• Journal of KIISE:Databases
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• v.28 no.3
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• pp.484-493
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• 2001

As real-time database systems are extended to the distributed computing environment, the need to apply the existing real-time concurrency control schemes to the distributed computing environment has been made. In this paper we propose an efficient concurrency control scheme for distributed real-time database system. Our proposed scheme guarantees a transaction to commit at its maximum, reduces the restart of a transaction that is on the prepared commit phase, and minimizes the time of the lock holding. This is because it raises the priority of the transaction that is on the prepared commit phase in the distributed real-time computing environment. In addition, it reduces the waiting time of a transaction that owns borrowed data and improves the performance of the system, as a result of lending the data that the transaction with the raised priority holds. We compare the proposed scheme with DO2PL_PA(Distributed Optimistic Two-Phase Locking) and MIRROR(Managing Isolation in Replicated Real-time Object Repositories) protocol in terms of the arrival rate of transactions, the size of transactions, the write probability of transactions, and the replication degree of data in a firm-deadline real-time database system based on two-phase commit protocol. It is shown through the performance evaluation that our scheme outperforms the existing schemes.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.583-594
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• 1999

With the advance of VLSI and network technologies, it has now become a common practice to deploy a various forms of distributed computing environments. A study shows that a lot of network-aware computers are in an idle state for considerable amount of time depending on the types of users and time frames of the day. If we can take the full advantage of those idle computers, we can obtain the enormous combined processing power without further costly investment. In this paper, we present a distributed batch-processing system, called the Java Distributed Batch-processing System (JDBS), which allows us to execute CPU-intensive, independent jobs across a pool of idle workstations on top of extant distributed computing environments. Since JDBS is implemented using a Java programming language, it not only extends the scope of machine types that can be joined to the pool, but makes it a lot easier to build an entire system. Besides, JDBS is scalable and fault-tolerant due to its multi-cluster organization and intelligent strategies. A graphical user interface is also provided to facilitate the registration and unregistration, job submission, and job monitoring.

• Journal of Korea Spatial Information System Society
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• v.7 no.1 s.13
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• pp.53-62
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• 2005

A challenging task in the LBS system engineering is to implement a highly scalable system architecture which can manage moderate-size configurations handling thousands of moving items as well as upper-end configurations handling distributed computing system architecture that consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone. In this paper, we explain a prototype location data server structuring major components of GALIS by employing the TMO programming scheme, including the execution engine middleware developed to support real-time distributed object programming and real-time distributed computing system design. We present how to generate realistic location sensing reports and how to process such location reports and location-related queries. Some experimental results showing performance factors regarding distributed query processing are also explained.

• Journal of KIISE
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• v.41 no.11
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• pp.958-966
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• 2014

Wireless sensor networks offer a distributed processing environment. Many sensor nodes are deployed in fields that have limited resources such as computing power, network bandwidth, and electric power. The sensor nodes construct their own networks automatically, and the collected data are sent to the sink node. In these traditional wireless sensor networks, network congestion due to packet flooding through the networks shortens the network life time. Clustering or in-network technologies help reduce packet flooding in the networks. Many studies have been focused on saving energy in the sensor nodes because the limited available power leads to an important problem of extending the operation of sensor networks as long as possible. However, we focus on the execution time because clustering and local distributed processing already contribute to saving energy by local decision-making. In this paper, we present a cooperative processing model based on the processing timeline. Our processing model includes validation of the processing, prediction of the total execution time, and determination of the optimal number of processing nodes for distributed processing in wireless sensor networks. The experiments demonstrate the accuracy of the proposed model, and a case study shows that our model can be used for the distributed application.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.11-16
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• 2004

Recently, collaborative works are increased more and more over the distributed heterogeneous computing environments. The availability of high-speed wide-area networks has also enabled collaborative multimedia applications such as video conferencing, distributed interactive simulation and collaborative visualization. Distributed high performance computing and collaborative multimedia applications, it is extremely important to efficiently perform group communication over a heterogeneous network. Typical group communication patterns are broadcast and Multicast. Heuristic algorithms such as FEF, ECEF, look-ahead make up the message transmission tree for the broadcast and multicast over the distributed heterogeneous systems. But, there are some shortcomings because these select the optimal solution at each step, it may not be reached to the global optimum In this paper, we propose a new heuristic algerian that constructs tree for efficiently collective communication over the previous heterogeneous communication model which has heterogenity in both node and network. The previous heuristic algorithms my result in a locally optimal solution, so we present more reasonable and available criterion for choosing edge. Through the performance evaluation over the various communication cost, improved heuristic algorithm we proposed have less completion time than previous algorithms have, especially less time complexity than look-ahead approach.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.19-28
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• 2017

