• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3603-3618
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• 2022

The offloading method is important when there are multiple mobile nodes and multiple edge servers. In the environment, those mobile nodes connect with edge servers with different bandwidths, thus taking different time and energy for offloading tasks. Considering the system load of edge servers and the attributes (the number of instructions, the size of files, deadlines, and so on) of tasks, the energy-aware offloading problem becomes difficult under our mobile edge environment (MCE). Most of the past work mainly offloads tasks by judging where the job consumes less energy. But sometimes, one task needs more energy because the preferred edge servers have been overloaded. Those methods always do not pay attention to the influence of the scheduling on the future tasks. In this paper, first, we try to execute the job locally when the job costs a lower energy consumption executed on the MD. We suppose that every task is submitted to the mobile server which has the highest bandwidth efficiency. Bandwidth efficiency is defined by the sending ratio, the receiving ratio, and their related power consumption. We sort the task in the descending order of the ratio between the energy consumption executed on the mobile server node and on the MD. Then, we give a "suffrage" definition for the energy consumption executed on different mobile servers for offloading tasks. The task selects the mobile server with the largest suffrage. Simulations show that our method reduces the execution time and the related energy consumption, while keeping a lower value in the number of uncompleted tasks.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.40-42
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• 2011

Smart hand-held devices like iPhone, iPad, Andriod and other mobile-OS machines are becoming a well known part of our daily lives. Utilization of these devices has gone beyond the expectations of their inventors. Evolution of Apple's iOS from a mobile phone Operating System to a wholesome platform for Portable Gaming is an adequate proof. Using these smart devices people are downloading applications from numerous online App Stores. Utilizing remote storage facilities and confining themselves to computing power far below than an entry level laptop, netbooks have emerged. Google's idea of Chrome OS coupled with Google's AppEngine is an eye-opener for researchers and developers. Keeping all these industry-proven innovations in mind we are proposing a Context-Driven Cloud-Oriented Application Architecture for smart devices. This architecture enables our smart devices to behave smarter by utilizing very less of local resources.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1205-1208
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• 2007

모바일 애드혹 네트워크는 기존의 셀룰러 네트워크와는 달리 고정된 기지국이 존재하지 않고 모바일 노드들만으로 구성된 네트워크이다. 모바일 애드혹 네트워크의 각각의 노드들은 제한된 자원과 한정된 용량을 가진 배터리로 동작한다. 만일 이 배터리를 모두 소모하게 된다면 중간 노드들이 다운이 되고, 결과적으로 전체 네트워크가 단절되는 문제가 발생할 수 있다. 기존의 전송 전력을 고려하여 경로를 설정하는 기법인 CLUSTERPOW는 노드 간에 연결되는 전송 전력을 최소화함으로써 데이터 전송 시 소비되는 전력을 줄이고자 하였다. 그러나 이 기법은 proactive 방식의 라우팅 프로토콜에는 적합하나 reactive 방식의 라우팅 프로토콜에는 적합하지 않다. 따라서 본 논문에서는 reactive 방식의 특성에 맞는 전송 전력 설정 기법인 FSRS(Fast Search Reverse Setting) 기법을 제안하였다. FSRS 기법은 reactive 방식에서 사용하는 컨트롤 패킷 플라딩을 사용한 경로 설정에서의 오버헤드를 줄이고자 클러스터 간 플라딩을 통해 목적지 노드를 빠르게 찾고 한정된 클러스터 간 경로를 통해 전송 전력을 고려한 세부적인 경로를 설정한다. FSRS 기법은 기존의 CLUSTERPOW 기법과 마찬가지로 효율적인 전송 전력으로 경로를 설정하였으며 또한 네트워크 생존 시간을 CLUSTERPOW보다 평균 43% 연장시켰다.

• Journal of Appropriate Technology
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• v.6 no.1
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• pp.56-64
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• 2020

Recently, major manufacturers are focusing their efforts on securing global competitiveness through smart factory, but developing countries have many difficulties in applying smart factory due to financial and technical conditions. This study is a preliminary study on the development of an ICT-based power monitoring system applicable to developing countries. The questionnaire surveyed and analyzed workers' perceptions of smart factory in a garment manufacturing factory in developing countries, Indonesia. Before and after the installation of the power monitoring system, the survey was conducted for 126 local managers and workers, and the correlation was analyzed using SPSS. As a result of analysis, factory workers in developing countries such as Indonesia are also positively aware of the necessity of introducing smart factory technology, and it is expected that the introduction of these technologies will affect job satisfaction and improve the factory environment. In addition, the result of the survey conducted after the installation of the power monitoring system increased the job satisfaction score by 5.5% compared to before the installation, and the scores on the perception of the necessity of the power monitoring system and the positive effect of the application of the system on the factory environment were increased 13% and 5.9%, respectively. It was also confirmed that managers rather than workers and female rather than male showed positive perception for the introduction of smart factory technology. The result of this study is expected to be an important reference in the direction of development of appropriate smart factory technology applicable to developing countries and the introduction of smart factory by manufacturers operating factories in developing countries.

