This page has only limited features, please log in for full access.
Recently, with the rapid growth of information technology (IT), diverse studies have been carried out for the grafting of devices based on the Internet of Things (IoT) for use in real life. With certain sensor functions and downsized mobile devices, IoT devices have improved users’ work efficiency, ease of mobility, and convenience in terms of not being restricted by location. In the case of IoT devices as such, computing offloading is regarded to be very important to overcome issues of limited computing power and storage capacity and the limitations of built-in batteries. For the computing offloading of IoT devices, diverse job allocation techniques considering performance resources have been studied. However, since only the static performance, dynamic performance, or performance and battery size of IoT devices are considered in job allocation, job reallocation problems are caused by battery consumption due to the use of patterns in which users execute certain applications. In this paper, an adaptive job allocation scheduler (AJAS) that adaptively redistributes the jobs allocated to IoT devices based on user behavior patterns is proposed. The AJAS allocates jobs using the dynamic performance resources and battery consumption rates of diverse IoT devices. In addition, the AJAS measures the battery consumption rate of user applications executed in the IoT device to assess whether the allocated jobs can be processed. The AJAS identifies IoT devices that cannot process jobs and minimizes states in which allocated jobs cannot be processed due to battery exhaustion and delay time due to job reallocation. For verification, an AJAS is designed and implemented to show that the AJAS improves device availability for job processing.
Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Adaptive job allocation scheduler based on usage pattern for computing offloading of IoT. Future Generation Computer Systems 2019, 98, 18 -24.
AMA StyleHyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Adaptive job allocation scheduler based on usage pattern for computing offloading of IoT. Future Generation Computer Systems. 2019; 98 ():18-24.
Chicago/Turabian StyleHyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2019. "Adaptive job allocation scheduler based on usage pattern for computing offloading of IoT." Future Generation Computer Systems 98, no. : 18-24.
STVF (Novel scheme for transcoding video file of multiple file formats) is a video sharing system novel scheme based on the parallel computing framework and Intra-cloud environment. The target user is community user within a certain scale. While using a small-scale server group, a parallel processing framework and an improved task assignment algorithm are utilized to realize high-speed video transcoding using ffmpeg, and different-definition videos are generated at high speed too. Dynamically analyze the size of the task to select the number of task processing servers to achieve STVF’s higher scalability. And through these operations so that the user can smoothly play suitable resolution in different smart machines format.
Seungchul Kim; Mu He; Hyun-Woo Kim; Young-Sik Jeong. Rapid Parallel Transcoding Scheme for Providing Multiple-Format of a Single Multimedia. Lecture Notes in Electrical Engineering 2018, 855 -861.
AMA StyleSeungchul Kim, Mu He, Hyun-Woo Kim, Young-Sik Jeong. Rapid Parallel Transcoding Scheme for Providing Multiple-Format of a Single Multimedia. Lecture Notes in Electrical Engineering. 2018; ():855-861.
Chicago/Turabian StyleSeungchul Kim; Mu He; Hyun-Woo Kim; Young-Sik Jeong. 2018. "Rapid Parallel Transcoding Scheme for Providing Multiple-Format of a Single Multimedia." Lecture Notes in Electrical Engineering , no. : 855-861.
The recent advances in information technology for mobile devices have increased the work efficiency of users, the mobility of compact mobile devices, and the convenience of location independence. However, mobile devices have limited computing power and storage capacity, so mobile cloud computing is being researched to overcome these limitations in mobile devices. Mobile cloud computing is divided into two methods: the use of external cloud services and the use of mobile resource management without a cloud server (MRM), which integrates the computing and storage resources of nearby mobile devices. Because mobile devices can freely participate in MRM, it is critical to have authentication technology to determine the correctness of information regarding resources. Conventional technologies require strong authentication techniques because they have vulnerabilities that can easily be tampered with via man-in-the-middle (MITM) attacks. This paper proposes the Secure Authentication Management human-centric Scheme (SAMS) to authenticate mobile devices using blockchain for trusting resource information in the mobile devices that are participating in the MRM resource pool. The SAMS forms a blockchain based on the resource information of the subordinate client nodes around the master node in the MRM. Devices in the MRM that have not been authorized through the SAMS cannot access or falsify data. To verify the SAMS for application with MRM, it was tested for data falsification by a malicious user accessing the SAMS, and the results show that data falsification is impossible.
