• Title/Summary/Keyword: Cloud computing systems

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Neural Network and Cloud Computing for Predicting ECG Waves from PPG Readings

  • Kosasih, David Ishak;Lee, Byung-Gook;Lim, Hyotaek
    • Journal of Multimedia Information System
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    • v.9 no.1
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    • pp.11-20
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    • 2022
  • In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

Auto-configurable Security Mechanism for NFV

  • Kim, HyunJin;Park, PyungKoo;Ryou, Jaecheol
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.786-799
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    • 2018
  • Recently, NFV has attracted attention as a next-generation network virtualization technology for hardware -independent and efficient utilization of resources. NFV is a technology that not only virtualize computing, server, storage, network resources based on cloud computing but also connect Multi-Tenant of VNFs, a software network function. Therefore, it is possible to reduce the cost for constructing a physical network and to construct a logical network quickly by using NFV. However, in NFV, when a new VNF is added to a running Tenant, authentication between VNFs is not performed. Because of this problem, it is impossible to identify the presence of Fake-VNF in the tenant. Such a problem can cause an access from malicious attacker to one of VNFs in tenant as well as other VNFs in the tenant, disabling the NFV environment. In this paper, we propose Auto-configurable Security Mechanism in NFV including authentication between tenant-internal VNFs, and enforcement mechanism of security policy for traffic control between VNFs. This proposal not only authenticate identification of VNF when the VNF is registered, but also apply the security policy automatically to prevent malicious behavior in the tenant. Therefore, we can establish an independent communication channel for VNFs and guarantee a secure NFV environment.

A Novel SDN-based System for Provisioning of Smart Hybrid Media Services

  • Jeon, Myunghoon;Lee, Byoung-dai
    • Journal of Internet Computing and Services
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    • v.19 no.2
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    • pp.33-41
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    • 2018
  • In recent years, technology is rapidly changing to support new service consumption and distribution models in multimedia service systems and hybrid delivery of media services is a key factor for enabling next generation multimedia services. This phenomenon can lead to rapidly increasing network traffic and ultimately has a direct and aggravating effect on the user's quality of service (QOS). To address the issue, we propose a novel system architecture to provide smart hybrid media services efficiently. The architecture is designed to apply the software-defined networking (SDN) method, detect changes in traffic, and combine the data, including user data, service features, and computation node status, to provide a service schedule that is suitable for the current state. To this end, the proposed architecture is based on 2-level scheduling, where Level-1 scheduling is responsible for the best network path and a computation node for processing the user request, whereas Level-2 scheduling deals with individual service requests that arrived at the computation node. This paper describes the overall concept of the architecture, as well as the functions of each component. In addition, this paper describes potential scenarios that demonstrate how this architecture could provide services more efficiently than current media-service architectures.

Intelligent Massive Traffic Handling Scheme in 5G Bottleneck Backhaul Networks

  • Tam, Prohim;Math, Sa;Kim, Seokhoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.874-890
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    • 2021
  • With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

Online Monitoring of Ship Block Construction Equipment Based on the Internet of Things and Public Cloud: Take the Intelligent Tire Frame as an Example

  • Cai, Qiuyan;Jing, Xuwen;Chen, Yu;Liu, Jinfeng;Kang, Chao;Li, Bingqiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.3970-3990
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    • 2021
  • In view of the problems of insufficient data collection and processing capability of multi-source heterogeneous equipment, and low visibility of equipment status at the ship block construction site. A data collection method for ship block construction equipment based on wireless sensor network (WSN) technology and a data processing method based on edge computing were proposed. Based on the Browser/Server (B/S) architecture and the OneNET platform, an online monitoring system for ship block construction equipment was designed and developed, which realized the visual online monitoring and management of the ship block construction equipment status. Not only that, the feasibility and reliability of the monitoring system were verified by using the intelligent tire frame system as the application object. The research of this project can lay the foundation for the ship block construction equipment management and the ship block intelligent construction, and ultimately improve the quality and efficiency of ship block construction.

A Container Orchestration System for Process Workloads

  • Jong-Sub Lee;Seok-Jae Moon
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.270-278
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    • 2023
  • We propose a container orchestration system for process workloads that combines the potential of big data and machine learning technologies to integrate enterprise process-centric workloads. This proposed system analyzes big data generated from industrial automation to identify hidden patterns and build a machine learning prediction model. For each machine learning case, training data is loaded into a data store and preprocessed for model training. In the next step, you can use the training data to select and apply an appropriate model. Then evaluate the model using the following test data: This step is called model construction and can be performed in a deployment framework. Additionally, a visual hierarchy is constructed to display prediction results and facilitate big data analysis. In order to implement parallel computing of PCA in the proposed system, several virtual systems were implemented to build the cluster required for the big data cluster. The implementation for evaluation and analysis built the necessary clusters by creating multiple virtual machines in a big data cluster to implement parallel computation of PCA. The proposed system is modeled as layers of individual components that can be connected together. The advantage of a system is that components can be added, replaced, or reused without affecting the rest of the system.

