• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.205-214
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• 2020

With the recent development of hardware and software technology, interest in the development of wearable devices is increasing. In particular, wearable devices require algorithms suitable for low-power and low-capacity embedded devices. Among them, there is an increasing demand for a signal compression algorithm that reduces communication overhead, in order to increase the efficiency of storage and transmission of electrocardiogram (ECG) signals requiring long-time measurement. Because normal beats occupy most of the signal with similar shapes, a high rate of signal compression is possible if normal beats are represented by a template. In this paper, we propose an algorithm for determining the normal beat template using the template cluster and Pearson similarity. Also, the template is expressed effectively as a few vertices through linear approximation algorithm. In experiment of Datum 234 of MIT-BIH arrhythmia database (MIT-BIH ADB) provided by Physionet, a compression ratio was 33.44:1, and an average distribution of root mean square error (RMSE) was 1.55%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1249-1272
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• 2016

In this paper, we propose a symmetric key establishment scheme for wireless sensor networks which tries to minimize the resource usage while satisfying the security requirements. This is accomplished by taking advantage of the communication pattern of wireless sensor networks and adopting heterogeneous wireless sensor networks. By considering the unique communication pattern of wireless sensor networks due to the nature of information gathering from the physical world, the number of keys to be established is minimized and, consequently, the overhead spent for establishing keys decreases. With heterogeneous wireless sensor networks, we can build a hybrid scheme where a small number of powerful nodes do more works than a large number of resource-constrained nodes to provide enhanced security service such as broadcast authentication and reduce the burden of resource-limited nodes. In addition, an on-demand key establishment scheme is introduced to support extra communications and optimize the resource usage. Our performance analysis shows that the proposed scheme is very efficient and highly scalable in terms of storage, communication and computation overhead. Furthermore, our proposed scheme not only satisfies the security requirements but also provides resilience to several attacks.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• Journal of KIISE
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• v.41 no.11
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• pp.878-884
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• 2014

File I/O buffer cache plays an important role in narrowing the wide speed gap between the main memory and the secondary storage. However, data loss or inconsistencies may occur if the system crashes before the data that has been updated in the buffer cache is flushed to storage. Thus, most operating systems adopt a daemon that periodically flushes dirty data to the secondary storage. In this study, we show that periodic flushes account for 30-70% of the total write traffic to storage and remove this inefficiency by implementing a small, non-volatile buffer cache. Specifically, we present space-efficient management techniques, such as delta-write and fragment-grouping, and show that the storage write traffic and throughput can be improved by a margin of 44.2% and 23.6%, respectively, with only a small NVRAM.

• Journal of KIISE
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• v.42 no.1
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• pp.7-14
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• 2015

Storage Class Memory(SCM) has been considered as a next-generation storage device because it has positive advantages to be used both as a memory and storage. However, there are significant problems of data consistency in recently proposed file systems for SCM such as insufficient data consistency or excessive data consistency-control overhead. This paper proposes a novel data consistency-control scheme, which changes the write mode for log data depending on the modified data ratio in a block, using a rollback-recovery scheme instead of the Write Ahead Logging (WAL) scheme. The proposed scheme reduces the log data size and the synchronization cost for data consistency. In order to evaluate the proposed scheme, we implemented our scheme on a Linux 3.10.2-based system and measured its performance. The experimental results show that our scheme enhances the write throughput by 9 times on average when compared to the legacy data consistency control scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.565-586
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• 2022

Cloud storage's elastic expansibility not only provides flexible services for data owners to store their data remotely, but also reduces storage operation and management costs of their data sharing. The data outsourced remotely in the storage space of cloud service provider also brings data security concerns about data integrity. Data integrity verification has become an important technology for detecting the integrity of remote shared data. However, users without data access rights to verify the data integrity will cause unnecessary overhead to data owner and cloud service provider. Especially malicious users who constantly launch data integrity verification will greatly waste service resources. Since data owner is a consumer purchasing cloud services, he needs to bear both the cost of data storage and that of data verification. This paper proposes a verification control algorithm in data integrity verification for remotely outsourced data. It designs an attribute-based encryption verification control algorithm for multiple verifiers. Moreover, data owner and cloud service provider construct a common access structure together and generate a verification sentinel to verify the authority of verifiers according to the access structure. Finally, since cloud service provider cannot know the access structure and the sentry generation operation, it can only authenticate verifiers with satisfying access policy to verify the data integrity for the corresponding outsourced data. Theoretical analysis and experimental results show that the proposed algorithm achieves fine-grained access control to multiple verifiers for the data integrity verification.

