• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.129-149
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• 1993

The high level of activity in the development and maintenance of computer software makes the scheduling of software projects an importnat factor in reducing operating costs and increasing competitiveness. Software activity is labor intensive. Scheduling management of hours of software work is complicated by ther interdependencies between the segments of work, and the uncertainties of the work itself. This paper discusses issues of scheduling in software engineering management, and presents a modular decomposition model for software project scheduling, taking advantage of the facility for decomposition of a software project into relatively independent work segment modules. Modular decomposition makes it possible to treat scheduling as clustering and sequencing in the context of integer programming. A heuristic algorithm for the model is presented with some computational experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.539-545
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• 2010

Through the AUTOSAR methodology, the embedded software shall become more flexible, reusable, maintainable than ever. However, it is not mentioned about specific timing constraints of software components in AUTOSAR. There are a few basic principles for mapping runnable entities. At this point, AUTOSAR software design with optimal scheduling method is one of the enabling technologies in vehicle embedded system. This paper presents an approach based on mapping runnable entities and task scheduling design method for EPS (Electric Power Steering) software components, based on AUTOSAR. In addition, the experimental results of concurrent simulation show that the proposed scheduling technique and timing synchronization in the software component design can achieve the improved torque ripple performance and it well suited for EPS application software.

• Korean Management Science Review
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• v.23 no.2
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• pp.187-198
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• 2006

Efficient scheduling for software development is a major concern for software engineers. Industries simultaneously try to perform a variety of projects with the limited resources on schedule. A way to overcome the limitation of resources is sharing of the resources through the projects. This study discusses the matrix organization for software development. A scheduling for matrix organization is a special case of project management problem. The ultimate goal of scheduling problem in this study is to minimize the overall duration of the multiple projects. A genetic algorithm is presented to solve the scheduling problem of the matrix organization and is substantiated with numerical results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.67-70
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• 2006

Efficient scheduling for software development is a major concern for software engineers. A industry simultaneously performs a variety of projects with the limited resources without overdue. A way to overcome the limitation of resources is sharing of the resources through the projects. This study discusses the matrix organization for software development. A scheduling for matrix organization is a special case of project management problem. The ultimate goal of scheduling problem in this study is to reduce the overall duration of the multiple projects. A genetic algorithm is presented to solve the scheduling problem of the matrix organization and is substantiated with numerical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5013-5034
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• 2019

In the Peer-to-Peer (P2P) streaming systems, peers randomly form a network overlay to share video resources with a data scheduling scheme. A data scheduling scheme can have a great impact on system performance, which should achieve two optimal objectives at the same time ideally. The two optimization objectives are to improve the perceived video quality and maximize the network throughput, respectively. Maximizing network throughput means improving the utilization of peer's upload bandwidth. However, maximizing network throughput will result in a reduction in the perceived video quality, and vice versa. Therefore, to achieve the above two objects simultaneously, we proposed a new data scheduling scheme based on multi-objective particle swarm optimization data scheduling scheme, called MOPSO-DS scheme. To design the MOPSO-DS scheme, we first formulated the data scheduling optimization problem as a multi-objective optimization problem. Then, a multi-objective particle swarm optimization algorithm is proposed by encoding the neighbors of peers as the position vector of the particles. Through extensive simulations, we demonstrated the MOPSO-DS scheme could improve the system performance effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.1-17
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• 2016

The separated management and operation of commercial IP/optical multilayer networks makes network operators look for a unified control plane (UCP) to reduce their capital and operational expenditure. Software-defined networking (SDN) provides a central control plane with a programmable mechanism, regarded as a promising UCP for future optical networks. The general control and scheduling mechanism in SDN-based optical burst switching (OBS) networks is insufficient so the controller has to process a large number of messages per second, resulting in low network resource utilization. In view of this, this paper presents the burst-flow scheduling mechanism (BFSM) with a proposed scheduling algorithm considering channel usage. The simulation results show that, compared with the general control and scheduling mechanism, BFSM provides higher resource utilization and controller performance for the SDN-based OBS network in terms of burst loss rate, the number of messages to which the controller responds, and the average latency of the controller to process a message.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2824-2837
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• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.391-396
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• 2013

As the construction environment has been changing all the times, the techniques for managing the construction projects have been improved accordingly. The schedule management technique, one of the construction management tools, has been evolved as well in order to be adaptable to new construction environment. Most of newly proposed scheduling techniques have been based on the Critical Path Method (CPM) that was proposed in 1956. The CPM is classified into two categories, Arrow Diagramming Method (ADM) and Precedence Diagramming Method (PDM). ADM is so good in the visual format but it cannot express the overlapping relationships between two consecutive activities. On the other hand, PDM can express the overlapping relationships but it is unsatisfactory in the visual format. Recently, as the construction environment becomes more complex and the role of schedule management becomes more and more important, the overlapping expression becomes one of critical factors for scheduling as well. Most of construction project participants prefer more comfortable visual format, however, the scheduling software based on the PDM cannot satisfy their basic requirement. Beeliner, new scheduling software based on the Beeline Diagramming Method (BDM) that was proposed in 2010, was developed in 2012, it can express more flexible overlapping relationships and has superior visual format as well. This paper presents major features and applications of Beeliner, and makes construction professionals understand new scheduling concept and its applications.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.4
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• pp.260-273
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• 2007

The wireless sensor network (WSN) nodes are required to operate for several months with the limited system resource such as memory and power. The hardware platform of WSN has 128Kbyte program memory and 8Kbytes data memory. Also, WSN node is required to operate for several months with the two AA size batteries. The MAC, Network protocol, and small application must be operated in this WSN platform. We look around the problem of memory and power for WSN requirements. Then, we propose a new computing model of system software for WSN node. It is the Atomic Object Model (AOM) with Dual Priority Scheduling. For the verification of model, we design and implement IEEE 802.15.4 MAC protocol with the proposed model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.53-69
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• 1991

This paper is concerned with software developments for scheduling and sequencing of FMS. The scheduling algorithms are developed for 3 types of FMS:single machine type FMS, flowshop type FMS. assembly line type FMS. For the single machine type FMS. full enumeration algorithm is used. For the flowshop type FMS heuristic algorithms are developed. For the assembly type FMS the exsisting PERT/CPM algorithm is applied. Numerical examples are presented for illustration of each algorithm. Each soft ware program list are attached as appendices.