• The KIPS Transactions:PartC
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• v.14C no.2
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• pp.185-190
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• 2007

The efficient node energy utilization is one of important performance factors in wireless sensor networks because sensor nodes operate with limited battery power. To extend the lifetime of the wireless sensor networks, maintaining balanced power consumption between sensor nodes is more important than reducing each energy consumption of the sensor node in the network. In this paper, we proposed a cluster formation algorithm to extend the lifetime of the networks and to maintain a balanced energy consumption of nodes. To obtain it, we add a tiny slot in a round frame, which enables to exchange the residual energy messages between the base station (BS). cluster heads, and nodes. The performance of the proposed protocol has been examined and evaluated with the NS 2 simulator. As a result of simulation, we have confirmed that our proposed algorithm show the better performance in terms of lifetime than LEACH. Consequently, our proposed protocol can effectively extend the network lifetime without other critical overhead and performance degradation.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.241-251
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• 2007

Energy consumption in the instruction cacheaccounts for a significant portion of the total processor energy consumption. Therefore, reducing energy consumption in the instruction cache is important in designing embedded processors. This paper proposes a method for reducing dynamic energy consumption in the instruction cache by partitioning it to smaller (less energy-consuming) sub-caches. When a request comes into the proposed cache, only one sub-cache is accessed by utilizing the locality of applications. By contrast, the other sub-caches are not accessed, leading todynamic energy reduction. In addition, the proposed cache reduces dynamic energy consumption by eliminating the energy consumed in tag matching. We evaluated the energy efficiency by running cycle accurate simulator, SimpleScalar. with power parameters obtained from CACTI. Simulation results show that the proposed cache reduces dynamic energy consumption by $37%{\sim}60%$ compared to the traditional direct-mapped instruction cache.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.557-559
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• 2014

We propose an efficient resource allocation scheme based on interference awareness for D2D (Device-to-Device) communication in cellular networks. Recently, many researchers have studied how to allocate frequency resources to DUE (D2D User Equipment) with full interference channel information. However, it is difficult to assume a scenario where instantaneous interference information between the CUE (Cellular UE) and DUE is known to the BS (Base Station). To tackle this problem, we proposed in this paper a new scheme in which the BS allocates a resource to CUE and DUE without a full channel information and can aware interference based on only transmit power and distance between UEs. Simulation results show effectiveness of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.18-25
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• 2007

In sensor networks, sensor nodes have limited computational capacity, power and memory. Thus energy efficiency is one of the most important requirements. How to extend the lifetime of wireless sensor networks has been widely discussed in recent years. However, one of the most effective approaches to cope with power conservation, network scalability, and load balancing is clustering technique. The function of a cluster head is to collect and route messages of all the nodes within its cluster. Cluster heads must be changed periodically for low energy consumption and load distribution. In this paper, we propose an energy-aware cluster head selection algorithm and Distance Estimation-based distributed Clustering Algorithm (DECA) in wireless sensor networks, which exchanges cluster heads for less energy consumption by distance estimation. Our simulation result shows that DECA can improve the system lifetime of sensor networks up to three times compared to the conventional scheme.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.4
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• pp.291-302
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• 2013

NAND flash memory (NFM) based storage devices, e.g. Solid State Drive (SSD), are rapidly replacing conventional storage devices, e.g. Hard Disk Drive (HDD). As NAND flash memory technology advances, its specification has evolved to support denser cells and larger pages and blocks. However, efforts to fully understand their impacts on design objectives such as performance, power, and cost for various applications are often neglected. Our research shows this recent trend can adversely affect the design objectives depending on the characteristics of applications. Past works mostly focused on improving the specific design objectives of NFM based systems via various architectural solutions when the specification of NFM is given. Several other works attempted to model and characterize NFM but did not access the system-level impacts of individual parameters. To the best of our knowledge, this paper is the first work that considers the specification of NFM as the design parameters of NAND flash storage devices (NFSDs) and analyzes the characteristics of various synthesized and real traces and their interaction with design parameters. Our research shows that optimizing design parameters depends heavily on the characteristics of applications. The main contribution of this research is to understand the effects of low-level specifications of NFM, e.g. cell type, page size, and block size, on system-level metrics such as performance, cost, and power consumption in various applications with different characteristics, e.g. request length, update ratios, read-and-modify ratios. Experimental results show that the optimized page and block size can achieve up to 15 times better performance than the conventional NFM configuration in various applications. The results can be used to optimize the system-level objectives of a system with specific applications, e.g. embedded systems with NFM chips, or predict the future direction of NFM.