Hyun-Woo Kim; Young-Sik Jeong. Secure Authentication-Management human-centric Scheme for trusting personal resource information on mobile cloud computing with blockchain. Human-centric Computing and Information Sciences 2018, 8, 11 .
AMA StyleHyun-Woo Kim, Young-Sik Jeong. Secure Authentication-Management human-centric Scheme for trusting personal resource information on mobile cloud computing with blockchain. Human-centric Computing and Information Sciences. 2018; 8 (1):11.
Chicago/Turabian StyleHyun-Woo Kim; Young-Sik Jeong. 2018. "Secure Authentication-Management human-centric Scheme for trusting personal resource information on mobile cloud computing with blockchain." Human-centric Computing and Information Sciences 8, no. 1: 11.
The rapid development of ICT has led to the wide popularity of mobile devices, which have helped improve business efficiency and enabled simple mobility as small and light devices and convenience of being available anytime, anywhere for cyber-physical-social big data. There are many ongoing studies on mobile cloud computing (MCC) to overcome the limited computing capability and storage capacity and internal battery limitation by taking advantage of the popularity of mobile devices for the processing cyber-physical-social big data. MCC consists of service-oriented architecture, agent-client architecture, and collaborative architecture, with job splitting and allocation as the critical factor. As such, job allocation techniques considering the performance resources of mobile devices have been studied. Note, however, that there is a problem of job reallocation due to continuous battery consumption since the studies consider only the performance resources of mobile devices at the time of job allocation or take into account the performance resources and remaining battery power only. This paper proposes the job allocation mechanism (JAM) for battery consumption minimization of cyber-physical-social big data processing in MCC, which continuously reflects the battery consumption rate to process jobs with mobile devices only without an external cloud server in a collaborative architecture-based MCC environment. JAM allocates jobs considering the periodic measurement of battery consumption and surplus resource to minimize the problem of job reallocation due to battery rundown of the mobile devices. This research designs and implements a system for verifying JAM and demonstrated that the job processing speed increased in an MCC environment for cyber-physical-social big data.
Gangman Yi; Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Job Allocation Mechanism for Battery Consumption Minimization of Cyber-Physical-Social Big Data Processing Based on Mobile Cloud Computing. IEEE Access 2018, 6, 21769 -21777.
AMA StyleGangman Yi, Hyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Job Allocation Mechanism for Battery Consumption Minimization of Cyber-Physical-Social Big Data Processing Based on Mobile Cloud Computing. IEEE Access. 2018; 6 ():21769-21777.
Chicago/Turabian StyleGangman Yi; Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2018. "Job Allocation Mechanism for Battery Consumption Minimization of Cyber-Physical-Social Big Data Processing Based on Mobile Cloud Computing." IEEE Access 6, no. : 21769-21777.
Human-intelligence workflow management (HIWM) is proposed as a means of dynamically distributing and processing storage work and calculating operations for fast augmented reality (AR) service provision on diverse smart mobile devices based on human behavior to apply the next generation web environments. In HIWM, pre-processing is performed to minimize service response time according to the definition of metadata and user requests for AR services. Basically, to process big data for AR services, a dynamic job distribution scheme is proposed based on the computing capacity of desktops constituting the cloud infrastructures. For final AR services by HIWM, the results of the evaluation of the performance of HIWM in relation to big data processing time are presented. The results show that processing time is 40.56% less than that of the existed methods in proportion to AR service requests.
Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Human-intelligence workflow management for the big data of augmented reality on cloud infrastructure. Neurocomputing 2017, 279, 19 -26.
AMA StyleHyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Human-intelligence workflow management for the big data of augmented reality on cloud infrastructure. Neurocomputing. 2017; 279 ():19-26.
Chicago/Turabian StyleHyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2017. "Human-intelligence workflow management for the big data of augmented reality on cloud infrastructure." Neurocomputing 279, no. : 19-26.
With the increasing utilization of cloud computing and cyber–physical systems (CPSs), which allow the expression and control of the real world in a virtual environment, researches related to these subjects are being actively conducted in various areas. The convergence of CPS and cloud computing is being researched primarily because of their high availability, high-performance computing, and high-throughput computing. CPS consisting of numerous sensors, actuators, controllers, and control managers requires optimized modeling, simulation, and resource management technologies to integrate physical elements with computing elements for processing, which will provide high-throughput computing and high-reliability services. But the main problem of sensor resource management is that information of sensors cannot be approached in case that a sensor failure occurs at the sensing target area. Thus, various researches have been done to reconstruct the topology, but the self-topology configuration of sensors causes unnecessary events and battery consumption from various sensor nodes. In this paper, adaptive resource management (ARM) is proposed to 1) minimize information loss due to the irregular lifespan of resources, such as sensors and actuators; and 2) quickly respond to any problems. ARM uses the many-core of GPU to speed up fault handling, parallelizes the sensor information to select an alternate node of the fault node, and presents the performance evaluation results of the execution time of CPU and GPU.
