• ETRI Journal
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• v.26 no.6
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• pp.615-621
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• 2004

Next generation mobile communication system, such as IMT-2000, adopts Turbo codes due to their powerful error correction capability. This paper presents a block-wise maximum a posteriori (MAP) Turbo decoding structure with a low memory requirement. During this research, it has been observed that the training size and block size determine the amount of required memory and bit-error rate (BER) performance of the block-wise MAP decoder, and that comparable BER performance can be obtained with much shorter blocks when the training size is sufficient. Based on this observation, a new decoding structure is proposed and presented in this paper. The proposed block-wise decoder employs a decoding scheme for reducing the memory requirement by setting the training size to be N times the block size. The memory requirement for storing the branch and state metrics can be reduced 30% to 45%, and synthesis results show that the overall memory area can be reduced by 5.27% to 7.29%, when compared to previous MAP decoders. The decoder throughput can be maintained in the proposed scheme without degrading the BER performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.801-804
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• 2009

In this paper, the Linux kernel memory map was analyzed as the approach to Improving performance for Embedded Linux system. Since the Linux kernel memory map supporting a stability and various H/W platforms and in which it becomes to the general purpose system with optimization manages the role of being important in the booting time and the efficient system utilization of resources, the analysis of the kernel memory map is required for the performance improvement of the Embedded Linux system in which it is restrictive the resources. According to the analysis result, and of the Linux kernel memory, the booting speed of and improvement of the memory efficiency were confirmed. It is therefore considered that the proposed in this paper and kernel memory allocation method are suitable to the memory availability improvement of the Embedded Linux system.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.244-254
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• 2006

This paper presents an efficient hybrid technique to compact the trie indexing the huge forward table small enough to be stored into cache for speeding up IP lookup. It combines two techniques, an encoding scheme called bit-map and a controlled-prefix expanding scheme to replace slow memory search with few fast-memory accesses and computations. For compaction, the bit-map represents each index and child pointer with one bit respectively. For example, when one node denotes n bits, the bit-map gives a high compression rate by consumes $2^{n-1}$ bits for $2^n$ index and child link pointers branched out of the node. The controlled-prefix expanding scheme determines the number of address bits represented by all root node of each trie's level. At this time, controlled-prefix scheme use a dynamic programming technique to get a smallest trie memory size with given number of trie's level. This paper proposes standard that can choose suitable trie structure depending on memory size of system and the required IP lookup speed presenting optimal memory size and the lookup speed according to trie level number.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.2
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• pp.101-107
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• 2014

Mobile robots use an environment map of its workspace to complete the surveillance task. However grid-based maps that are commonly used map format for mobile robot navigation use a large size of memory for accurate representation of environment. In this reason, grid-based maps are not suitable for path planning of mobile robots using embedded board. In this paper, we present the path planning algorithm that produce a secure path rapidly. The proposed approach utilizes a hybrid map that uses less memory than grid map and has same efficiency of a topological map. Experimental results show that the fast path planning uses only 1.5% of the time that a grid map based path planning requires. And the results show a secure path for mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.860-863
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• 1997

FCM(Fuzzy Cognitive Map) is a fuzzy signed directed graph for representing causal reasoning which has fuzziness between causal concepts. Authors have already proposed FCM-based fault diagnostic scheme. However, the previously proposed scheme has the problem of lower diagnostic resolution. In order to improve the diagnostic resolution, a new diagnostic scheme based on extended FCM which incorporates the concept of fuzzy number into FCM is developed in this paper. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and pattern matching scheme are also proposed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.725-732
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• 2002

Block-wise MAP (Maximum A posteriori) decoding algorithm for turbo-codes requires less memory than Log-MAP decoding algorithm. The ER (Bit Error Rate) performance of previous block-wise MAP decoding algorithm depend on the block length and training length. To maximize hardware utilization and perform successive decoding, the block length is set to be equal to the training length in previous MAP decoding algorithms. Simulation result on the BER performance shows that the EBR performance can be maintained with shorter blocks when training length is sufficient. This paper proposes an architecture for area efficient block-wise MAP decoder. The proposed architecture employs the decoding schema for reducing memory by using the training length, which in N times larger than block length. To efficiently handle the proposed schema, a pipelined architecture is proposed. Simulation results show that memory usage can be reduced by 30%~45% in the proposed architecture without degrading the BER performance.

• Journal of KIISE
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• v.43 no.9
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• pp.998-1007
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• 2016

In recent years, the cost of automotive ECU (Electronic Control Unit) has accounted for more than 30% of total car production cost. However, the complexity of testing and debugging an automotive ECU is increasing because automobile manufacturers outsource automotive ECU production. Therefore, a large amount of cost and time are spent to localize faults during testing an automotive ECU. In order to solve these problems, we propose a fault localization method in memory for developers who run the integration testing of automotive ECU. In this method, memory is partitioned by utilizing memory map, and fault-suspiciousness for each partition is calculated by utilizing memory update information. Then, the fault-suspicious region for partitions is decided based on calculated fault-suspiciousness. The preliminary result indicated that the proposed method reduced the fault-suspicious region to 15.01(%) of memory size.

• Spatial Information Research
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• v.20 no.5
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• pp.67-76
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• 2012

Recently the mobile DBMS (Database Management System) is popular to store and manage large data in a mobile device. Especially, the research and development about mobile storage structure and querying method for navigation map data in a mobile device have been performed. The performance of the mobile DBMS in which random data accesses are most queries if the NAND flash memory is used as storage media of the DBMS is degraded. The reason is that the performance of flash memory is good in writing sequentially but bad in writing randomly as the features of the NAND flash memory. So, new storage structure and querying policies of the mobile DBMS are needed in the mobile DBMS in which a flash memory is used as storage media. In this paper, we have studied the policy of the database page management to enhance the performance of the frequent random update and applied this policy to the navigation-specialized mobile DBMS which supports incremental map update. And also we have evaluated the performance of this policy by experiments.

• Journal of KIISE
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• v.42 no.9
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• pp.1109-1116
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• 2015

In this paper, we propose a query processing approach that uses the Spark functional programming and distributed memory system to solve the computational overhead of SPARQL. In the semantic web, RDF ontology data is produced at large scale, and the main challenge for the semantic web is to query and manipulate such a large ontology with a high throughput. The most existing studies on SPARQL have focused on deploying the Hadoop MapReduce framework, and although approaches based on Hadoop MapReduce have shown promising results, they achieve a low level of throughput due to the underlying distributed file processes. Therefore, in order to speed up the query processes, we suggest query- processing methods that are based on memory caching in distributed memory system. Our approach is also integrated with a clause unification method for propagating between the clauses that exploits Spark join, map and filter methods along with caching. In our experiments, we have achieved a high level of performance relative to other approaches. In particular, our performance was nearly similar to that of Sempala, which has been considered to be the fastest query processing system.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.237-243
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• 2012

In recent system-on-chip (SoC) designs, several hundred embedded memory cores have occupied the largest portion of the chip area. Therefore, the yield of SoCs is strongly dependent on the yield of the embedded memory cores. If all memories had built-in self repair (BISR) with optimal repair rates, the area overhead would be very large. A bit-map sharing method using a memory grouping is proposed to reduce the area overhead. Since the bit-map memory occupies the largest portion of the area of the built-in redundancy analysis (BIRA), the proposed bit-map sharing method can greatly reduce the area overhead of the BIRA. Based on the experimental results, the proposed method can reduce the area overhead by about 80%.