• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1472-1482
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• 2005

In this paper, we propose a socket interface layer for large-scale multimedia servers that adopt TCP/IP Offload Engines (TOE). In order to provide legacy network applications with binary level compatibility, the socket interface layer intercepts all socket-related system calls to forward to either TOE or legacy TCP/IP Protocol stack. The layer is designed and implemented as a kernel module in Linux. The layer is located between BSD socket layer and INET socket layer, and passes the application's socket requests to INET socket layer or TOE. The layer provides multimedia servers and web servers with the following features: (1) All standard socket APIs and file I/O APIs that are supported (2) Support for binary level compatibility of existing socket programs (3) Support for TOE and legacy Ethernet NICs at the same time.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.54-62
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• 2010

Inverted index structures have become the most efficient data structure for high performance indexing of large text collections, especially online index maintenance, In-Place and merge-based index structures are the two main competing strategies for index construction in dynamic search environments. In the above-mentioned two strategies, a contiguity of posting information is the mainstay of design for online index maintenance and query time. Whereas with the emergence of new storage device(SSD, SCRAM), those do not consider a contiguity of posting information in the design of index structures because of its superiority such as low access latency and I/O throughput speeds. However, SSD(Solid State Drive) is not well suited for traditional inverted structures due to the poor random write throughput in practical systems. In this paper, we propose the new efficient online index structure(SPM) for SSD that significantly reduces the query time and improves the index maintenance performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.

• Journal of Internet Computing and Services
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• v.4 no.1
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• pp.53-65
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• 2003

I/O processing speed of relatively sluggish storage devices incurs overall performance degradation in computer systems. As a solution to improve the situation, SAN(Storage Area Network) has been proposed. In order to utilize a SAN system more effectively, where storage devices are directly connected with a high speed network such as Fibre Channel, a proper management tool is needed. In this paper, we present a design and implementation of a performance monitoring and configuration management tool for the SANtopia system which supports global file sharing in the SAN environment The developed tool is to monitor the performance of the Linux hosts composing the SANtopia system and to manage the configuration of the hosts and storage devices. It also supports GUI(Graphic User Interface) environment using the JAVA programming language.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.101-121
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• 2010

This paper presents an intelligent prefetching technique that significantly improves performance of hybrid fash-disk storage, a combination of flash memory and hard disk. Since flash memory embedded in a hybrid device is much faster than hard disk in terms of I/O operations, it can be utilized as a 'cache' space to improve system performance. The basic strategy for prefetching is to utilize sequential pattern mining, with which we can extract the access patterns of objects from historical access sequences. We use two techniques for enhancing the performance of hybrid storage with prefetching. One of them is to modify a FAST algorithm for mapping the flash memory. The other is to extend the unit of prefetching to a block level as well as a file level for effectively utilizing flash memory space. For evaluating the proposed technique, we perform the experiments using the synthetic data and real UCC data, and prove the usability of our technique.