• Journal of Welding and Joining
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• v.24 no.5
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• pp.62-66
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• 2006

Panel line is an important process occupying the largest work amount in shipbuilding. In this research product simulation has been carried out to establish the optimal production scheduling. For this purpose a web-based panel line simulator was developed using an object modeling technology and C# language. The balance of work-load and increase in the productivity by the improvement of production facilities and process are the key factors for a good scheduling. In this study SPRT(Shortest Remaining Process Time) rule was applied for the work-load balancing and a good result achieved. To increase the productivity in the stiffener welding stage which is a bottleneck; process, more welding heads and higher welding speed were tested using the developed simulator. The simulation results showed that either more welding head or higher welding speed decreased the total work time. Use of both, however, deteriorated the productivity because of the bottleneck in the following stage. This result points out that the improvement of production facilities and/or process should be evaluated with their influences on the leading and following processing stage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3201-3223
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• 2020

Wireless communication has become the promising technology in the recent times because of its applications in Internet of Things( IoT) devices. The IEEE 802.15.4e has become the key technology for IoT devices which utilizes the Time-Slotted Channel Hopping (TSCH) networks for the communication between the devices. In this paper, we develop a Two Level Scheduling Algorithm (TLSA) for scheduling multiple packets with different arrival rate at the source nodes in a TSCH networks based on the link activated by a centralized scheduler. TLSA is developed by considering three types of links in a network such as link i with packets arrival type 1, link j with packets arrival type 2, link k with packets arrival type 3. For the data packets arrival, two stages in a network is considered.At the first stage, the packets are considered to be of higher priority.At the second stage, the packets are considered to be of lower priority.We introduce level 1 schedule for the packets at stage 1 and level 2 schedule for the packets at stage 2 respectively. Finally, the TLSA is validated with the two different energy functions i.e., y = e^ax - 1 and y = 0.5x² using MATLAB 2017a software for the computation of average and worst ratios of the two levels.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.9
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• pp.12-19
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• 2002

Guaranteed Frame Rate(GFR) service is intended to efficiently support TCP/IP traffic in ATM networks. The GFR service not only guarantees a minimum service rate at the frame level, but also supports a fair share of available bandwidth. The original GFR proposal outlined two switch implementation scheme : FIFO Queuing and perVC-Queuing. In general, it has been shown that FIFO Queuing is not sufficient to provide rate guarantees and perVC-Queuing with scheduling is needed. In perVC-Queuing implementation, scheduling algorithm plays key rule to provide rate guarantees and to improve fairness. We proposed a new scheduling algorithm for the GFR service. Proposed algorithm can provide minimum service rate guarantee and fair sharing to GFR VCs. Computer simulation results show that proposed scheduling scheme provide a much better performance in TCP Goodput and fairness than previous scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.975-980
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• 2019

In this paper, we propose a deep learning-based scheduling scheme for user selection in multi-user multi-antenna networks which is considered one of key technologies for the next generation mobile communication systems. We obtained 90,000 data samples from the conventional optimal scheme to train the proposed neural network and verified the trained neural network to check if the trained neural network is over-fitted. Although the proposed neural network-based scheduling algorithm requires considerable complexity and time for training in the initial stage, it does not cause any extra complexity once it has been trained successfully. On the other hand, the conventional optimal scheme continuously requires the same complexity of computations for every scheduling. According to extensive computer-simulations, the proposed deep learning-based scheduling algorithm yields about 88~96% average sum-rates of the conventional scheme for SNRs lower than 10dB, while it can achieve optimal average sum-rates for SNRs higher than 10dB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3266-3285
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• 2014

With limited computing and storage resources, many network applications of encryption algorithms require low power devices and fast computing components. CHESS-64 is designed by employing simple key scheduling and Data-Dependent operations (DDO) as main cryptographic components. Hardware performance for Field Programmable Gate Arrays (FPGA) and for Application Specific Integrated Circuits (ASIC) proves that CHESS-64 is a very flexible and powerful new cipher. In this paper, the security of CHESS-64 block cipher under related-key differential cryptanalysis is studied. Based on the differential properties of DDOs, we construct two types of related-key differential characteristics with one-bit difference in the master key. To recover 74 bits key, two key recovery algorithms are proposed based on the two types of related-key differential characteristics, and the corresponding data complexity is about $2^{42.9}$ chosen-plaintexts, computing complexity is about $2^{42.9}$ CHESS-64 encryptions, storage complexity is about $2^{26.6}$ bits of storage resources. To break the cipher, an exhaustive attack is implemented to recover the rest 54 bits key. These works demonstrate an effective and general way to attack DDO-based ciphers.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.99-106
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• 2005