An Efficient Software Defined Data Transmission Scheme based on Mobile Edge Computing for the Massive IoT Environment

  • Kim, EunGyeong;Kim, Seokhoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.974-987
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    • 2018
  • This paper presents a novel and efficient data transmission scheme based on mobile edge computing for the massive IoT environments which should support various type of services and devices. Based on an accurate and precise synchronization process, it maximizes data transmission throughput, and consistently maintains a flow's latency. To this end, the proposed efficient software defined data transmission scheme (ESD-DTS) configures and utilizes synchronization zones in accordance with the 4 usage cases, which are end node-to-end node (EN-EN), end node-to-cloud network (EN-CN), end node-to-Internet node (EN-IN), and edge node-to-core node (EdN-CN); and it transmit the data by the required service attributes, which are divided into 3 groups (low-end group, medium-end group, and high-end group). In addition, the ESD-DTS provides a specific data transmission method, which is operated by a buffer threshold value, for the low-end group, and it effectively accommodates massive IT devices. By doing this, the proposed scheme not only supports a high, medium, and low quality of service, but also is complied with various 5G usage scenarios. The essential difference between the previous and the proposed scheme is that the existing schemes are used to handle each packet only to provide high quality and bandwidth, whereas the proposed scheme introduces synchronization zones for various type of services to manage the efficiency of each service flow. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of throughput, control message overhead, and latency. Therefore, the proposed ESD-DTS is very suitable for upcoming 5G networks in a variety of massive IoT environments with supporting mobile edge computing (MEC).

A Study on Distributed System Construction and Numerical Calculation Using Raspberry Pi

  • Ko, Young-ho;Heo, Gyu-Seong;Lee, Sang-Hyun
    • International journal of advanced smart convergence
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    • v.8 no.4
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    • pp.194-199
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    • 2019
  • As the performance of the system increases, more parallelized data is being processed than single processing of data. Today's cpu structure has been developed to leverage multicore, and hence data processing methods are being developed to enable parallel processing. In recent years desktop cpu has increased multicore, data is growing exponentially, and there is also a growing need for data processing as artificial intelligence develops. This neural network of artificial intelligence consists of a matrix, making it advantageous for parallel processing. This paper aims to speed up the processing of the system by using raspberrypi to implement the cluster building and parallel processing system against the backdrop of the foregoing discussion. Raspberrypi is a credit card-sized single computer made by the raspberrypi Foundation in England, developed for education in schools and developing countries. It is cheap and easy to get the information you need because many people use it. Distributed processing systems should be supported by programs that connected multiple computers in parallel and operate on a built-in system. RaspberryPi is connected to switchhub, each connected raspberrypi communicates using the internal network, and internally implements parallel processing using the Message Passing Interface (MPI). Parallel processing programs can be programmed in python and can also use C or Fortran. The system was tested for parallel processing as a result of multiplying the two-dimensional arrangement of 10000 size by 0.1. Tests have shown a reduction in computational time and that parallelism can be reduced to the maximum number of cores in the system. The systems in this paper are manufactured on a Linux-based single computer and are thought to require testing on systems in different environments.

A study of Reference Model of Smart Library based on Linked Open Data (링크드오픈데이터 기반 스마트 라이브러리의 참조모델에 관한 연구)

  • Moon, Hee-kyung;Han, Sung-kook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.9
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    • pp.1666-1672
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    • 2016
  • In recent years, smart technology has been applied to various information system fields. Especially, traditional library service area is changing to Smart-Library from Digital-Library. In this environment are need to library service software platform for supporting variety content, library services, users and smart-devices. Due to this, existing library service has a limitation that inhibits semantic interoperability between different heterogeneous library systems. In this paper, we propose Linked-Open-Data based smart library as an archetype of future-library system that provide a variety content and system interaction and integration of services. It is an innovative system of the cutting-edge information intensive. Therefore, we designed system environments according to various integration requirements for smart library based on Linked-Open-Data. And, we describe the functional requirements of smart-library systems by considering the users' demands and the eco-systems of information technology. In addition, we show the reference framework, which can accommodate the functional requirements and provide smart knowledge service to user through a variety of smart-devices.

Performance Optimization in GlusterFS on SSDs (SSD 환경 아래에서 GlusterFS 성능 최적화)

  • Kim, Deoksang;Eom, Hyeonsang;Yeom, Heonyoung
    • KIISE Transactions on Computing Practices
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    • v.22 no.2
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    • pp.95-100
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    • 2016
  • In the current era of big data and cloud computing, the amount of data utilized is increasing, and various systems to process this big data rapidly are being developed. A distributed file system is often used to store the data, and glusterFS is one of popular distributed file systems. As computer technology has advanced, NAND flash SSDs (Solid State Drives), which are high performance storage devices, have become cheaper. For this reason, datacenter operators attempt to use SSDs in their systems. They also try to install glusterFS on SSDs. However, since the glusterFS is designed to use HDDs (Hard Disk Drives), when SSDs are used instead of HDDs, the performance is degraded due to structural problems. The problems include the use of I/O-cache, Read-ahead, and Write-behind Translators. By removing these features that do not fit SSDs which are advantageous for random I/O, we have achieved performance improvements, by up to 255% in the case of 4KB random reads, and by up to 50% in the case of 64KB random reads.