• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.511-516
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• 2006

The data grid computing provides geographically distributed storage resources to solve computational problems with large-scale data. Unlike cache replacement policies in virtual memory or web-caching replacement, an optimal file replacement policy for data grids is the one of the important problems by the fact that file size is very large. The traditional file replacement policies such as LRU(Least Recently Used) LCB-K(Least Cost Beneficial based on K), EBR(Economic-based cache replacement), LVCT(Least Value-based on Caching Time) have the problem that they have to predict requests or need additional resources to file replacement. To solve theses problems, this paper propose SBR-k(Sized-based replacement-k) that replaces files based on file size. The results of the simulation show that the proposed policy performs better than traditional policies.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.1-6
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• 2022

With the emergence of the new era of the 4th industrial revolution, compute-bound workloads with large memory footprint like big data processing increase dramatically. Even in such compute-bound workloads, however, we observe bulky I/Os while loading big data from storage to memory. Although file I/O cache plays a role of accelerating the performance of storage I/O, we found out that the cache hit rate in such environments is not improved even though we increase the file I/O cache capacity because of some special I/O references generated by compute-bound workloads. To cope with this situation, we propose a new file I/O cache management policy that improves the cache hit rate for compute-bound workloads significantly. Trace-driven simulations by replaying file I/O reference logs of compute-bound workloads show that the proposed cache management policy improves the cache hit rate compared to the well-acknowledged CLOCK algorithm by a large margin.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.57-64
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• 2008

The data grid computing provides geographically distributed storage resources to solve computational problems with large-scale data. Unlike cache replacement policies in virtual memory or web-caching replacement, an optimal file replacement policy for data grids is the one of the important problems by the fact that file size is very large. The traditional file replacement policies such as LRU(Least Recently Used), LCB-K(Least Cost Beneficial based on K), EBR(Economic-based cache replacement), LVCT(Least Value-based on Caching Time) have the problem that they have to predict requests or need additional resources to file replacement. To solve theses problems, this paper propose SBR-k(Sized-based replacement-k) that replaces files based on file size. The proposed policy considers file size to reduce the number of files corresponding to a requested file rather than forecasting the uncertain future for replacement. The results of the simulation show that hit ratio was similar when the cache size was small, but the proposed policy was superior to traditional policies when the cache size was large.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.834-850
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• 2021

IT security companies have been releasing file system filter driver security solutions based on the whitelist, which are being used by several enterprises in the relevant industries. However, in February 2019, a whitelist vulnerability was discovered in Microsoft Edge browser, which allows malicious code to be executed unknown to users. If a hacker had inserted a program that executed malicious code into the whitelist, it would have resulted in considerable damage. File system filter driver security solutions based on the whitelist are discretionary access control (DAC) models. Hence, the whitelist is vulnerable because it only considers the target subject to be accessed, without taking into account the access rights of the file target object. In this study, we propose an industrial device security system for Windows to address this vulnerability, which improves the security of the security policy by determining not only the access rights of the subject but also those of the object through the application of the mandatory access control (MAC) policy in the Windows industrial operating system. The access control method does not base the security policy on the whitelist; instead, by investigating the setting of the security policy not only for the subject but also the object, we propose a method that provides improved stability, compared to the conventional whitelist method.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.399-404
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• 2006

In Jana 2, to enforce a suity policy of a program, programmer writes permission sets required by the code at the policy file, sets Security Manager on system and executes the program. Then Security Manager checks by stack inspection whether an access request to resource should be granted or denied whenever code tries to access critical resource. In this paper, we develop a visualization tool which helps programmers enforce security policy effectively into programs. This system is based on the static permission check analysis which analyzes permission checks which must succeed or fail at each method. Based on this analysis information, programmer can examine visually how permission checks and their stack inspection are performed. By modifying program or policy file if necessary and examining analysis information repeatedly, programmer can enforce security policy correctly.