Hyun-Woo Kim; Gangman Yi; Jong Hyuk Park; Young-Sik Jeong. Adaptive resource management using many-core processing for fault tolerance based on cyber–physical cloud systems. Future Generation Computer Systems 2017, 105, 884 -893.
AMA StyleHyun-Woo Kim, Gangman Yi, Jong Hyuk Park, Young-Sik Jeong. Adaptive resource management using many-core processing for fault tolerance based on cyber–physical cloud systems. Future Generation Computer Systems. 2017; 105 ():884-893.
Chicago/Turabian StyleHyun-Woo Kim; Gangman Yi; Jong Hyuk Park; Young-Sik Jeong. 2017. "Adaptive resource management using many-core processing for fault tolerance based on cyber–physical cloud systems." Future Generation Computer Systems 105, no. : 884-893.
In recent years, the use of ubiquitous computing has increased continuously so that studies on ubiquitous computing have been conducted in various life fields. Ubiquitous computing provides any services anywhere and anytime through networks conveniently to improve the quality of life of users. Ubiquitous computing is constructed via a variety of invisible sensors, networks, and computing environments. For multi-purpose sensors, deployment of the topology and topology lifetime are very important depending on wired or wireless sensors. Uneven energy consumption due to integrated routing sensors according to topology deployment types is a factor that degrades the quality of service (QoS) about user convenience services and lifetime of total topology. As a result, a number of studies on maximization of topology lifetime have been conducted. However, previous studies focused on deployment environments and limited sensors so that they cannot be deployed to real sites. Therefore, this study proposes an adaptive power management scheme (APMS) that manages sensor power adaptively according to deployment environments to maximize topology lifetime. The APMS maximizes topology lifetime by changing routing paths according to lifetime log to manage sensor power. Furthermore, active responses for optimum topology can be achieved by deploying sensors via simulation prior to sensors deployed to the real environments by users.
Boo-Kwang Park; Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Adaptive power management scheme using many-core for maximizing network topology lifetime based on ubiquitous computing. Journal of Systems Architecture 2017, 77, 63 -71.
AMA StyleBoo-Kwang Park, Hyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Adaptive power management scheme using many-core for maximizing network topology lifetime based on ubiquitous computing. Journal of Systems Architecture. 2017; 77 ():63-71.
Chicago/Turabian StyleBoo-Kwang Park; Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2017. "Adaptive power management scheme using many-core for maximizing network topology lifetime based on ubiquitous computing." Journal of Systems Architecture 77, no. : 63-71.
Infrastructure as a service with desktops (DIaaS) based on the extensible mark-up language (XML) is herein proposed to utilize surplus resources. DIaaS is a traditional surplus-resource integrated management technology. It is designed to provide fast work distribution and computing services based on user service requests as well as storage services through desktop-based distributed computing and storage resource integration. DIaaS includes a nondisruptive resource service and an auto-scalable scheme to enhance the availability and scalability of intra-cloud computing resources. A performance evaluation of the proposed scheme measured the clustering performance time for surplus resource utilization. The results showed improvement in computing and storage services in a connection of at least two computers compared to the traditional method for high-availability measurement of nondisruptive services. Furthermore, an artificial server error environment was used to create a clustering delay for computing and storage services and for nondisruptive services. It was compared to the Hadoop distributed file system (HDFS).
Hyun-Woo Kim; Jaekyung Han; Jong Hyuk Park; Young-Sik Jeong. DIaaS: Resource Management System for the Intra-Cloud with On-Premise Desktops. Symmetry 2017, 9, 8 .
AMA StyleHyun-Woo Kim, Jaekyung Han, Jong Hyuk Park, Young-Sik Jeong. DIaaS: Resource Management System for the Intra-Cloud with On-Premise Desktops. Symmetry. 2017; 9 (1):8.
Chicago/Turabian StyleHyun-Woo Kim; Jaekyung Han; Jong Hyuk Park; Young-Sik Jeong. 2017. "DIaaS: Resource Management System for the Intra-Cloud with On-Premise Desktops." Symmetry 9, no. 1: 8.
