• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2008.06a
• /
• pp.911-912
• /
• 2008

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.829-831
• /
• 1996

This paper is concerning on a study on the object-oriented programming and its application to maintenance scheduling. The concept of object-oriented programming enables us to modify and reuse software with much ease. By introducing object-oriented programming to maintenance scheduling, we can develop a hierarchical and reusable software in maintenance scheduling. The maintenance scheduling problem becoming more and more large and complex can be dealt with the concept of object-oriented technique and we hope this concept will give a reasonable solution. And evolutionary computation will be developed as a optimization technique.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.11
• /
• pp.5243-5263
• /
• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.11
• /
• pp.3523-3543
• /
• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.1
• /
• pp.287-307
• /
• 2018

There are two targets to schedule parallel jobs in the Cloud: (1) scheduling the jobs as many as possible, and (2) reducing the average execution time of the jobs. Most of previous work mainly focuses on the computing speed of resources without considering other attributes, such as bandwidth, memory and so on. Especially, past work does not consider the supply-demand condition from those attributes. Resources have different attributes, considering those attributes together makes the scheduling problem more difficult. This is the problem that we try to solve in this paper. First of all, we propose a new parallel job scheduling method based on a classification method of resources from different attributes, and then a scheduling method-CPLMT (Cloud parallel scheduling based on the lists of multiple attributes) is proposed for the parallel tasks. The classification method categories resources into different kinds according to the number of resources that satisfy the job from different attributes of the resource, such as the speed of the resource, memory and so on. Different kinds have different priorities in the scheduling. For the job that belongs to the same kinds, we propose CPLMT to schedule those jobs. Comparisons between our method, FIFO (First in first out), ASJS (Adaptive Scoring Job Scheduling), Fair and CMMS (Cloud-Minmin) are executed under different environments. The simulation results show that our proposed CPLMT not only reduces the number of unfinished jobs, but also reduces the average execution time.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1995.04a
• /
• pp.208-215
• /
• 1995

Numerous solution methods for scheduling problems such as part dispatching problem, operation sequence problem have been suggested as a means to be embedded in hierarchical or centralized shop floor control. Under the preceding control philosophies, however, response to changes in the shop floor status is quite slow and timely decision is sometimes impossible. Moreover, the control software becomes too large and it is almost impossible to modify the control software when the configuration of the shop floor changes. In agile manufacturing which emerged recently to cope with quick response and easy modifiability when unexpected changes occur, a new control policy is needed. CSCW[Computer Supported Cooperative Work] based shop floor control casts a different view on scheduling problems. Decisions are made locally when requested and useful information is scattered among agents for its efficient use. Adaptation is easy because agents are -'plug compatible or portable. In this paper, scheduling problems occurring under CSCW based shop floor control are identified and characterized. Traditional scheduling problems are reviewed from the CSCW viewpoint. All the control entities involved in the shop floor can be found and used to defined agents. With these entities and CSCW concept, possible scheduling problems are identified.

• Journal of Multimedia Information System
• /
• v.5 no.1
• /
• pp.53-58
• /
• 2018

The Republic of Korea (ROK) has been putting much effort to deal with diabetes which is being increasingly found in all age groups due to inadequate diet. Diabetes is closely related to one's eating habits and lifestyle that often cause hyperglycemia so that it is essential for the diabetic patients to change them to improve or control the major symptoms of diabetes. This study introduces a software engineering solution to support these patients. The software designed for the solution lets the patients to easily recognize their sugar levels and current treatment schemes and then advises a more effective approach along with the essential information through the embedded push service. The major goal of this study is to support diabetes patients by providing a convenient but effective means to prevent or improve diabetic symptoms by patients themselves who will in turn change their lifestyles in a positive manner.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.04a
• /
• pp.677-679
• /
• 2017

Data convergecast is an indispensable task for any WSN applications. Typically, scheduling in the WSN consists of two phases: tree construction and scheduling. The optimal tree structure and scheduling for the network is proven NP-hard. This paper focuses on the delay optimality while constructing the data convergecast tree. The algorithm can take any tree as the input, and by performing the switches (i.e. a node changes its parent), the expected aggregation delay is potentially reduced. Note that while constructing the tree, only the in-tree collisions between the child nodes sending data to their common parent is considered.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.13 no.6
• /
• pp.279-288
• /
• 2018

As a result of the technological advances in the E / E system, automotive system can provide advanced functions for safety and comfort. In addition, mechanical systems is changed to the electronic system. And the systems perform cooperative functions through communication. So the E / E system becomes more complicated as the size of the system increases. In order to secure the safety of complicated E / E system, ISO26262 standard require that Freedom from Interference and Sufficient Independence be met. In this paper, we propose a software scheduling method that can guarantee the independence between decomposed components after software decomposition and software development of ASIL D level EPB (Electronic Parking Brake) system.

• Journal of KIISE:Software and Applications
• /
• v.34 no.5
• /
• pp.487-501
• /
• 2007

To achieve high resource utilization for multi-issue DSPs, production compiler commonly includes variants of iterative modulo scheduling algorithm. However, excessive cyclic data dependences, which exist in communication and media processing loops, unduly restrict modulo scheduling freedom. As a result, replicated functional units in multi-issue DSPs are often under-utilized. To address this resource under-utilization problem, our paper describes a novel compiler preprocessing strategy for effective modulo scheduling. The preprocessing strategy proposed capitalizes on two new transformations, which are referred to as cloning and dismantling. Our preprocessing strategy has been validated by an implementation for StarCore SC140 DSP compiler.