• ETRI Journal
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• v.38 no.3
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• pp.529-539
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• 2016

Recently, a product-matrix (PM) framework was proposed to construct optimal regenerating codes for homogeneous distributed storage systems (DSSs). In this paper, we propose an extended PM (EPM) framework for coding of heterogeneous DSSs having different repair bandwidths but identical storage capacities. Based on the EPM framework, an explicit construction of minimum remote-repair bandwidth regenerating (MRBR) codes is presented for a specific heterogeneous DSS, where two geographically different datacenters with associated storage nodes are deployed. The data reconstruction and regeneration properties of the MRBR code are proved strictly. For the purpose of demonstration, an example implementation of MRBR code is provided. The presented MRBR code is the first optimal strict-regenerating code for heterogeneous DSSs. In addition, our proposed EPM framework can be applied to homogeneous systems also.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1182-1199
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• 2023

Fractional repetition (FR) codes can achieve exact uncoded repair for multiple failed nodes, with lower computational complexity and bandwidth overhead, and effectively improve repair performance in distributed storage systems (DSS). The actual distributed storage system is dynamic, that is, the parameters such as node storage overhead and number of storage nodes will change randomly and dynamically. Considering that traditional FR codes cannot be flexibly applied to dynamic distributed storage systems, a new construction scheme of adaptive-and-resolvable FR codes based on hypergraph coloring is proposed in this paper. Specifically, the linear uniform regular hypergraph can be constructed based on the heuristic algorithm of hypergraph coloring proposed in this paper. Then edges and vertices in hypergraph correspond to nodes and coded packets of FR codes respectively, further, FR codes is constructed. According to hypergraph coloring, the FR codes can achieve rapid repair for multiple failed nodes. Further, FR codes based on hypergraph coloring can be generalized to heterogeneous distributed storage systems. Compared with Reed-Solomon (RS) codes, simple regenerating codes (SRC) and locally repairable codes (LRC), adaptive-and-resolvable FR codes have significant advantages over repair locality, repair bandwidth overhead, computational complexity and time overhead during repairing failed nodes.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.9-17
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• 2009

In this paper, we propose a dynamic load distribution technique at the operating system level in mobile storage systems with a heterogeneous storage pair of a small form-factor and disk and a flash memory, which aims at saving energy consumption as well as enhancing I/O performance. Our proposed technique takes a combinatory approach of file placement and buffer cache management techniques to find how the load can be distributed in an energy and performance-aware way for a heterogeneous mobile storage air of a hard disk and a flash memory. We demonstrate that the proposed technique provides better experimental results with heterogeneous mobile storage devices compared with the existing techniques through extensive simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• Journal of The Korean Association of Information Education
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• v.9 no.1
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• pp.79-86
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• 2005

With the rapid advance of computer and communication technology, the amount of data transferred is also increasing more than ever. The recent trend of education systems is connecting related information semantically in different systems in order to improve the utilization of computerized information Therefore, Web-based teaching-learning is developing in the ubiquitous learning direction that learners select and organize the contents, time and order of learning by themselves. That is, it is evolving to provide teaching-learning environment adaptive to individual learners' characteristics (their level of knowledge, pattern of study, areas of interest). This paper proposes the efficient evaluation method of learning contents in a mediator for the integration of heterogeneous information resources. This means that the autonomy of a remote server can be preserved to the highest degree. In addition, this paper proposes the adaptive optimization of learning contents such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a learning content from the past, the accumulated usage frequency of a learning content decays as time goes by.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.95-102
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• 2012

In this paper, we propose a method that can construct efficiently a P2P overlay multicast network composed of many heterogeneous peers in communication bandwidth, processing power and a storage size by selecting a peer in a distributed fashion using an ant-colony theory that is one of the computational intelligence methods. The proposed method considers not only the capacity of a peer but also the number of children peers supported by the peer and the hop distance between a multicast source and the peer when selecting a parent peer of a newly joining node. Thus, an P2P multicast overlay network is constructed efficiently in that the distances between a multicast source and peers are maintained small. In addition, the proposed method works in a distributed fashion in that peers use their local information to find a parent node. Thus, compared to a centralized method where a centralized server maintains and controls the overlay construction process, the proposed method scales well. Through simulations, we show that, by making a few high capacity peers support a lot of low capacity peers, the proposed method can maintain the size of overlay network small even there are a few thousands of peers in the network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.970-973
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• 2012

