• Journal of Information Processing Systems
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• v.17 no.5
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• pp.905-917
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• 2021

In recent years, edge computing technology consists of several Internet of Things (IoT) devices with embedded sensors that have improved significantly for monitoring, detection, and management in an environment where big data is commercialized. The main focus of edge computing is data optimization or task offloading due to data and task-intensive application development. However, existing offloading approaches do not consider correlations and associations between data and tasks involving edge computing. The extent of collaborative offloading segmented without considering the interaction between data and task can lead to data loss and delays when moving from edge to edge. This article proposes a range segmentation of dynamic offloading (RSDO) algorithm that isolates the offload range and collaborative edge node around the edge node function to address the offloading issue.The RSDO algorithm groups highly correlated data and tasks according to the cause of the overload and dynamically distributes offloading ranges according to the state of cooperating nodes. The segmentation improves the overall performance of edge nodes, balances edge computing, and solves data loss and average latency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.258-264
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• 2022

The smart farm for livestock, in which information and communication technology (ICT) is combined with livestock farm, is mostly based on the cloud computing paradigm. A cloud-based smart livestock farm has disadvantages such as increased response time, burden on cloud resource caused by the increased number of IoT sensors, traffic burden on the network, and lack of failure resilience mechanisms through collaboration with adjacent IoT devices. In this paper, with these problems in mind, we propose an IoT collaboration system based on edge computing. By using the relatively limited computing resources of the edge device to share the cloud's web server function, we aim to reduce the cloud's resources needed and improve response time to user requests. In addition, through the heartbeat-based failure recovery mechanism, IoT device failures were detected and appropriate measures were taken.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.117-124
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• 2012

A client collaboration (CC) system is proposed for a user relay system. The proposed scheme focuses on the management of transmit power and leakage interference. In the proposed CC system, edge users transmit signals to the masters considered as user relays. The masters relay the signals of the edge users to the base station using the resource blocks (RBs) that are assigned to the edge users. The leakage interference and power consumption were analyzed in the CC system. In addition, an optimal master location problem was formulated based on the signal-to-leakage-plus-noise ratio (SLNR). Because the optimal master location problem is quite complex, a sub-optimal master location problem was proposed and a closed-form sub-optimal master location was obtained. The edge users generate smaller leakage interference and power consumption in the proposed CC system compared to the system without the CC. The numerical results showed that the edge users generate smaller leakage interference and power consumption in the proposed CC system compared to the system without the CC, and the average throughput increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1551-1558
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• 2022

We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.625-627
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• 2022

FEC (Fog/Edge Computing) 환경에서 지연시간 최소화는 로컬과 에지 서버 간의 효율적인 협력을 보장하기 위한 최적의 계산 오프로딩 방법 결정을 통해 실현될 수 있다. 본 논문은 임의의 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 로컬(모바일 장치)과 에지 서버 간의 협업 경로를 추출하는 방법을 제안한다. 제안 방법은 다중 분기구조를 포함하는 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 최적 협업 실행경로 추출 방법을 제안한다. 제안 방법은 각 부분 모듈들의 실행위치에 따라 변화되는 지연시간 측정 및 분석에 적용가능하다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.591-593
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• 2022

This paper proposes a partial offloading system for minimizing application service processing latency in an FEC (Fog/Edge Computing) environment, and it analyzes the offloading effect of the proposed system against local-only and edge-server-only processing based on network load. A partial offloading algorithm based on reconstruction linearization of multi-branch structures is included in the proposed system, as is an optimal collaboration algorithm between mobile devices and edge servers [1,2]. The experiment was conducted by applying layer scheduling to a logical CNN model with a DAG topology. When compared to local or edge-only executions, experimental results show that the proposed system always provides efficient task processing strategies and processing latency.

• Journal of Internet Computing and Services
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• v.2 no.5
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• pp.1-7
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• 2001

Recently, there are two important research trends in the literature the red-time collaborative computing end electronic business process automation. This paper is one of those efforts that would establish an effective business office working and computing environment hough the integration of those two cutting-edge technologies. That is, we try to develop a workflow modeling tool that is semantically based upon the information control net(ICN), which is a typical workflow model for specifying office work procedures(business processes), and that is systemically based upon the real-time collaborative operations by a set of actors, which is called group, We name it "group ICN editor". This paper describes the design and implementation of the group ICN editor that is operable under the real-time collaborative computing environment. We use the Flexible rJAMM toolkit that enables the ICN editor to operate among multiple actors(group) through the event-driven collaboration platform, Consequently, a set of workflow and business processes defined through this editor is not only stored onto database but also transformed into the format of the workflow process definition language(WPDL) that is a standardized workflow description and specification language proposed by the workflow management coalition(WfMC).ion(WfMC).

