• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4122-4143
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• 2018

Because of the increment in network scale and test expenditure, simulators gradually become main tools for research on key problems of wireless networking, such as radio resource management (RRM) techniques. However, existing simulators are generally event-driven, causing unacceptably large simulation time owing to the tremendous number of events handled during a simulation. In this article, a mass-processing framework for RRM simulations is proposed for the scenarios with a massive amount of terminals of Internet of Things accessing 5G communication systems, which divides the time axis into RRM periods and each period into a number of mini-slots. Transmissions within the coverage of each access point are arranged into mini-slots based on the simulated RRM schemes, and mini-slots are almost fully occupied in dense scenarios. Because the sizes of matrices during this process are only decided by the fixed number of mini-slots in a period, the time expended for performance calculation is not affected by the number of terminals or packets. Therefore, by avoiding the event-driven process, the proposal can simulate dense scenarios in a quite limited time. By comparing with a classical event-driven simulator, NS2, we show the significant merits of our proposal on low time and memory costs.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.41-46
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• 2022

This study analyzed the results and implications of the industry-university cooperation human resource nurturing process based on the I-O model for the Motion Graphics major and the Global Hotelier major in Baek seok University. In this study, based on the analysis of the human resources training performance through industry-university cooperation in the motion graphics and hotelier fields for 5 years, what kind of efforts were made for successful human resource training, and the level of performance was analyzed and improvement points were suggested. In this study, four strategies were set for successful industry-university-tailored human resource nurturing: student-industry matching through industry participation in education, industry-university integrated education, education quality advancement, and customized education infrastructure construction. As a result of the analysis, customized human resource training should first be developed through industry demand survey and a mirror-type practice room should be built to fit the corporate environment. Second, it was found that it is possible to be individual only if there is an active participation of industry experts throughout the curriculum such as subjects and non-subjects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.881-902
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• 2024

Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy-hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.3
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• pp.245-252
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• 2016

The Service Platform for going to Kindergarten configured with Beacon Devices, Gateway attached to the BUS, Mobile Communication Network, and Application Server. In this paper, We understand the need for Commuting Kindergarten Services, And interface to Specification of Kindergartener's Beacon Identification, And so design to Gateway Resource Tree Functions. For the Service Interfacing, Commute alerts handled in Parental Cellphone through APP. The Service Platform can check the registered beacon data collection and operation management function.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.165-184
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• 2023

The ARX-based lightweight block cipher is widely used in resource-constrained IoT devices due to fast and simple operation of software and hardware platforms. However, there are three weaknesses to ARX-based lightweight block ciphers. Firstly, only half of the data can be changed in one round. Secondly, traditional ARX-based lightweight block ciphers are static structures, which provide limited security. Thirdly, it has poor diffusion when the initial plaintext and key are all 0 or all 1. This paper proposes a new dynamic ARX-based lightweight block cipher to overcome these weaknesses, called DABC. DABC can change all data in one round, which overcomes the first weakness. This paper combines the key and the generalized two-dimensional cat map to construct a dynamic permutation layer P1, which improves the uncertainty between different rounds of DABC. The non-linear component of the round function alternately uses NAND gate and AND gate to increase the complexity of the attack, which overcomes the third weakness. Meanwhile, this paper proposes the round-based architecture of DABC and conducted ASIC and FPGA implementation. The hardware results show that DABC has less hardware resource and high throughput. Finally, the safety evaluation results show that DABC has a good avalanche effect and security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.385-392
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• 2015

In IoT(Internet of Things), it is important for wireless networks to communicate data created among resource-constrained wireless nodes, where time synchronization is needed for meaningful data creation and transmission. Time Synchronization by flooding is one of the mostly used protocols for WSN(Wireless Sensor Networks). Even though this type of scheme has some advantages over other types (i.e. a simple algorithm and independency of topology and so on), too many data transmission is required, leading to large power consumption. So, reducing transmission data is an important issue for energy efficiency in this kind of networks. In this paper, a new Flooding-based time synchronization protocol is proposed to use energy efficiently by reducing a transmitted traffic. The proposed scheme's performance has been evaluated and compared with an representative scheme, FTSP(Flooding Time Synchronization Protocol) by simulation. The results are shown that the proposed scheme is better than FTSP.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.305-313
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• 2018

With the explosive growth of smart phones and efficiency, the Android of an open mobile operating system is gradually increasing in the use and the availability. Android systems has proven its availability and stability in the mobile devices, the home appliances's operating systems, the IoT products, and the mechatronics. However, as the usability increases, the malicious code based on Android also increases exponentially. Unlike ordinary PCs, if malicious codes are infiltrated into mobile products, mobile devices can not be used as a lock and can be leaked a large number of personal contacts, and can be lead to unnecessary billing, and can be cause a huge loss of financial services. Therefore, we proposed a method to detect and delete malicious files in real time in order to solve this problem. In this paper, we also designed a method to detect and delete malicious codes in a more effective manner through the process of installing Android-based applications and signature-based malicious code detection method. The method we proposed and designed can effectively detect malicious code in a limited resource environment, such as mobile environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.307-315
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• 2017

Random number generator(RNG) is essential in cryptographic applications. As recently a system using small devices such as IoT, Sensor Network, SmartHome appears, the lightweight cryptography suitable for this system is being developed. However due to resource limitations and difficulties in collecting the entropy, RNG designed for the desktop computer are hardly applicable to lightweight environment. In this paper, we propose a lightweight RNG to produce cryptographically strong random number using sensors. Our design uses a Hankel matrix, block cipher as the structure and sensors values as noise source. Futhermore, we implement the lightweight RNG in Arduino that is one of the most popular lightweight devices and estimate the entropy values of sensors and random number to demonstrate the effectiveness and the security of our design.