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.35-44
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• 2008

It is important to manage access control for secure ubiquitous applications. In this paper, we present an access-control system for executing policy file which includes access control rules. We implemented Context-aware Access Control Manager(CACM) based on Java Context-Awareness Framework(JCAF) which provides infrastructure and API for creating context-aware applications. CACM controls accesses to method call based on the access control rules in the policy file. We also implemented a support tool to help programmers modify incorrect access control rules using static analysis information, and a simulator for simulating ubiquitous applications. We describe simulation results for several ubiquitous applications.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.384-393
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• 2002

A Parallel file system is normally used to support excessive file requests from parallel applications in a cluster system, whereas prefetching is useful for improving the file system performance. This paper proposes a new prefetching method, Fips(dynamic File Prefetching Scheme based on file access patterms), that is particularly suitable for parallel scientific applications and multimedia web services in a parallel file system. The proposed prefetching method introduces a dynamic prefetching scheme to predict data blocks precisely in run-time although the file access patterns are irregular. In addition, it includes an algorithm to determine whether and when the prefetching is performed using the current available I/O bandwidth. Experimental results confirmed that the use of the proposed prefetching policy in a parallel file system produced a higher file system performance.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.241-245
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• 2008

Non-volatile RAM (NVRAM) has both characteristics of nonvolatility and byte addressability. In order to efficiently exploit this NVRAM in the file system layer, we proposed the MiNV (Metadata in NVram) file system in our previous research. MiNV file system maintains all the metadata in NVRAM while storing file data in NAND Flash memory. In this paper, we experimentally analyze the efficiency for the execution of garbage collection in the MiNV file system. Also, we quantify the file system performance gains obtained from efficient garbage collection. Experimental results show that garbage collection on the MiNV file system executes more efficiently that on YAFFS even though these file systems adopt exactly the same garbage collection policy. Specifically, the MiNV file system invokes the aggressive garbage collection mechanism less frequently than YAFFS. Additionally, the MiNV file system postpones the first execution of the aggressive garbage collection mechanism in our experiments. From the experiments, we verify that the efficiency of garbage collection leads to performance improvements of the MiNV file system.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.422-426
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• 2007

Personal mobile devices equipped with non-volatile storage such as MP3 player, PMP, cellular phone, and USB memory require safety for the stored data on the devices. One of the safety requirements is secure deletion, which is removing stored data completely so that the data can not be restored illegally. In this paper, we study how to design the secure deletion on Flash memory, commonly used as storage media for mobile devices. We consider two possible secure deletion policy, named zero-overwrite and garbage-collection respectively, and analyze how each policy affects the performance of Flash memory file systems. Then, we propose an adaptive file deletion scheme that exploits the merits of the two possible policies. Specifically, the proposed scheme applies the zero-overwrite policy for small files, whereas it employs the garbage-collection policy for large files. Real implementation experiments show that the scheme is not only secure but also efficient.

• Journal of Digital Contents Society
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• v.14 no.1
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• pp.51-57
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• 2013

Storage device based on Flash Memory have many attractive features such as high performance, low power consumption, shock resistance, and low weight, so they replace HDDs to a certain extent. An Storage device based on Flash Memory has FTL(Flash Translation Layer) which emulate block storage devices like HDDs. A garbage collection, one of major functions of FTL, effects highly on the performance and the lifetime of devices. However, there is no de facto standard for new garbage collection algorithms. To solve this problem, we propose File Clustering Algorithm. File Clustering Algorithm respect to update page from same file at the same time. So, these are clustered to same block. For this mechanism, We propose Page Allocation Policy in FTL and use MIN-MAX GAP to guarantee wear leveling. To verify the algorithm in this paper, we use TPC Benchmark. So, The performance evaluation reveals that the proposed algorithm has comparable result with the existing algorithms(No wear leveling, Hot/Cold) and shows approximately 690% improvement in terms of the wear leveling.