• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.61-72
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• 2020

Social problems, such as economic instability, aging population, heightened competition, and changes in personal values, might become more serious in the near future. Affective computing has received much attention in the scholarly community as a possible solution to potential social problems. Accordingly, we examined domestic and global knowledge structure, major keywords, current research status, international research collaboration, and network for each major keyword, focusing on keywords related to affective computing. We searched for articles on a specialized academic database (Scopus) using major keywords and carried out bibliometric and network analyses. We found that China and the United States (U.S.) have been active in producing knowledge on affective computing, whereas South Korea lags well behind at around 10%. Major keywords surrounding affective computing include computing, processing, affective analysis, research, user modeling categorizing recognitions, and psychological analysis. In terms of international research collaboration structure, China and the U.S. form the largest cluster, whereas other countries like the United Kingdom, Germany, Switzerland, Spain, and Canada have been strong collaborators as well. Contrastingly, South Korea's research has not been diverse and has not been very successful in producing research outcomes. For the advancement of affective computing research in South Korea, the present study suggests strengthening international collaboration with major countries, including the U.S. and China and diversifying its research partners.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.1-10
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• 2006

Ubiquitous computing, a new type of network environment has been generating much interest recently and has been actively studied. In ubiquitous computing, the sensor network which consists of low electric power ad-hoc network-based sensors and sensor nodes, is particularly the most important factor The sensor network serves as the mediator between ubiquitous computing and the actual environment. Related studies are focused on network . management through lightweight hardware using RFID. However, to apply these to actual environment, more practical scenarios as well as more secured studies equipped with secures and efficiency features are needed. Therefore, this study aims to build a wireless network based on PTD for multi users, which provides the largest utility in individual networks, and propose an appropriate management method. The proposed method is designed to enhance security and efficiency related to various services required in wireless networks, based on the reliable peripheral devices for users or pm. using pm, which has been applied to electronic commerce transactions in existing papers, this study also proposed an appropriate management method that is suitable for a dynamic environment and setting a temporary group to provide various services.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.27-32
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• 2019

Along with the growth of u-Healthcare, we propose a security enhancement based on network separation for CloudHIS with for handling healthcare information to cope with cyber attack. To protect against all security threats and to establish clear data security policies, we apply desktop computing servers to cloud computing services for CloudHIS. Use two PCs with a hypervisor architecture to apply physical network isolation and select the network using KVM switched controller. The other is a logical network separation using one PC with two OSs, but the network is divided through virtualization. Physical network separation is the physical connection of a PC to each network to block the access path from both the Internet and the business network. The proposed system is an independent desktop used to access an intranet or the Internet through server virtualization technology on a user's physical desktop computer. We can implement an adaptive solution to prevent hacking by configuring the CloudHIS, a cloud system that handles medical hospital information, through network separation for handling security enhancement.

• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.51-59
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• 2019

Edge computing, which is computing on the edge of the network, is becoming a market value as a means of overcoming the fear of communication disconnection and delay reduction, which are the technical weaknesses of cloud computing. Edge computing is continuously expanding applications in various applications such as safety industry, smart factories, autonomous vehicles, mobile communications, and AR/VR. Looking at edge computing trends from Microsoft, IBM, HPE, and Dell EMC, current edge computing must be understood as an integral binding technology and not as a simple complement to the cloud. This paper examines market trends in edge computing and analyzes the impact of edge computing on major related industries.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.1-12
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• 2006

In this study, a value framework for ubiquitous computing is developed and presented. Using 'value focused thinking' approach suggested by Keeney, twenty-two potential users of ubiquitous computing were interviewed and 435 statements were obtained from these interviews. Subsequent purification and redundancy removal process reduces these 435 statements into 166 objectives users have in their mind when thinking about ubiquitous computing. These 166 objectives were again simplified into 37 objectives by clustering. Through a focus group interview, these objectives were again classified into a means-ends network diagram by analyzing reciprocal relationships among them. Resulting means-ends network reveals the value framework inherent within the perception of users. This framework will be useful as a reference in developing new business models in ubiquitous computing as well as developing technologies themselves.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.137-142
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• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

• Journal of Computing Science and Engineering
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• v.7 no.3
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• pp.198-203
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• 2013

In this paper, we focus on a novel Internet architecture, based on the urbanization of virtual machines. In this approach, virtual networks are built linking specific virtual elements (router, switch, firewall, box, access point, etc.). A virtual network represents a network with an independent protocol stack that shares resources from the underlying network infrastructure. Virtualization divides a real computational environment into virtual computational environments that are isolated from each other, and interact with the upper computational layer, as would be expected from a real, non-virtualized environment. Metamorphic networks enhance several concepts related to future networks, and mainly the urbanization of virtual machines. We present this new paradigm, and the methodology, based on the worldwide metamorphic network platform "M-Net". The metamorphic approach could solve many complex problems, especially related to Cloud computing services.

• Convergence Security Journal
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• v.10 no.3
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• pp.15-22
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• 2010

Information security is a critical issue for network centric warfare(NCW). This paper provides defense information security guidelines for NCW, especially for ubiquitous network computing environment. For this purpose, this paper identified changes of battle aspect of tactical level and characteristics of information threats, and finally, the research suggested several information security guidelines for NCW. This paper is to intended to help military organization's planners determine practical and implemental plans in the near future.

• ETRI Journal
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• v.35 no.2
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• pp.207-217
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• 2013

This paper introduces the modular cellular neural network (CNN), which is a new CNN structure constructed from nine one-layer modules with intercellular interactions between different modules. The new network is suitable for implementing many image processing operations. Inputting an image into the modules results in nine outputs. The topographic characteristic of the cell interactions allows the outputs to introduce new properties for image processing tasks. The stability of the system is proven and the performance is evaluated in several image processing applications. Experiment results on texture segmentation show the power of the proposed structure. The performance of the structure in a real edge detection application using the Berkeley dataset BSDS300 is also evaluated.