In cloud environment, enterprises use a number of systems which are not interconnected and save master information in a distributed way in each of them. Master information which is not managed is incorrect and discord each other so that lowers efficiency of business process and disables optimum decision making. It is necessary to do high-qualified management of master information to operate efficient and errorless business process. This paper suggests TMDM as a solution to solve heterogeneous problems occurred between interconnected master information in cloud environment and to manage business process in an efficient method. TMDM is an information storage that is suggested to solve mutual discord problems between master information using Topic Maps that considers correlation between data. Topic Maps can be connected by association between topics in order to access through a topic to all related knowledge information which is described by the topic. This also can be applied to master information between legacy systems within cloud.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.12-26
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• 2004

In the past, geographic data is constructed and serviced through independent formats of its own according to each GIS(Geographic Information System). Recently the provision of interoperability in GIS is important to efficiently apply the various geographic data between conventional GIS's. Whereupon OGC(Open GIS Consortium) proposed GML(Geography Markup Language) to offer the interoperability between heterogeneous GISs in distributed environments. The GML is an XML encoding for the transport and storage of geographic information, including both the spatial and non-spatial properties of geographic features. Also, the GML includes Web Map Server Implementation Specification to service the GML documents. Accordingly the prototype to provide the reciprocal interchange of geographic information between conventional GIS's and GML documents is widely studied. In this paper, we propose a mapping method of geographic in formation between spatial database and GML for the prototype to support the interoperability between heterogeneous geographic information. For this method, firstly the scheme of converting geographic in Formation of the conventional spatial database into the GML document according to the GML specification is explained, and secondly the scheme to transform geographic information of GML documents to geographic data of spatial database is showed. Consequently, the proposed method is applicable to the framework for integrated geographic information services based on Web by making an offer the interoperability between already built geographic information of conventional GIS's using a mapping method of geographic information between spatial database and GML.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.83-94
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• 2004

Recent researches which purport to Integrate distributed information have been concentrated on developing efficient mediator systems that not only provide a high degree of autonomy for local users but also support the flexible integration of required functions for global users. However, there has been little attention on how to evaluate a global query in a mediator. A global query is transformed into a set of its sub-queries and each sub-query is the unit of evaluation in a remote server. Therefore, it is possible to speed up the execution of a global query if the previous results of frequently evaluated sub-queries are materialized in a mediator. Since the Integration schema of a mediator can be incrementally modified and the evaluation frequency of a global query can also be continuously varied, query usage should be carefully monitored to determine the optimized set of materialized sub-queries. Furthermore, as the number of sub-queries increases, the optimization process itself may take too long, so that the optimized set Identified by a long optimization process nay become obsolete due to the recent change of query usage. This paper proposes the adaptive selection of materialized sub-queries such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a query from the past, the accumulated usage frequency of a query decays as time goes by.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.46-54
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• 2018

The Internet of Things (IoT) is an environment in which various devices provide services to users through communications. Because of the nature of the IoT, data are stored and distributed in heterogeneous information systems. In this situation, IoT end applications should be able to access data without having information on where the data are or what the type of storage is. This mechanism is called Service Discovery (SD). However, some problems arise, since the current SD architectures search for data in physical devices. First, turnaround time increases from searching for services based on physical location. Second, there is a need for a data structure to manage devices and services separately. These increase the administrator's service configuration complexity. As a result, the device-oriented SD structure is not suitable to the IoT. Therefore, we propose an SD structure called Name-based Service-centric Service Discovery (NSSD). NSSD provides name-based centralized SD and uses the IoT edge gateway as a cache server to speed up service discovery. Simulation results show that NSSD provides about twice the improvement in average turnaround time, compared to existing domain name system and distributed hash table SD architectures.