• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.37-50
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• 2022

Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.314-328
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• 2023

In this paper, we propose a texture map compression method based on the hierarchical coding method of SHVC to support the scalability function of dynamic mesh compression. The proposed method effectively eliminates the redundancy of multiple-resolution texture maps by downsampling a high-resolution texture map to generate multiple-resolution texture maps and encoding them with SHVC. The dynamic mesh decoder supports the scalability of mesh data by decoding a texture map having an appropriate resolution according to receiver performance and network environment. To evaluate the performance of the proposed method, the proposed method is applied to V-DMC (Video-based Dynamic Mesh Coding) reference software, TMMv1.0, and the performance of the scalable encoder/decoder proposed in this paper and TMMv1.0-based simulcast method is compared. As a result of experiments, the proposed method effectively improves in performance the average of -7.7% and -5.7% in terms of point cloud-based BD-rate (Luma PSNR) in AI and LD conditions compared to the simulcast method, confirming that it is possible to effectively support the texture map scalability of dynamic mesh data through the proposed method.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.591-601
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• 2011

Today's Internet which provides communication channels with best-effort end-to-end performance is rapidly evolving into an autonomic global computing platform. Achieving autonomicity in the Future Internet will require a performance architecture that (a) allows users to request and own 'slices' of geographically-distributed host and network resources, (b) measures and monitors end-to-end host and network status, (c) enables analysis of the measurements within expert systems, and (d) provides performance intelligence in a timely manner for application adaptations to improve performance and scalability. We describe the requirements and design of one such "Future Internet performance architecture" (FIPA), and present our reference implementation of FIPA called 'OnTimeMeasure.' OnTimeMeasure comprises of several measurement-related services that can interact with each other and with existing measurement frameworks to enable performance intelligence. We also explain our OnTimeMeasure deployment in the global environment for network innovations (GENI) infrastructure collaborative research initiative to build a sliceable Future Internet. Further, we present an applicationad-aptation case study in GENI that uses OnTimeMeasure-enabled performance intelligence in the context of dynamic resource allocation within thin-client based virtual desktop clouds. We show how a virtual desktop cloud provider in the Future Internet can use the performance intelligence to increase cloud scalability, while simultaneously delivering satisfactory user quality-of-experience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.741-762
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• 2011

Recently, multicast routing protocols become increasingly important aspect in Mobile Ad hoc Networks (MANETs), as they effectively manage group communications. Meanwhile, multimedia and real-time applications are becoming essential need for users of MANET. Thus it is necessary to design efficient and effective Quality of Service (QoS) multicast routing strategies. In this paper, we address the scalability problem of multicast routing protocols to support QoS over MANETs. In particular, we introduce a Position-Based QoS Multicast Routing Protocol (PBQMRP). Basically, the protocol based on dividing the network area into virtual hexagonal cells. Then, the location information is exploited to perform efficient and scalable route discovery. In comparison with other existing QoS multicast routing protocols, PBQMRP incurs less control packets by eliminating network flooding behavior. Through simulation, the efficiency and scalability of PBQMRP are evaluated and compared with the well-known On-Demand Multicast Routing Protocol (ODMRP). Simulation results justify that our protocol has better performance, less control overhead and higher scalability.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.753-763
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• 1999

The existing SCADA(Supervisory Control and Data Acquisition) system software is usually developed to suitable for the specific hardware platforms. However, as per rapid improvement of computer performance and development of network technology, it is required to support scalability and inter-operability in existing different SCADA systems. In order to meet such requirements, in this paper, we propose a new type of SCADA testbed using Java for electric distribution applications. The system consists of three modules; development support tools, client and server modules. The basic architecture of the proposed SCADA system is similar to existing one, however, we improve the function of MTU and MMI interface to facilitate LAN and WAN environment. Also, the proposed system can deals with alarm and history data by using heterogeneous DBMS. Since the system is built in Java environment, the development cost is cheap and it can support sacalability and portability. Our experience can be utilized to develop next generation of small and medium size of SCADA system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.157-164
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• 2012