Following the progressive development of IT technology, on-premise IT resources have been shifted to cloud computing environments. The principle reason for this change in IT resource-composing environments is that cloud computing services allow IT resources to be used as and when necessary, which means without buying hardware equipment. For this reason, studies on diverse aspects are being conducted for better security, rapidity, availability, reliability, and elasticity of cloud computing. Among the virtualization technologies that are basic for cloud computing, desktop storage virtualization (DSV) is composed of distributed legacy desktop personal computers. In DSV environments, clustering by unavailable state time and auto-scaling for storage provision as requested by users are considered very important. In addition, deferred processing for analysis of desktop PC performance states in DSV environments to select an appropriate desktop PC is directly connected to the quality of service (QoS). Although diverse algorithms and schemes for clustering and auto-scaling have been developed to this end, they have limited performance or have been made without considering DSV environments. Consequently, large amounts of deferred processing time are required. In the present paper, an efficient auto-scaling scheme (EAS) is proposed that minimizes deferred processing time in Internet of Things (IoT) environments by using many-cores of the GPU for clustering and auto-scaling in DSV environments. The EAS provides higher QoS to storage users compared to the CPU by mapping the information of numerous distributed desktop PCs on individual threads of the GPU and processing the information in parallel.
Hyun-Woo Kim; Young-Sik Jeong. Efficient auto-scaling scheme for rapid storage service using many-core of desktop storage virtualization based on IoT. Neurocomputing 2016, 209, 67 -74.
AMA StyleHyun-Woo Kim, Young-Sik Jeong. Efficient auto-scaling scheme for rapid storage service using many-core of desktop storage virtualization based on IoT. Neurocomputing. 2016; 209 ():67-74.
Chicago/Turabian StyleHyun-Woo Kim; Young-Sik Jeong. 2016. "Efficient auto-scaling scheme for rapid storage service using many-core of desktop storage virtualization based on IoT." Neurocomputing 209, no. : 67-74.
Character recognition schemes on information and communication technology devices, such as smart phones that use touchscreens, are currently used daily. In character recognition, users complete a desired sentence with predetermined character allocation by pushing buttons or using touch typing. Existing character recognition requires pushing many buttons for sentence completion. Smart phones, representative smart devices with diverse built-in sensors, have improved convenience by minimizing the number of pushes required for sentence completion based on application research using the drag function of the touchscreen. Despite the development of many touch interfaces, scarce character recognition schemes exist that account for those with disabilities or for unspecified situations, such as users wearing gloves. This paper proposes the Korean Grapheme Immersive Recognition Scheme (KGIRS), which uses gyro and acceleration sensors and was developed for smart devices with diverse built-in sensors. The KGIRS recognizes user gestures through gyro and acceleration sensors and performs Korean grapheme recognition by mapping a character recognition table. The KGIRS could be an excellent solution for the inconvenience of many existing push-type character input schemes by providing character recognition without restraint, regardless of the user’s condition, even for touch incapability. Moreover, it can be used when general users have trouble typing characters using a push-type scheme.
Yoon-A Heo; Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Korean grapheme recognition immersive scheme with gesture on smartphone. Multimedia Tools and Applications 2016, 1 -16.
AMA StyleYoon-A Heo, Hyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Korean grapheme recognition immersive scheme with gesture on smartphone. Multimedia Tools and Applications. 2016; ():1-16.
Chicago/Turabian StyleYoon-A Heo; Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2016. "Korean grapheme recognition immersive scheme with gesture on smartphone." Multimedia Tools and Applications , no. : 1-16.
Recent advancements in Information Technology (IT) have sparked the creation of numerous and diverse types of devices and services. Manual data collection measurement methods have been automated through the use of various wireless or wired sensors. Single sensor devices are included in smart devices such as smartphones. Data transmission is critical for big data collected from sensor nodes, such as Mobile Sensor Nodes (MSNs), where sensors move dynamically according to sensor mobility, or Fixed Sensor Nodes (FSNs), where sensor locations are decided by the users. False data transfer processing of big data results in topology lifespan reduction and data transfer delays. Hence, a variety of simulators and diverse load-balancing algorithms have been developed as protocol verification tools for topology lifespan maximization and effective data transfer processing. However, those previously developed simulators have limited functions, such as an event function for a specific sensor or a battery consumption rate test for sensor deployment. Moreover, since the previous load-balancing algorithms consider only the general traffic distribution and the number of connected nodes without considering the current topology condition, the sustainable load-balancing technique that takes into account the battery consumption rate of the dispersed sensor nodes is required. Therefore, this paper proposes the Sustainable Load-balancing Scheme (SLS), which maximizes the overall topology lifespan through effective and sustainable load-balancing of data transfer among the sensors. SLS is capable of maintaining an effective topology as it considers both the battery consumption rate of the sensors and the data transfer delay.
Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Sustainable Load-Balancing Scheme for Inter-Sensor Convergence Processing of Routing Cooperation Topology. Sustainability 2016, 8, 436 .
AMA StyleHyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Sustainable Load-Balancing Scheme for Inter-Sensor Convergence Processing of Routing Cooperation Topology. Sustainability. 2016; 8 (5):436.
Chicago/Turabian StyleHyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2016. "Sustainable Load-Balancing Scheme for Inter-Sensor Convergence Processing of Routing Cooperation Topology." Sustainability 8, no. 5: 436.
In recent years, as information technology (IT) has advanced rapidly, multimedia smart devices have been designed to provide a variety of services with which users can interact using touch screens. A smart phone is among the typical smart devices and it has provided simple mobility and a convenient interface via touch screens, as well as enabling desktop personal computer (PC) operations thanks to their high performance and miniaturization. In pace with this rapid advancement, a variety of input schemes has also been developed to allow users to enter text conveniently and rapidly. However, despite the development of such various input schemes, learning delay time and typos occur frequently. Furthermore, as touch screen-based multimedia smart devices employ finger-based text inputs, disabled persons or individuals who cannot use their fingers freely may have difficulties. In this paper, a virtual keyboard using a Gyro-Accelerometer sensor (VGA), which is an efficient text input keypad using an accelerometer sensor and gyro sensor, is proposed. The VGA can input text using a gyro sensor and accelerometer sensor embedded in multimedia smart devices. Through the VGA, users whose fingers are not freely available can enter texts easily and comfortably.
Hyun-Woo Kim; Boo-Kwang Park; HwiRim Byun; Yoon-A Heo; Young-Sik Jeong. Efficient Character Input Scheme Based on Gyro-Accelerometer Sensor for NUI. Lecture Notes in Electrical Engineering 2015, 101 -107.
AMA StyleHyun-Woo Kim, Boo-Kwang Park, HwiRim Byun, Yoon-A Heo, Young-Sik Jeong. Efficient Character Input Scheme Based on Gyro-Accelerometer Sensor for NUI. Lecture Notes in Electrical Engineering. 2015; ():101-107.
Chicago/Turabian StyleHyun-Woo Kim; Boo-Kwang Park; HwiRim Byun; Yoon-A Heo; Young-Sik Jeong. 2015. "Efficient Character Input Scheme Based on Gyro-Accelerometer Sensor for NUI." Lecture Notes in Electrical Engineering , no. : 101-107.
Recently, research on cloud-integrated Internet of Things where an Internet of Things (IoT) is converged with a cloud environment has been actively pursued. An IoT operates through interaction among many composition elements, such as actuators and sensors. At present, IoTs are used in diverse areas (for example, traffic control and safety, energy savings, process control, communications systems, distributed robots, and other important applications). In daily life, IoTs should provide services of high reliability corresponding with various physical elements. In order to guarantee highly reliable IoT services, optimized modeling, simulation, and resource management technologies integrating physical elements and computing elements are required. For such reasons, many systems are being developed where autonomic computing technologies are applied that sense any internal errors or external environmental changes occurring during system operation and where systems adapt or evolve themselves. In an IoT environment composed of large-scale nodes, autonomic computing requires a high processing amount and efficient storage processing of computing in order to process sensing data efficiently. In addition, due to the heterogeneous composition of IoT environments, separate middleware is required to share collected information. Accordingly, this paper proposed an efficient resource management scheme (ERMS) that efficiently manages IoT resources using cloud infrastructure satisfying the high availability, expansion, and high processing amount requirements. ERMS provides a XML-based standard sensing data storage scheme in order to store and process heterogeneous IoT sensing data in the cloud infrastructure. In addition, ERMS provides classification techniques to efficiently store and process distributed IoT data.
Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Efficient Resource Management Scheme for Storage Processing in Cloud Infrastructure with Internet of Things. Wireless Personal Communications 2015, 91, 1635 -1651.
