• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.322-330
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• 2009

In order to utilize NAND flash memory as storage media which does not allow update-in-place and limits the number of block erase count, various garbage collection policies supporting wear-leveling have been investigated. Conventional garbage collection policies require cleaning-index calculation for the entire blocks to choose a block to be garbage-collected to support wear-leveling whenever a garbage collection is required, which results in performance degradation of system. This paper proposes a garbage collection policy which supports wear-leveling using a threshold value, which is in fact a variance of erase counts and by the maximum erase count of all blocks, without calculating the cleaning-index. During garbage collection, the erase cost is minimized by using the Greedy Policy if the variance is less than the threshold value. It achieves wear-leveling by excluding the block with the largest erase count from erase target blocks if the variance is larger than threshold value. The proposed scheme shows that a standard deviation approaches to zero as the erase count of blocks approaches to its upper limit and the measured speed of garbage collection is two times faster than the conventional schemes.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.5
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• pp.269-277
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• 2018

NAND flash memory has widely been used because of non-volatility, low power consumption and fast access time. However, it suffers from inability to provide update-in-place and the erase cycle is limited. The unit of read/write operation is a page and the unit of erase operation is a block. Moreover erase operation is slower than other operations. We proposed the Adaptive Garbage Collection (called "AGC") policy which focuses on not only reducing garbage collection process time for real-time guarantee but also wear-leveling for a flash memory lifetime. The AGC performs better than Cost-benefit policy and Greedy policy. But the AGC does not consider the operation characteristics. So we proposed the Advanced Adaptive Garbage Collection (called "A-AGC") policy which considers the page write operation count and block erase operation count. The A-AGC reduces the write operations by considering the data update frequency and update data size. Also, it reduces the erase operations by considering the file fragmentation. We implemented the A-AGC policy and measured the performance compared with the AGC policy. Simulation results show that the A-AGC policy performs better than AGC, specially for append operation.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.3
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• pp.121-130
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• 2017

NAND flash memory has advantages of non-volatility, little power consumption and fast access time. However, it suffers from inability that does not provide to update-in-place and the erase cycle is limited. Moreover, the unit of read/write operation is a page and the unit of erase operation is a block. Therefore, erase operation is slower than other operations. The AGC, the proposed garbage collection policy focuses on not only garbage collection time reduction for real-time guarantee but also wear-leveling for a flash memory lifetime. In order to achieve above goals, we define three garbage collection operating modes: Fast Mode, Smart Mode, and Wear-leveling Mode. The proposed policy decides the garbage collection mode depending on system CPU usage rate. Fast Mode selects the dirtiest block as victim block to minimize the erase operation time. However, Smart Mode selects the victim block by reflecting the invalid page number and block erase count to minimizing the erase operation time and deviation of block erase count. Wear-leveling Mode operates similar to Smart Mode and it makes groups and relocates the pages which has the similar update time. We implemented the proposed policy and measured the performance compare with the existing policies. Simulation results show that the proposed policy performs better than Cost-benefit policy with the 55% reduction in the operation time. Also, it performs better than Greedy policy with the 87% reduction in the deviation of erase count. Most of all, the proposed policy works adaptively according to the CPU usage rate, and guarantees the real-time performance of the system.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.422-428
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• 2009

NAND flash memory is widely used in embedded systems because of many attractive features, such as small size, light weight, low power consumption and fast access speed. However, it requires garbage collection, which includes erase operations. Erase operation is slower than other operations. Further, a block has a limited erase lifetime (typically 100,000) after which a block becomes unusable. The proposed garbage collection policy focuses on minimizing the total number of erase operations, the deviation value of each block and the garbage collection time. NAND flash memory consists of pages of three types, such as valid pages, invalid pages and free pages. In order to achieve above goals, we use a page ratio to decide when to do garbage collection and to select the target victimblock. Additionally, we implement allocating method and group management method. Simulation results show that the proposed policy performs better than Greedy or CAT with the maximum rate 85% of reduction in the deviation value of the erase operations and 6% reduction in garbage collection time.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.1-7
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• 2016

In this paper, we propose in this paper present a novel locality data allocation policy as COLD(Correlated Locality Data) allocation policy. COLD is defined as a set of data that will be updated together later. By distributing a COLD into a NAND block separately, it can preserve th locality. In addition, by handling multiple COLD simultaneously, it can obtain the parallelism among NAND chips. We perform two experiment to demonstrate the effectiveness of the COLD data allocation policy. First, we implement COLD detector, and then, analyze a well-known workload. And we confirm the amount of COLD found depending on the size of data constituting the COLD. Secondly, we compared the traditional page-level mapping policy and COLD for garbage collection overhead in actual development board Cosmos OpenSSD. Experimental results have shown that COLD data allocation policy is significantly reduces the garbage collection overhead. Also, we confirmed that garbage collection overhead vary depending on the COLD size.

