• Journal of the Korean Society for Precision Engineering
• /
• v.31 no.4
• /
• pp.287-295
• /
• 2014

Smart manufacturing (SM) considered as a new trend of modern manufacturing helps to meet objectives associated with the productivity, quality, cost and competiveness. It is characterized by decentralized, distributed, networked compositions of autonomous systems. The model of SM is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee's foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To prove this concept, a cloud machining system is considered as research object in which internet of things and cloud computing are used to integrate, organize and allocate the machining resources. Artificial life tools are used for cooperation among autonomous elements in the cloud machining system.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.10 no.3
• /
• pp.119-127
• /
• 2015

In the IoT(Internet of Things) environment, methods that user can access sensor node directly to collect sensing data or manage sensor in a gateway have a limitations. To solve this problem, cloud based sensor network architectures are proposed. In this paper, we proposed CoAP based IoT architecture that a lightweight gateway is used for data gathering instead of using a heavy traditional one and users can request sensing data through IoT applications running in the cloud environment and analyze signaling message cost. By doing so, our system can reduce message cost compared to the traditional gateway based system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5634-5653
• /
• 2018

Internet of things (IoT) is based on a global dynamic information network with cloud services where a great number of devices (things) exchange data to provide added-value services and products. There are several commercial and open source IoT platforms available in the market to connect devices to internet; however, they have cost and operational constraints that make them not suitable for academic projects. In this work, an IoT platform, known as Novus-io, is introduced in order to support academic projects for undergraduate students. With this platform and proper training, undergraduate students from different majors (not only from information technology and electronics) are capable to upgrade their school projects with IoT functionalities. The objective of this approach is to provide to any undergraduate student skills and knowledge on IoT, so they will be prepared, in their imminent step toward professionalism, to understand the relevance of digital services in today's world.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.3
• /
• pp.49-55
• /
• 2019

An open office or a shared office is emerging as the emphasis on the collaborative and communicative work environments is increasing. In the past, the user maintained the space, but the maintenance of indoor space became difficult because there is no fixed user. Indoor space information can be collected using the ICBM framework system. The facility management can achieve this with data. Therefore, this study proposed a framework based on ICBM (Internet of Things, Cloud, Big Data, and Mobile) for verifying the possibility of a smart facility management system for indoor space. IoT (Internet of Things) technology was used to measure the indoor temperature, humidity, occupancy, and brightness continuously, and provided the data to Web API via WiFi. Data acquired automatically via IoT, existing maintenance data, and spatial information were integrated through the Cloud. Big data collected by sensors were processed as meaningful spatial information for maintenance. Indoor space information and maintenance information can be delivered to the manager through the mobile. Based on the collected data, room occupancy recognition is limited due to a range of ultrasonic wave sensors. On the other hand, brightness represents the space conditions. The difference between lighting on/off, weekday and weekend can be shown. The temperature data and the relative humidity data were collected steadily to evaluate the comfort.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.188-191
• /
• 2013

인간과 사물, 서비스 세 가지 분산된 환경 요소에 대해 인간의 명시적 개입 없이 상호 협력적으로 센싱, 네트워킹, 정보 처리 등 지능적 관계를 형성하는 사물 공간 연결망인 IoT(Internet of Things)에서 센싱된 정보를 처리하고 서비스하기 위한 환경을 적시적소에 배치(Depolyment) 하기 위하여 클라우드 서비스와의 연동방법에 대해 본 논문에서 연구하였다. Public Cloud환경에서 Hadoop Cluster를 구성하여 IoT 서비스에 적용할 수 있는 통합 환경을 구축하면 폭발적으로 증가하는 IoT 데이터를 저장하고 빠른 시간안에 이를 효과적으로 처리 및 분석하기 위한 시스템 구축이 가능하며 분산 저장소에 저장된 데이터를 분석하고 의미있는 지식을 발견하여 새로운 비즈니스 모델 창출에 기여할 수 있다. 본 논문에서 Public Cloud 환경에서 Hadoop Clouster를 구성하여 IoT에서 생성되는 데이터를 효과적으로 처리하고 분석할 수 있는 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.507-510
• /
• 2013

Cloud computing is an emerging technology, which allows the user to fulfill his needs by outsourcing the resources. With the passage of time, cloud computing has become an essential part of our lives. But it still requires some sort of standardization, specially in terms of user's trust, privacy, and security related things. This study presents different types of cloud computing services and their working domains along with some key virtualization related issues that are encountered by the cloud service provider as well as the user. Those key issues, related with virtual network are discussed in this paper. This study provides a basis to work further on those issues, so that the key concerns are addressed as soon as possible and cloud computing could become standardized and more prevalent.

• Journal of Digital Convergence
• /
• v.14 no.2
• /
• pp.235-243
• /
• 2016

Legacy data centers are transforming toward cloud data centers according to the advance of mobile and Internet of Things technology, processing of big data, and development of cloud computing technology. The goal of cloud data centers is to efficiently manage energy and facility, and to rapidly provide service demands to users by operating virtualized ICT(Information and Communication Technology) resources. Accordingly, it requires to configure and operate networks for efficiently providing virtualized ICT resources. This paper analyzes networking technologies suitable for cloud data centers and presents ways to efficiently operate the data center.

• Journal of Internet of Things and Convergence
• /
• v.8 no.6
• /
• pp.85-92
• /
• 2022

Demand for big data analysis and AI developers is increasing, but there is a lack of an education base to supply them. In this paper, by developing a cloud-based artificial intelligence education platform, the goal was to establish an environment in which practical practical training can be efficiently learned at low cost at educational institutions and IT companies. The development of the education platform was carried out by planning scenarios for each user, architecture design, screen design, implementation of development functions, and hardware construction. This training platform consists of a containerized workload, service management platform, lecture and development platform for instructors and students, and secured cloud stability through real-time alarm system and age test, CI/CD development environment, and reliability through docker image distribution. The development of this education platform is expected to expand opportunities to enter new businesses in the education field and contribute to fostering working-level human resources in the AI and big data fields.

• Journal of Internet of Things and Convergence
• /
• v.7 no.1
• /
• pp.9-19
• /
• 2021

The data mining design incorporated with big data based cloud computing system is investigated for the nuclear terrorism prevention where the conventional physical protection system (PPS) is modified. The networking of terror related bodies is modeled by simulation study for nuclear forensic incidents. It is needed for the government to detect the terrorism and any attempts to attack to innocent people without illegal tapping. Although the mathematical algorithm of the study can't give the exact result of the terror incident, the potential possibility could be obtained by the simulations. The result shows the shape oscillation by time. In addition, the integration of the frequency of each value can show the degree of the transitions of the results. The value increases to -2.61741 in 63.125th hour. So, the terror possibility is highest in later time.

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