AMA StyleHyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Efficient Resource Management Scheme for Storage Processing in Cloud Infrastructure with Internet of Things. Wireless Personal Communications. 2015; 91 (4):1635-1651.
Chicago/Turabian StyleHyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2015. "Efficient Resource Management Scheme for Storage Processing in Cloud Infrastructure with Internet of Things." Wireless Personal Communications 91, no. 4: 1635-1651.
WSN (wireless sensor network) technology came to become fairly activated and as WSN is a part of the world's environment, research on it is considered important. WSN automated life and work; miniaturized wireless sensor nodes enable observational measurement in regions where access by humans is difficult or periodic sensing data is necessary. Thousands of such sensor nodes are needed. However, when they are wrongly placed in an observed area, sensor node batteries may run out fast or disconnection may result, which may trigger the loss of sensing data by sensor nodes and create an enormous cost. Moreover, even though sensor nodes have the same function, there are different kinds; therefore, it is difficult to select and place optimal sensor nodes. Accordingly, this paper proposed the WS3L (wireless sensor simulator using sensor log) as a simulator aimed at the composition of a more efficient sensing infrastructure and problem analysis for Internet of Things. This WS3L utilized sensor log data for precise prediction, not merely execution depending on simulators developed earlier. This WS3L read sensor log data of the observed area from the user and provided various analysis functions to examine problems.
Young-Sik Jeong; Hyun-Woo Kim; Neil Y. Yen; Jong Hyuk Park. Multi-WSN Simulator with Log Data for Efficient Sensing on Internet of Things. International Journal of Distributed Sensor Networks 2015, 11, 1 .
AMA StyleYoung-Sik Jeong, Hyun-Woo Kim, Neil Y. Yen, Jong Hyuk Park. Multi-WSN Simulator with Log Data for Efficient Sensing on Internet of Things. International Journal of Distributed Sensor Networks. 2015; 11 (7):1.
Chicago/Turabian StyleYoung-Sik Jeong; Hyun-Woo Kim; Neil Y. Yen; Jong Hyuk Park. 2015. "Multi-WSN Simulator with Log Data for Efficient Sensing on Internet of Things." International Journal of Distributed Sensor Networks 11, no. 7: 1.
Following the rapid growth of ubiquitous computing, many jobs that were previously manual have now been automated. This automation has increased the amount of time available for leisure; diverse services are now being developed for this leisure time. In addition, the development of small and portable devices like smartphones, diverse Internet services can be used regardless of time and place. Studies regarding diverse virtualization are currently in progress. These studies aim to determine ways to efficiently store and process the big data generated by the multitude of devices and services in use. One topic of such studies is desktop storage virtualization, which integrates distributed desktop resources and provides these resources to users to integrate into distributed legacy desktops via virtualization. In the case of desktop storage virtualization, high availability of virtualization is necessary and important for providing reliability to users. Studies regarding hierarchical structures and resource integration are currently in progress. These studies aim to create efficient data distribution and storage for distributed desktops based on resource integration environments. However, studies regarding efficient responses to server faults occurring in desktop-based resource integration environments have been insufficient. This paper proposes a mechanism for the sustainable operation of desktop storage (SODS) for high operational availability. It allows for the easy addition and removal of desktops in desktop-based integration environments. It also activates alternative servers when a fault occurs within a system.
Hyun-Woo Kim; Jong Hyuk Park; Duinkhorjav Majigsuren; Young-Sik Jeong. Efficient Sustainable Operation Mechanism of Distributed Desktop Integration Storage Based on Virtualization with Ubiquitous Computing. Sustainability 2015, 7, 7568 -7580.
AMA StyleHyun-Woo Kim, Jong Hyuk Park, Duinkhorjav Majigsuren, Young-Sik Jeong. Efficient Sustainable Operation Mechanism of Distributed Desktop Integration Storage Based on Virtualization with Ubiquitous Computing. Sustainability. 2015; 7 (6):7568-7580.
Chicago/Turabian StyleHyun-Woo Kim; Jong Hyuk Park; Duinkhorjav Majigsuren; Young-Sik Jeong. 2015. "Efficient Sustainable Operation Mechanism of Distributed Desktop Integration Storage Based on Virtualization with Ubiquitous Computing." Sustainability 7, no. 6: 7568-7580.