• Journal of KIISE:Databases
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• v.29 no.4
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• pp.247-261
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• 2002

Aggregation is an important operation that affects the performance of OLAP systems. In this paper we define a new class of aggregation queries, called range-groupby queries, and present a method for processing them. A range-groupby query is defined as a query that, for an arbitrarily specified region of an n-dimensional cube, computes aggregations for each combination of values of the grouping attributes. Range-groupby queries are used very frequently in analyzing information in MOLAP since they allow us to summarize various trends in an arbitrarily specified subregion of the domain space. In MOLAP applications, in order to improve the performance of query processing, a method of maintaining precomputed aggregation results, called the prefix-sum array, is widely used. For the case of range-groupby queries, however, maintaining precomputed aggregation results for each combination of the grouping attributes incurs enormous storage overhead. Here, we propose a fast algorithm that can compute range-groupby queries with minimal storage overhead. Our algorithm maintains only one prefix-sum away and still effectively processes range-groupby queries for all possible combinations of the grouping attributes. Compared with the method that maintains a prefix-sum array for each combination of the grouping attributes in an n-dimensional cube, our algorithm reduces the space overhead by (equation omitted), while accessing a similar number of cells.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.91-100
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• 2020

This paper presents an evaluation framework for prototyping multimedia streaming services including audio and video in a distributed and/or decentralized storage that can evaluate service quality and performance under various network conditions. The evaluation framework focuses on important indicators which measure and improve service quality by applying decentralized storage to multimedia streaming services that can mimic the scalability of the existing server-client software architecture and the issue of a single point of failure. The integrated framework not only measures performance indicators for evaluating the quality and performance of multimedia streaming on open source based multimedia content streaming services, but also adjusts network quality using network virtualization technology for comprehensive evaluations. The experimental results show that the integrated framework has low overhead in building and operating a decentralized storage with multimedia streaming services on a single host computer which validates the scalability of the developed framework.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.93-100
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• 2017

Recently, demands for high-performance flash-based storage devices (i.e., flash SSD) have rapidly grown in social network services, cloud computing, super-computing, and enterprise storage systems. The industry and academic communities made the NVMe specification for high-performance storage devices, and NVMe-based flash SSDs can be now obtained in the market. In this article, we evaluate performance of NoSQL databases that social network services and cloud computing services heavily adopt by using NVMe-based flash SSDs. To this end, we use NVMe SSD that Samsung Electronics recently developed, and the SSD used in this study has performance up to 3.5GB/s for sequential read/write operations. We use WiredTiger for NoSQL databases, and it is a default storage engine for MongoDB. Our experimental results show that log processing in NoSQL databases is a major overhead when high-performance NVMe-based flash SSDs are used. Furthermore, we optimize components of log processing and optimized WiredTiger show up to 15 times better performance than original WiredTiger.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.11
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• pp.379-384
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• 2016

NAND flash storage is widely used for computer systems, because of it has faster response time, lower power consumption, and larger capacity per unit area than hard disk. However, currently used I/O scheduler in the operating system is optimized for characteristics of the hard disk. Therefore, the conventional I/O scheduler includes the unnecessary overhead in the case of the NAND flash storage to be applied. Particularly, when the write requests performed intensively, garbage collection is performed intensively. So, it occurs the problem that the processing of the I/O request delay. In this paper, we propose the new I/O scheduler to solve the problem of garbage collection performs intensively, and to optimize for NAND flash storage. In the result of performance evaluation, proposed scheme shows an improvement the user responsiveness by reducing 1% of the average read response time and 78% of the maximum response time.