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.95-105
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• 2013

Recently, SME's Collaboration activities have become one of a vital factor for sustaining competitive edge. This is because of the rapidly changing and competitive market environment, and also to leverage performance by overcoming obstacles of having limited internal resources. Discussing about the effects and relationships of the firm's collaboration activities and its outputs are not new. However, as ICT and various technologies have been diffused into the traditional industries, boundaries and practice capabilities within the industries are becoming ambiguous. Thus contents of the products/services and their development methods are also go and come over the industries. Although many researchers suggested the relations of SME's collaboration activities and innovation performances, most of the previous literatures are focusing on broad perspectives of firm's environmental factors rather than considering various SME's idiosyncrasy factors such as their major product and customer types at once. Therefore, the purpose of this paper is to analyze how SME(Small Medium Enterprise)'s external collaboration activities by their idiosyncrasy act as an input to types of innovation performance. In order to analyze collaboration effects in detail, we defined factors that can represent the SME's business environment - Perceived importance of using external resources, Perceived importance of external partnership, Collaboration and Collaboration levels of Major Product types, Customer types and lastly the Firm Sizes. We have also specifically divided the performance of innovation types as product innovation and process innovation based on existing research. In this study, the empirical analysis is based on Probit Regression Model to observe the correlations with the impact of each SME's business environment and their activities. For the empirical data, 497 samples were collected which, this sample data was extracted from the 'Korean Open Innovation Survey' performed by ETRI(Korean Electronics Telecommunications Research Institute) in 2010. As a result, empirical test results indicated that the impact of collaboration varies depend on the innovation types (Product and Process Innovation). The Impact of the collaboration level for the product innovation tend to be more effective when SMEs are developing for a final product, targeting on for individual customers (B2C). But on the other hand, the analysis result of the Process innovation tend to be higher than the product innovation, when SMEs are developing raw materials for their partners or to other firms targeting on for manufacturing industries(B2B). Also perceived importance of using external resources has effected to both product and process innovation performance. But Perceived importance of external partnership was statistically insignificant. Interesting finding was that the service product has negative effects on for the process innovation performance. And Relationship between size of the firms and their external collaboration activities with their performance of the innovations indicated that the bigger firms(over 100 of employees) tend to have better for both product and process innovations. Finally, implications of the results can be suggested as performance of innovation can be varied depends on firm's unique business idiosyncrasy as well as levels of external collaboration activities. The Implication of this research can be considered for firms in selecting an appropriate strategy as well as for policy makers.

• Journal of Platform Technology
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• v.9 no.1
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• pp.15-22
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• 2021

In a smart manufacturing environment, more and more devices are connected to the Internet so that a large volume of data can be obtained during all phases of the product life cycle. The large-scale industries, companies and organizations that have more operational units scattered among the various geographical locations face a huge resource consumption because of their unorganized structure of sharing resources among themselves that directly affects the supply chain of the corresponding concerns. Cloud-based smart manufacturing paradigm facilitates a new variety of applications and services to analyze a large volume of data and enable large-scale manufacturing collaboration. The manufacturing units include machinery that may be situated in different geological areas and process instances that are executed from different machinery data should be constantly managed by the super admin to coordinate the manufacturing process in the large-scale industries these environments make the manufacturing process a tedious work to maintain the efficiency of the production unit. The data from all these instances should be monitored to maintain the integrity of the manufacturing service system, all these data are computed in the cloud environment which leads to the latency in the performance of the smart manufacturing service system. Instead, validating data from the external device, we propose to validate the data at the front-end of each device. The validation process can be automated by script validation and then the processed data will be sent to the cloud processing and storing unit. Along with the end-device data validation we will implement the APM(Asset Performance Management) to enhance the productive functionality of the manufacturers. The manufacturing service system will be chunked into modules based on the functionalities of the machines and process instances corresponding to the time schedules of the respective machines. On breaking the whole system into chunks of modules and further divisions as required we can reduce the data loss or data mismatch due to the processing of data from the instances that may be down for maintenance or malfunction ties of the machinery. This will help the admin to trace the individual domains of the smart manufacturing service system that needs attention for error recovery among the various process instances from different machines that operate on the various conditions. This helps in reducing the latency, which in turn increases the efficiency of the whole system