Recently wireless sensor networks have been used as the technology that is actively grafted onto industries and daily living. Sensors should have built-in routing functions and basic sensing functions for the self-configuration of topologies. The number of sensors necessary for using them in an actual observation ranges from tens to hundreds or thousands. When theses sensors are wrongly placed in an observation region, they can quickly run out of batteries or be disconnected. These incidents may result in huge losses in terms of sensing data from numerous sensors and their costs. Therefore a number of simulators have been developed as tools for effective design and verification before the actual arrangement of sensors. While a number of simulators have been developed, simulation results can be fairly limited and the execution speed can be markedly slow depending on the function of each simulator. To improve the performance of existing simulators, this paper aimed to develop a parallel processing simulator for separate sensor (P2S3) that enables users to selectively use the GPU mode. It enables parallel and independent operations by matching GPU with many cores in order to resolve the slowdown of the execution speed when numerous sensor nodes are used for simulations. Also, P2S3 include the analyzed of sensor nodes with log data and visualization. The P2S3 supports the GPU mode in an environment that allows the operation of compute unified device architecture (CUDA), and performs the parallel simulation processing of multiple sensors using the mode within a short period of time.
Hyun-Woo Kim; Eun-Ha Song; Jong Hyuk Park; Young-Sik Jeong. Parallel Processing Simulator for Separate Sensor of WSN Simulator with GPU. 2015 IEEE 29th International Conference on Advanced Information Networking and Applications 2015, 255 -262.
AMA StyleHyun-Woo Kim, Eun-Ha Song, Jong Hyuk Park, Young-Sik Jeong. Parallel Processing Simulator for Separate Sensor of WSN Simulator with GPU. 2015 IEEE 29th International Conference on Advanced Information Networking and Applications. 2015; ():255-262.
Chicago/Turabian StyleHyun-Woo Kim; Eun-Ha Song; Jong Hyuk Park; Young-Sik Jeong. 2015. "Parallel Processing Simulator for Separate Sensor of WSN Simulator with GPU." 2015 IEEE 29th International Conference on Advanced Information Networking and Applications , no. : 255-262.
With the rapid advancement of information technology in recent years, significant research addressing the efficient storage of big data has been conducted. Traditionally, big data with media-driven service have simply implied extensive amounts of data. However, this definition has evolved to include the extraction of values, analysis, and the prediction of results from a vast volume of unstructured and varied datasets. Because of the explosive growth of computer processing technologies, the creation of big data has originated from unstructured data, text data, image data, and location data created by a variety of digital devices. Classically, the storage of big data has been administered by companies that provide storage services or by specialized storage companies. Significant cost is incurred to store big data efficiently and maintain sufficient storage requirements, which increase continuously. In this paper, a human-centric Resource-Integrated System for Big Data (RISBD) is proposed that utilizes the resources of legacy desktop computers for big data storage to future communication. This is advantageous in terms of the cost of implementing a new storage system. Furthermore, it provides high storage scalability because it is an XML-based standard storage integration system developed using software.
Hyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. Human-centric storage resource mechanism for big data on cloud service architecture. The Journal of Supercomputing 2015, 72, 2437 -2452.
AMA StyleHyun-Woo Kim, Jong Hyuk Park, Young-Sik Jeong. Human-centric storage resource mechanism for big data on cloud service architecture. The Journal of Supercomputing. 2015; 72 (7):2437-2452.
Chicago/Turabian StyleHyun-Woo Kim; Jong Hyuk Park; Young-Sik Jeong. 2015. "Human-centric storage resource mechanism for big data on cloud service architecture." The Journal of Supercomputing 72, no. 7: 2437-2452.
Recently, following the rapid development of IT, diverse virtualization-based studies have been conducted on big data storage. Among the diverse studies, desktop storage virtualization integrates unused storage in distributed legacy desktops using virtualization and provides integrated storage to users for other purposes. In the case of this desktop storage virtualization, high availability is regarded as very important to providing reliability to storage users. In addition, although studies on hierarchical structures and resource incorporation in desktop-based integration environments have been conducted, studies on efficient operations following the occurrence of server faults are insufficient. To achieve this operational high availability, in the present paper, a Sustainable Operation Algorithm (SOA) that can actively respond to the occurrence of desktop server faults in desktop-based storage integration environments is proposed. If the SOA is applied in desktop-based integration environments, desktops can be easily added or removed. The alternative server actively operates following the occurrence of faults. Finally, the SOA provides high QoS to storage users.
Hyun-Woo Kim; HwiRim Byun; Eun-Ha Song; Young-Sik Jeong. Sustainable Operation Algorithm for High Availability with Integrated Desktop Storage Based on Virtualization. Lecture Notes in Electrical Engineering 2015, 123 -128.
