under the assumption that the Storage/Retrieval (S/R) machine performs either single command(SC) or dual command(DC) only. In reality, depending on the operating policy and the status of the system at a particular time, the S/R machine performs a SC or a DC, or becomes idle. In order to resolve this weak point, we propose a stochastic model for the performance estimation of unit-load ASIRS by using a M/G/1 queueing model with a single server and two queues. Server utilization, expected numbers of waiting storage and retrieval commands and mean time spent in queue and system are found.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.629-636
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• 2007

This paper describes the process of analyzing vehicle stiffness in terms of frequency band in order to improve vehicle handling. Vehicle handling and ride comfort are highly related to the systems such as suspension, seat, steering, and the car body design. In existing analytical processes, the resonance frequency of a car body is designed to be greater than 25 Hz in order to increase the stiffness of the body against idle vibration. This paper introduces a method for using a band with a frequency lower than 20 Hz to analyze how stiffness affects vehicle handling. Accordingly, static stiffness analysis of a 1g cornering force was conducted to minimize the deformation of vehicle components derived from a load on parts attached to the suspension. In addition, this technology is capable of achieving better performance than older technology. Analysis of how body attachment stiffness affects the dynamic stiffness of a bushing in the attachment parts of the suspension is expected to lead to improvements with respect to vehicle handling and road noise. The process of developing a car body with a high degree of stiffness, which was accomplished in the preliminary stage of this study, confirms the possibility of improving the stability performance and of designing a lightweight prototype car. These improvements can reduce the time needed to develop better vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.