• Journal of KIISE:Software and Applications
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• v.29 no.12
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• pp.957-965
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• 2002

Garbage collection in the CLDC typically employs a stop-the-world GC algorithm which is performing a complete garbage collection when needed. This technique is unsuitable for the interactive Java embedded system because this can lead to long and unpredictable delays. In this paper, We present a garbage collection algorithm which reduces the average delay time and supports the interactive environment. Our garbage collector is composed of the allocator and the collector. The allocator determines the allocation position of free-list according to object size, and the collector uses an incremental mark-sweep algorithm. The garbage collector is called periodically by the thread scheduling policy and the allocator allocates the objects of marked state during collection cycle. Also, we introduce a color toggle mechanism that changes the meaning of the bit patterns at the end of the collection cycle. We compared the performance of our implementation with stop-the-world mark-sweep GC. The experimental results show that our algorithm reduces the average delay time and that it provides uniformly low response times.

• 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 Korea Multimedia Society
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• v.12 no.12
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• pp.1710-1717
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• 2009

Flash memory has become the most important storage media in mobile devices along with its attractive features such as low power consumption, small size, light weight, and shock resistance. However, a flash memory can not be written before erased because of its erase-before-write characteristic, which lead to some garbage collection when there is not enough space to use. In this paper, we propose a novel garbage collection scheme, called block-level buffer garbage collection. When it is need to do merge operation during garbage collection, the proposed scheme does not merge the data block and corresponding log block but also search the block-level buffer to find the corresponding block which will be written to flash memory in the next future, and then decide whether merge it in advance or not. Our experimental results show that the proposed technique improves the flash performance up to 4.6% by reducing the unnecessary block erase numbers and page copy numbers.

• Journal of the Korea Society of Computer and Information
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• v.22 no.4
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• pp.25-32
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• 2017

Recently, the use of NAND flash memory is being increased as a secondary device to displace conventional magnetic disk. NAND flash memory, as one among non-volatile memories, has many advantages such as low power, high reliability, low access latency, and so on. However, NAND flash memory has disadvantages such as erase-before-write, unbalanced operation speed, and limited P/E cycles, unlike conventional magnetic disk. To solve these problems, NAND flash memory mainly adopted FTL (Flash Translation Layer). In particular, garbage collection technique in FTL tried to improve the system lifetime. However, previous garbage collection techniques have a sensitive property of the system lifetime according to write pattern. To solve this problem, we propose BSGC (Balanced Selection-based Garbage Collection) technique. BSGC efficiently selects a victim block using all intervals from the past information to the current information. In this work, SFL (Search First linked List), as the proposed block allocation policy, prolongs the system lifetime additionally. In our experiments, SFL and BSGC prolonged the system lifetime about 12.85% on average and reduced page migrations about 22.12% on average. Moreover, SFL and BSGC reduced the average response time of 16.88% on average.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.617-625
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• 2009

NAND flash memory is widely used in embedded systems because of many attractive features, such as small size, light weight, low power consumption and fast access speed. However, it requires garbage collection, which includes erase operations. Erase operation is very slow. Besides, the number of the erase operations allowed to be carried out for each block is limited. The proposed garbage collection method focuses on minimizing the total number of erase operations, the deviation value of each block and the garbage collection time. NAND flash memory consists of pages of three types, such as valid pages, invalid pages and free pages. In order to achieve above goals, we use a page rate to decide when to do garbage collection and to select the target victim block. Additionally, We implement allocating method and group management method. Simulation results show that the proposed policy performs better than Greedy or CAT with the maximum rate at 82% of reduction in the deviation value of erase operation and 75% reduction in garbage collection time.