This paper introduces an implementation of SVC player which runs on Android platform and can play SVC video stream on line from SVC video server. SVC(Scalable Video Coding) is a scalable video encoding technique which supports three scalability such as temporal scalability, spatial scalability, and quality scalability. To implement the SVC player on Android, we implemented a SVC decoder using JSVM open source written in C/C++ as a native part on Android and developed Android UI in Java. Also we built an SVC encoding system off line and an SVC streaming server to conduct on-line SVC streaming experiments. Finally, after we installed the SVC player developed in this paper on Motoroi mobile phone, we evaluated and analyzed on-line streaming performance of the SVC player. The result showed that the player worked well and it had no jitter in streaming with the size of QCIF and 10fps from a fully encoded SVC video source.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.98-103
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• 2021

In this study, we propose a group communication technique that guarantees security and expandability by configuring a network consisting of IoT terminals equipped with security functions. As the number of devices participating in the network increases, network resources are proportionally reduced, and adding a security function to the IoT device increases the delay time due to encryption in the IoT device. If the error rate that occurs in the network increases, network resources are quickly consumed due to retransmission. Therefore, IoT terminals are grouped to ensure scalability while supporting security, reducing the consumption of network resources even when the number of participating nodes increases, thus ensuring scalability. For the future implementation, the encryption method used in IoT terminals considered the standard of IEEE802.5.4, and the standardization trend was investigated and classified. The proposed method applies IoT devices that provide security functions of the IEEE802.5.4 standard to the group communication base to ensure reliability and scalability. In the performance evaluation, the effectiveness of the proposed method was confirmed by comparing the delay times when grouping IoT devices with security functions through simulation.

• Journal of KIISE
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• v.42 no.4
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• pp.541-549
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• 2015

A large volume of continuously growing BGP data files can raise two technical challenges regarding scalability and manageability. Due to the recent development of the open-source distributed computing infrastructure, Hadoop, it becomes feasible to handle a large amount of data in a scalable manner. In this paper, we present a new Hadoop-based BGP tool (BGPdoop) that provides the scale-out performance as well as the extensible and agile analysis capability. In particular, BGPdoop realizes a query-based BGP record exploration function using Hive on the partitioned BGP data structure, which enables flexible and versatile analytics of BGP archive files. From the experiments for the scalability with a Hadoop cluster of 20 nodes, we demonstrate that BGPdoop achieves 5 times higher performance and the user-defined analysis capability by expressing diverse BGP routing analytics in Hive queries.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.199-205
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• 2008

The centralized conference model has advantage of conference management and control. however it's scalability has been limited as performance degrades largely with increasing number of conference users. So new distributed conference models which improve scalability of centralized conference model have been suggested recently. In the distributed conference model. as conference users exceed a predefined maximum number, a new conference server is added to the conference dynamically. In this paper, We have proposed a new method which increases efficiency of conference event package processing that primary conference server should charge in the distributed conference environment. The primary conference server exchanges informations with each secondary conference servers and conference users by using conference event package. And from the conference information database it selects SIP(Session Initiation Protocol) UA(User Agent) which will share notification to the conference users, and transfers lists to each conference servers. The conference servers make the selected UAs share processing of conference event package, so loads of SIP signal processing decrease, and improve scalability of distributed conference model. The performance of our proposed model is evaluated by experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.207-212
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• 2018

As a data analysis tool which is becoming popular in the Big Data era, R is rapidly expanding its user range by providing powerful statistical analysis and data visualization functions. Major advantage of R is its functional scalability based on open source, but its scale scalability is limited, resulting in performance degrades in large data processing. RHadoop, one of the extension packages to complement it, can improve data analysis performance as it supports Hadoop platform-based distributed processing of programs written in R. In this paper, we evaluate the validity of RHadoop by evaluating the performance improvement of RHadoop in real medical big data analysis. Performance evaluation of the analysis of the medical history information, which is provided by National Health Insurance Service, using R and RHadoop shows that RHadoop cluster composed of 8 data nodes can improve performance up to 8 times compared with R.