Various methods for reducing the load on the server have been implemented in performing face recognition remotely by the spread of IP security cameras. In this paper, IP surveillance cameras at remote sites are input through a DSP board equipped with face detection function, and then face detection is performed. Then, the facial region image is transmitted to the server, and the face recognition processing is performed through face recognition distributed processing. As a result, the overall server system load and significantly reduce processing and real-time face recognition has the advantage that you can perform while linked up to 256 cameras. The technology that can accomplish this is to perform 64-channel face recognition per server using distributed processing server technology and to process face search results through 250 camera channels when operating four distributed processing servers there was.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2831-2847
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• 2017

In this paper, a joint destination-relay selection and antenna mode selection scheme for full-duplex (FD) relay network is investigated, which consists of one source node, N FD amplify-and-forward (AF) relays and M destination nodes. Multiple antennas are configured at the source node, and beamforming technique is adopted. Two antennas are employed at each relay, one for receiving and the other for transmitting. Only one antenna is equipped at each destination node. In the proposed scheme, the best destination node is firstly selected according to the direct links between the source node and destination nodes. Then the transmit and receive mode of two antennas at each relay is adaptively selected based on the relaying link condition. Meanwhile, the best relay with the optimal Tx/Rx antenna configuration is selected to forward the signals. To characterize the performance of the proposed scheme, the closed-form expression of the outage probability is derived; meanwhile, the simple asymptotic expressions are also obtained. Our analysis shows that the proposed scheme obtains the benefits of multi-relay diversity and multi-destination diversity. Moreover, extra space diversity in the medium SNR region can be achieved due to the antenna selection at the relay. Finally, Monte-Carlo simulations are provided to consolidate the analytical results, and show the effectiveness of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1490-1501
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• 2016

In this paper, we propose an image-based indoor localization system using parallel distributed computing. In order to reduce computation time for indoor localization, an scale invariant feature transform (SIFT) algorithm is performed in parallel by using Apache Spark. Toward this goal, we propose a novel image processing interface of Apache Spark. The experimental results show that the speed of the proposed system is about 3.6 times better than that of the conventional system.

• Journal of KIISE
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• v.41 no.10
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• pp.799-809
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• 2014

In this paper, we address the problem of computing Pearson correlation coefficients and Spearman's rank correlation coefficients in a secure manner while data providers preserve privacy of their own data in distributed environment. For a data mining or data analysis in the distributed environment, data providers(data owners) need to share their original data with each other. However, the original data may often contain very sensitive information, and thus, data providers do not prefer to disclose their original data for preserving privacy. In this paper, we formally define the secure correlation computation, SCC in short, as the problem of computing correlation coefficients in the distributed computing environment while preserving the data privacy (i.e., not disclosing the sensitive data) of multiple data providers. We then present SCC solutions for Pearson and Spearman's correlation coefficients using secure scalar product. We show the correctness and secure property of the proposed solutions by presenting theorems and proving them formally. We also empirically show that the proposed solutions can be used for practical applications in the performance aspect.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.89-100
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• 2000

Recently, studies on the mobile computing environments that enable mobile hosts to move while retaining its network connection are in progress. In these mobile computing environments, one of the necessary components is the distributed file system supporting mobile hosts, and there are several issues for the design and implementation of the shared file system. Among these issues, there are problems caused by network traffic on limited bandwidth of wireless media. Also, there are consistency maintenance issues that are caused by update-conflicts on the shared files in the distributed file system. In this paper, we propose TWB(Trickle Write-Back) scheme that utilizes weak connectivity for cache management of mobile clients. This scheme focuses on saving bandwidth, reducing waste of disk space, and reducing risks caused by disconnection. For such goals, this scheme lets mobile clients write back intermediate states periodically or on demand while delaying unnecessary write-backs. Meanwhile, this scheme is based on the existing distributed file system architecture and provides transparency.