The task scheduling in multiprocessor system Is one of the key elements in the effective utilization of multiprocessor systems. The optimal assignment of tasks to multiprocessor is, in almost all practical cases, an NP hard problem. Consequently various modern heuristics based algorithms have been proposed for practical reason. Recently, several approaches using Genetic Algorithm (GA) are proposed. However, these algorithms have only one objective such as minimizing cost and makespan. This paper proposes a new task scheduling algorithm using Genetic Algorithm combined simulated annealing (GA+SA) on multiprocessor environment. In solution algorithms, the Genetic Algorithm (GA) and the simulated annealing (SA) are cooperatively used. In this method. the convergence of GA is improved by introducing the probability of SA as the criterion for acceptance of new trial solution. The objective of proposed scheduling algorithm is to minimize makespan and total number of processors used. The effectiveness of the proposed algorithm is shown through simulation studies. In simulation studies, the results of proposed algorithm show better than that of other algorithms.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.493-501
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• 2013

A key challenge in massively multiplayer on-line game(MMOG) systems is providing real-time response latencies to the large number of concurrent game players. MMOG systems are a kind of soft real-time systems because requests from many players should be responded within specified time constraints. Client events have different timeliness and consistency requirements according to their nature in the game world. These requirements lead to tasks with different priorities on CPU processing. In order to meet their timing constraints, we propose priority scheduling methods that attempt to allocate preferentially more CPU bandwidth to serve an task with the higher priority level in the presence of transient overloading. The proposed scheduling methods are capable of enhancing real-time performance of MMOG system by maximizing the number of tasks with higher priority completed successfully within their deadlines while minimizing total average latency of tasks finished after given deadlines. The performance of these scheduling methods is evaluated through extensive simulation experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4103-4121
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• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.3-8
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• 2016

Wireless networks have evolved to the appearance of heterogeneous wireless networks(HetNet), where various networks provide data services with various data rates and coverage. One of technical issues for HetNet is efficient utilization of radio resources for system performance enhancement. For the next generation wireless networks, energy saving has become one of key performance indices, so energy-efficient resource management schemes for HetNet need to be developed. This paper addresses an energy-efficient scheduling for HetNet in order to improve the energy efficiency while maintaining similar system throughput as existing scheme, for which an energy-efficient scheduling that energy efficiency factor is included. Simulation results show that the proposed scheme achieves the reduction of energy consumption while admitting limited ragne of throughput degradation in comparison with the conventional proportional fair scheduling.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.78-86
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• 2015

Up-to-date business environment for manufacturers is very complex and rapidly changing. In other words, companies are facing a variety of changes, such as diversifying customer requirements, shortening product life cycles, and switching to small quantity batch production. In this situation, the companies are introducing the concept of JIT (just-in-time) to solve the problem of on-time production and on-time delivery for survival. Though many companies have introduced ERP (enterprise resource planning) systems and MRP (material requirement planning) systems, the performance of these systems seems to fall short of expectations. In this paper, the case study on introducing an APS (advanced planning and scheduling) system based on dispatching rules to a machining company and on finding a method to establish an efficient production schedule is presented. The case company has trouble creating an effective production plan and schedule, even though it is equipped with an MRP-based ERP system. The APS system is applied to CNC (computer numerical control) machines, which are key machines of the case company. The overall progress of this research is as follows. First, we collect and analyze the master data on individual products and processes of the case company in order to build a production scheduling model. Second, we perform a pre-allocation simulation based on dispatching rules in order to calculate the priority of each order. Third, we perform a set of production simulations applying the priority value in order to evaluate production lead time and tardiness of pre-defined dispatching rules. Finally, we select the optimal dispatching rule suitable for work situation of the case company. As a result, an improved production schedule leads to an increase in production and reduced production lead time.