• ETRI Journal
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• v.42 no.3
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• pp.388-398
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• 2020

We herein propose a heuristic redundancy selection algorithm that combines resubmission, replication, and checkpointing redundancies to reduce the resiliency overhead in fault-tolerant workflow scheduling. The appropriate combination of these redundancies for workflow tasks is obtained in two consecutive phases. First, to compute the replication vector (number of task replicas), we apportion the set of provisioned resources among concurrently executing tasks according to their needs. Subsequently, we obtain the optimal checkpointing interval for each task as a function of the number of replicas and characteristics of tasks and computational environment. We formulate the problem of obtaining the optimal checkpointing interval for replicated tasks in situations where checkpoint files can be exchanged among computational resources. The results of our simulation experiments, on both randomly generated workflow graphs and real-world applications, demonstrated that both the proposed replication vector computation algorithm and the proposed checkpointing scheme reduced the resiliency overhead.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.642-647
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• 2014

In this paper, a hybrid genetic algorithm (HGA) approach is proposed for an n-job, m-machine flow shop scheduling problem with limited capacity buffers with blocking in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. HGA adopts the idea of seed selection and development in order to improve the exploitation and exploration power of genetic algorithms (GAs). Extensive computational experiments have been conducted to compare the performance of HGA with that of GA.

• Journal of the Korea Society for Simulation
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• v.5 no.2
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• pp.41-58
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• 1996

The Discrete Event Systems Specification(DEVS) formalism specifies a discrete event system in a hierarchical, modular form. This paper presents a distributed simulation environment D-DEVSim++ for models specified by the DEVS formalism. D-DEVSim++ employs a new simulation scheme which is a hybrid algorithm of the hierarchical simulation and Time Warp mechanisms. The scheme can utilize both the hierarchical scheduling parallelism and the inherent parallelism of DEVS models. This hierarchical scheduling parallelism is investigated through analysis. Performance of the proposed methodology is evaluated through benchmark simulation on a 5-dimensional hypercube parallel machine. The performance results indicate that the methodology can achieve significant speedup. Also, it is shown that the analyzed speedup for the hierarchical scheduling time corresponds the experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5269-5286
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• 2018

Task scheduling is one of the key issues in improving system performance and optimizing resource management in cloud computing environment. In order to provide appropriate services for heterogeneous users, we propose a novel task scheduling strategy with service differentiation, in which the delay sensitive tasks are assigned to the rapid cloud with high-speed processing, whereas the fault sensitive tasks are assigned to the reliable cloud with service restoration. Considering that a user can receive service from either local SaaS (Software as a Service) servers or public IaaS (Infrastructure as a Service) cloud, we establish a hybrid queueing network based system model. With the assumption of Poisson arriving process, we analyze the system model in steady state. Moreover, we derive the performance measures in terms of average response time of the delay sensitive tasks and utilization of VMs (Virtual Machines) in reliable cloud. We provide experimental results to validate the proposed strategy and the system model. Furthermore, we investigate the Nash equilibrium behavior and the social optimization behavior of the delay sensitive tasks. Finally, we carry out an improved intelligent searching algorithm to obtain the optimal arrival rate of total tasks and present a pricing policy for the delay sensitive tasks.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.171-177
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• 2009

Optical packet switching(OPS) is a strong candidate for the next-generation internet, since it has a fine switching granularity at the packet level for providing flexible bandwidth, and provides seamless integration between WDM layer and IP layer. Optical packet switching have been studied in two categories: OPS in synchronous and OPS in asynchronous networks. In this article we are focused on contention resolution of OPS in asynchronous networks. The hybrid buffer have been addressed, to reduce packet loss further as one of the alternative buffer structures for contention resolution of asynchronous and variable length packets, which consists of the FDL buffer and the electronic buffer. The OPS design issue for the limited number of TWCs and internal wavelengths is important in the aspect of switch cost and resource efficiency. Therefore, an hybrid buffer structured optical packet switch and its scheduling algorithm is presented for considering the limited number of TWCs and internal wavelengths, for contention resolution of asynchronous and variable length packets. The proposed algorithm could lead to the packet loss improvement compared to the legacy LAUC-VF algorithm with only the FDL buffer.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.114-116
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• 2004

The temperature profile control issue in the resistive welder for the electronic parts is discussed. The average current of the welder tip depends on the phase(on-time) of the AC power and the tip temperature maintains or increases/decreases depending on the integral of the current square and heat loss, The basic PID control algorithm with thermo-couple feedback is difficult to track the temperature profile for various parts and optimal gain changes much. So constant gain PID algorithm is not enough to cover various electronic parts welding and a Fuzzy-PID automatic gain tuning algorithm is devised and added to conventional PID algorithm and this hybrid control architecture is implemented and the experimental results are shown.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.189-196
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• 2009

We propose a hybrid broadcast scheduling based on a combination of periodic and on-demand data scheduling methods for mobile data broadcasting in convergence networks from communication and broadcasting. We consider an environment in which the forward channel is for data broadcasting and the reverse channel is for sending data requests via cellular phones, WLAN, WiBro, etc. Collecting statistics of requests from clients, the server partitions the data items into hot-item and cold-item sets. Hot items are sent based on a push-based scheduling. An on-demand scheduling method is applied to cold items. Performance evaluation from simulations shows that our proposed scheduling algorithm yields small response time with high successful response ratio.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.1-9
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• 2016

In this paper, for the improvement of quality of service(QoS) performance of heterogeneous networks, multi-cell scheduling is proposed. In order to implement the proposed algorithm, for the recognition of the impact on the throughput performance of users, macro-pico-cells that form distributed architecture were proposed. In operating heterogeneous networks, considering the centralized structure, a macro-RRH(Remote Radio Head) deployment scenario was proposed. For interference mitigation of the proposed system, by applying the optional sub-frame, through CQI(Channel Quality Indicator) measurement for each sub-frame period, constraint conditions were measured according to system situations. For the simplification, the pattern of the same ABS muting was assumed. In the above two multi-cell environments, the algorithm of high-speed load balancing maintenance was proposed.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.193-198
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• 2022

Face Detection is one of the most important aspects of image processing, it considers a time-consuming problem in real-time applications such as surveillance systems, face recognition systems, attendance system and many. At present, commodity hardware is getting more and more heterogeneity in terms of architectures such as GPU and MIC co-processors. Utilizing those co-processors along with the existing traditional CPUs gives the algorithm a better chance to make use of both architectures to achieve faster implementations. This paper presents a hybrid implementation of the face detection based on the local binary pattern (LBP) algorithm that is deployed on both traditional CPU and MIC co-processor to enhance the speed of the LBP algorithm. The experimental results show that the proposed implementation achieved improvement in speed by 3X when compared to a single architecture individually.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.49-56
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• 2023

In this study, we propose a genetic algorithm (GA) to optimize the allocation and operation order of transporters. The solution in the GA is represented by a set of lists each of which the operation order of the corresponding transporter. In addition, it was implemented in the form of a hybrid genetic algorithm combining effective local search operations for performance improvement. The local search reduces the number of operating transporters by moving blocks from a transporter with a low workload into that with a high workload. To evaluate the effectiveness of the proposed algorithm, it was compared with Multi-Start and a pure genetic algorithm through a simulation environment similar in scale to an actual shipyard. For the largest problem, compared to them, the number of transporters was reduced by 40% and 34%, and the total task time was reduced by 27% and 17%, respectively.