AMA StyleHyun-Woo Kim, HwiRim Byun, Eun-Ha Song, Young-Sik Jeong. Sustainable Operation Algorithm for High Availability with Integrated Desktop Storage Based on Virtualization. Lecture Notes in Electrical Engineering. 2015; ():123-128.
Chicago/Turabian StyleHyun-Woo Kim; HwiRim Byun; Eun-Ha Song; Young-Sik Jeong. 2015. "Sustainable Operation Algorithm for High Availability with Integrated Desktop Storage Based on Virtualization." Lecture Notes in Electrical Engineering , no. : 123-128.
Following IT innovations, manual operations have been automated, improving the overall quality of life. This has been possible because an organic topology has been formed among many diverse smart devices grafted onto real life. To provide services to these smart devices, enterprises or users use the cloud. Cloud services are divided into infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). SaaS is operated on PaaS, and PaaS is operated on IaaS. Since IaaS is the foundation of all services, algorithms for the efficient operation of virtualized resources are required. Among these algorithms, desktop resource virtualization is used for high resource availability when existing desktop PCs are unavailable. For this high resource availability, clustering for hierarchical structures is important. In addition, since many clustering algorithms show different percentages of the main resources depending on the desktop PC distribution rates and environments, selecting appropriate algorithms is very important. If diverse attempts are made to find algorithms suitable for the operating environments’ desktop resource virtualization, huge costs are incurred for the related power, time and labor. Therefore, in the present paper, a desktop resource virtualization clustering simulator (DRV-CS), a clustering simulator for selecting clusters of desktop virtualization clusters to be maintained sustainably, is proposed. The DRV-CS provides simulations, so that clustering algorithms can be selected and elements can be properly applied in different desktop PC environments through the DRV-CS.
Jong Hyuk Park; Hyun-Woo Kim; Young-Sik Jeong. Efficiency Sustainability Resource Visual Simulator for Clustered Desktop Virtualization Based on Cloud Infrastructure. Sustainability 2014, 6, 8079 -8091.
AMA StyleJong Hyuk Park, Hyun-Woo Kim, Young-Sik Jeong. Efficiency Sustainability Resource Visual Simulator for Clustered Desktop Virtualization Based on Cloud Infrastructure. Sustainability. 2014; 6 (11):8079-8091.
Chicago/Turabian StyleJong Hyuk Park; Hyun-Woo Kim; Young-Sik Jeong. 2014. "Efficiency Sustainability Resource Visual Simulator for Clustered Desktop Virtualization Based on Cloud Infrastructure." Sustainability 6, no. 11: 8079-8091.
The touch screen, the fruit of recent IT development, is incorporated into many applications through a variety of touch screen smart multimedia devices (e.g., digital cameras, TVs, door-lock systems, smart phones, tablet PCs and so on). For smart multimedia devices, it provides convenient use of time and space for many people by replacing many desktop PC functions. Although this convenience has gained popularity among the public, the security is usually neglected. In addition, the miniaturization of smart devices provides easy portability, but it also leads to more chances of being lost or stolen. Inherent features are generalized, but the features also increase risk of exposing personal information. As a result, smart multimedia devices provide a variety of locking features to protect personal information. The features include simple hiding of the screen, password buttons, and pattern locks. Although password and pattern lock features exhibit some degree of security, they are vulnerable to shoulder surfing or smudging. In this paper, vulnerable security points of smart multimedia devices are complemented and the locking system for enhanced security (LSES), in which intuitive user interface provides convenience, is proposed. LSES reduces exposure risk factors with various input methods for the lock pattern.
Young-Sik Jeong; Hyun-Woo Kim; Jong Hyuk Park. An effective locking scheme of smart multimedia devices with convenience and enhanced security. Multimedia Tools and Applications 2014, 75, 15171 -15183.
AMA StyleYoung-Sik Jeong, Hyun-Woo Kim, Jong Hyuk Park. An effective locking scheme of smart multimedia devices with convenience and enhanced security. Multimedia Tools and Applications. 2014; 75 (23):15171-15183.
Chicago/Turabian StyleYoung-Sik Jeong; Hyun-Woo Kim; Jong Hyuk Park. 2014. "An effective locking scheme of smart multimedia devices with convenience and enhanced security." Multimedia Tools and Applications 75, no. 23: 15171-15183.