• Journal of Internet Computing and Services
• /
• v.19 no.1
• /
• pp.37-47
• /
• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.2 no.2 s.3
• /
• pp.43-54
• /
• 2003

As the demand for ubiquitous mobile wireless Internet grows, vehicles are receiving a lot of attention as new networking platforms. The demand for 4G all-IP networks encourages vehicle networks to be connected using IPv6. By means of network mobility (NEMO) support, we can connect sensors, controllers, local ,servers as well as passengers' devices of a vehicle to the Internet through a mobile router. The mobile router provides the connectivity to the Internet and mobility transparency for the rest of the mobile nodes of an in-vehicle nv6 network. So, it is .important for the mobile router to assure reliable connection and a sufficient data rate for the group of nodes behind it. To provide reliability, this paper proposes an adaptive multihoming architecture of multiple mobile routers. Proposed architecture makes use of different mobility characteristics of different vehicles. Simulation results with different configurations show that the proposed architecture increases session preservation thus increases reliability and reduces packet loss. We also show that the proposed architecture is adaptive to heterogeneous access environment which provide different access coverage areas and data rates. The result shows that our architecture achieves sufficient data rates as well as session preservation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.4B
• /
• pp.311-322
• /
• 2006

Peer-to-peer (P2P) systems have become a popular medium through which to share huge amounts of data. On the basis of network topology, P2P systems are divided into three types: centralized, structured distribution, unstructured distribution. Unstructured P2P systems such as Gnutella are novel in the sense that they are extensible and reliable. However, as the number of nodes increases, unstructured P2P systems would suffer from the high complexity of search operations that have to scan the network to find the required data items. Efficient replication of data items can reduce the complexity, but it introduces another problem of maintaining consistency among replicated data items when each data item could be updated. In this paper, we propose a new update propagation algorithm that propagates an updated data item to all of its replica. The proposed algorithm can reduce the message transfer overhead by adopting the notion of timestamp and hybrid push/pull messaging.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.11
• /
• pp.2533-2540
• /
• 2013

In multihop cellular network environments, the mobility of nodes is a major obstacle to find a reliable routing path between a mobile node (MN) and the access node (AN). Therefore, in this paper, we propose a fast and reliable neighbor discovery protocol that enables the fast and reliable neighbor discovery by considering the node mobility in the multihop cellular network. The proposed neighbor discovery protocol inhibits the transmission of unnecessary control messages to quickly find a suitable neighbor node (NN) and performs a priority-based access control to transmit control messages without collision in the order of NN desirable to be selected. Simulation results show that the proposed neighbor discovery protocol can discover the NNs faster than the conventional scheme and select a more reliable relay node although the number of neighbor nodes increases and the node mobility increases.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.12
• /
• pp.1348-1356
• /
• 1991

The need for MAN(Metropolitan Area Network)has been increased by demands for high performance comuter communication. According to the definition of MAN by IEEE 802.6 MANs have diameter of about 50km, bandwidth of more than 1Mbps, and limited delay, Because optical fibers have unique characteristics that make them attractive for the implementation of MANs several fiber optic networks suitable for MAN application have been proposed. Those networks have drawbacks such as unlimited delay, many processing nodes and limited number of stations. Also IEEE 802.6 proposals and oters improved networks were proposed, but they have complicated access procedures and data buffering and difficulties in implementation. This paper descrives the design of Fiber Optic Metropolitan Area Network in Seoul(Seoul FOMAN) to overcome the drawback, Seoul FOMAN is hierarchical MAN and designed based on the topology of 43 end offices in Seoul. We propose MAN topology, proper access protocol and analyze the performance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.4
• /
• pp.913-920
• /
• 2011

In this paper, a logic process based 1-kbit EEPROM IP for RFID tag chips of 900MHz is designed. The cell array of the designed 1-kbit EEPROM IP is arranged in a form of four blocks of 16 rows x 16 columns, that is in a two-dimensional arrangement of one-word EEPROM phantom cells. We can reduce the IP size by making four memory blocks share CG (control gate) and TG (tunnel gate) driver circuits. We propose a TG switch circuit to supply respective TG bias voltages according to operational modes and to keep voltages between devices within 5.5V in terms of reliability in order to share the TG driver circuit. Also, we can reduce the power consumption in the read mode by using a partial activation method to activate just one of four memory blocks. Furthermore, we can reduce the access time by making BL (bit line) switching times faster in the read mode from reduced number of cells connected to each column. We design and compare two 1-kbit EEPROM IPs, two blocks of 32 rows ${\times}$ 16 columns and four blocks of 16 rows ${\times}$ 16 columns, which use Tower's $0.18{\mu}m$ CMOS process. The four-block IP is smaller by 11.9% in the layout size and by 51% in the power consumption in the read mode than the two-block counterpart.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.93-107
• /
• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.