• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.2
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• pp.209-218
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• 2009

In a wireless sensor network(WSN) each sensor node deals with numerous sensing data elements. For the sake of energy efficiency and network lifetime, sensing data must be handled effectively. A technique used for this is data aggregation. Sending/receiving data involves numerous steps such as MAC layer control packet handshakes and route path setup, and these steps consume energy. Because these steps are involved in all data communication, the total cost increases are related to the counts of data sent/received. Therefore, many studies have proposed sending combined data, which is known as data aggregation. Very effective methods to aggregate sensing data have been suggested, but there is no means of deciding how long the sensor node should wait for aggregation. This is a very important issue, because the wait time affects the total communication cost and data reliability. There are two types of data aggregation; the data counting method and the time waiting method. However, each has weaknesses in terms of the delay. A hybrid method can be adopted to alleviate these problems. But, it cannot provide an optimal point of aggregation. In this paper, we suggest a stochastic-based data aggregation scheme, which provides the cost(in terms of communication and delay) optimal aggregation point. We present numerical analysis and results.

• Journal of the Semiconductor & Display Technology
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• v.15 no.1
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• pp.47-51
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• 2016

Human visual system infers 3D vision through stereo disparity in the stereoscopic images, and stereo visioning are recently being used in consumer electronics which has resulted in much research in the application field. Basically, stereo vision system consists of four processes, which are cost computation, cost aggregation, disparity calculation, and disparity refinement. In this paper, we present and evaluate the existing various methods, focusing on cost aggregation for stereo vision system to comparatively analyze the performance of their algorithms for a given set of resources. Experiments show that Normalized Cross Correlation and Zero-Mean Normalized Cross Correlation provide higher accuracy, however they are computationally heavy for embedded system in the real time systems. Sum of Absolute Difference and Sum of Squared Difference are more suitable selection for embedded system, but they should be required on improvement to apply to the real world system.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.83-95
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• 2020

Because sensor nodes have limited resources in wireless sensor networks, data aggregation can efficiently reduce communication overhead and extend the network lifetime. Although many existing methods are particularly useful for data aggregation applications, they incur unbalanced communication cost and waste lots of sensors' energy. In this paper, we propose a privacy-preserving, energy-saving data aggregation scheme (EBPP). Our method can efficiently reduce the communication cost and provide privacy preservation to protect useful information. Meanwhile, the balanced energy of the nodes can extend the network lifetime in our scheme. Through many simulation experiments, we use several performance criteria to evaluate the method. According to the simulation and analysis results, this method can more effectively balance energy dissipation and provide privacy preservation compared to the existing schemes.

• Journal of Computing Science and Engineering
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• v.3 no.1
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• pp.27-58
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• 2009

Aggregation join queries are an important class of queries over data streams. These queries involve both join and aggregation operations, with window-based joins followed by an aggregation on the join output. All existing research address join query optimization and aggregation query optimization as separate problems. We observe that, by putting them within the same scope of query optimization, more efficient query execution plans are possible through more versatile query transformations. The enabling idea is to perform aggregation before join so that the join execution time may be reduced. There has been some research done on such query transformations in relational databases, but none has been done in data streams. Doing it in data streams brings new challenges due to the incremental and continuous arrival of tuples. These challenges are addressed in this paper. Specifically, we first present a query processing model geared to facilitate query transformations and propose a query transformation rule specialized to work with streams. The rule is simple and yet covers all possible cases of transformation. Then we present a generic query processing algorithm that works with all alternative query execution plans possible with the transformation, and develop the cost formulas of the query execution plans. Based on the processing algorithm, we validate the rule theoretically by proving the equivalence of query execution plans. Finally, through extensive experiments, we validate the cost formulas and study the performances of alternative query execution plans.

• Korean Management Science Review
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• v.17 no.2
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• pp.115-124
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• 2000

Activity-Based Costing(ABC) is an accounting cost system which allocates the overhead cost to each cost object more accurately. ABC system achieves improved accuracy in estimating the cost of cost object by using multiple cost drivers to trace the cost of activities to the cost objects associated with the resources consumed by those activities. The selection and the aggregation of these cost driver candidates can pose difficult problems. This paper deals with these problems in mathematical programming approach. The first model is formulated as an integer programming model in cost driver selection and the second model is formulated as multi-objective goal programming model in reduction of cost drivers already selected.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1194-1199
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• 2009

Stereo vision system is useful method for inferring 3D depth information from two or more images. So it has been the focus of attention in this field for a long time. Stereo matching is the process of finding correspondence points in two or more images. A central problem in a stereo matching is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we proposed a new stereo matching technique using weighted cost aggregation. To begin with, we extract the weight in given stereo images based on features. We compute the costs of the pixels in a given window using correlation of weighted color and brightness information. Then, we match pixels in a given window between the reference and target images of a stereo pair. To demonstrate the effectiveness of the algorithm, we provide experimental data from several synthetic and real scenes. The experimental results show the improved accuracy of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.396-399
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• 2009

Stereo vision system is useful method for inferring 3D depth information from two or more images. So it has been the focus of attention in this field for a long time. Stereo matching is the process of finding correspondence points in two or more images. A central problem in a stereo matching is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we proposed a new stereo matching technique using weighted cost aggregation. To begin with, we extract the weight in given stereo images based on features. We compute the costs of the pixels in a given window using correlation of weighted color, brightness and distance information. Then, we match pixels in a given window between the reference and target images of a stereo pair. To demonstrate the effectiveness of the algorithm, we provide experimental data from several synthetic and real scenes. The experimental results show the improved accuracy of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.3
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• pp.150-154
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• 2011

The technology to build high speed network using low cost DSL in the areas where the cost to build high speed network is high and the network environment is not very accommodating is important in providing the high speed network that meets the user demand and utilizing the network resources in an efficient way. This study presents development of the link aggregation equipment that performs the access control and firewall functions for packet processing based LAN users. The equipments developed support up to 5 line link aggregation as opposed to current 2 line link aggregation. The equipments also allow the use of high speed network in the areas where the network environment is not very accommodating. Also, the fail-over function is added to each line to provide reliability and the self-security function is enhanced to protect the network from unauthorized use and prevents waste of network resources by authorized users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.224-241
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• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.121-129
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• 2011

In wireless sensor networks, a compromised sensor node can inject false data during data aggregation. Existing solutions of securing data aggregation require high communication cost in securing data aggregation. In this paper, we propose a monitoring-based secure data aggregation protocol that minimizes communication cost of identifying the location of false data injection attacks. The main idea is that when monitoring nodes find an injected false data, their reporting messages along with Message Authentication Codes (MACs) are summarized in a single message before sending it to the Base Station (BS). Then the BS identifies the attacking node. The simulation shows that energy consumption of the proposed protocol with short and normal concatenations of MACs are 45% and 36% lower than that of an existing protocol, respectively.