• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4329-4348
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• 2019

Mobile cloud computing (MCC) can offload heavy computation from mobile devices onto nearby cloudlets or remote cloud to improve the performance as well as to save energy for these devices. Therefore, it is essential to consider how to achieve efficient computation offloading with constraints for multiple users. However, there are few works that aim at multi-objective problem for multiple users. Most existing works concentrate on only single objective optimization or aim to obtain a tradeoff solution for multiple objectives by simply setting weight values. In this paper, a multi-objective optimization model is built to minimize the average energy consumption, time and cost while satisfying the constraint of bandwidth. Furthermore, an improved multi-objective optimization algorithm called D-NSGA-II-ELS is presented to get Pareto solutions with better convergence and diversity. Compared to other existing works, the simulation results show that the proposed algorithm can achieve better performance in terms of energy consumption, time and cost while satisfying the constraint of the bandwidth.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.2
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• pp.13-24
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• 2006

We consider a privacy-preserving cooperative computation protocol evaluating a beneficial function of all participants' secret inputs, such that each party finally holds a share of the function output. We propose a practical privacy-preserving cooperative computation protocol for solving the linear system of equations problem md the linear least-squares problem. Solutions to these problems are widely used in many areas such as banking, manufacturing, and telecommunications. Our multi-party protocol is an efficiently extended version of the previous two-party model.

• Bulletin of the Korean Mathematical Society
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• v.60 no.1
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• pp.1-22
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• 2023

Let L(s, χ) be the Dirichlet L-series associated with an f-periodic complex function χ. Let P(X) ∈ ℂ[X]. We give an expression for ∑^f_n=1 χ(n)P(n) as a linear combination of the L(-n, χ)'s for 0 ≤ n < deg P(X). We deduce some consequences pertaining to the Chowla hypothesis implying that L(s, χ) > 0 for s > 0 for real Dirichlet characters χ. To date no extended numerical computation on this hypothesis is available. In fact by a result of R. C. Baker and H. L. Montgomery we know that it does not hold for almost all fundamental discriminants. Our present numerical computation shows that surprisingly it holds true for at least 65% of the real, even and primitive Dirichlet characters of conductors less than 10⁶. We also show that a generalized Chowla hypothesis holds true for at least 72% of the real, even and primitive Dirichlet characters of conductors less than 10⁶. Since checking this generalized Chowla's hypothesis is easy to program and relies only on exact computation with rational integers, we do think that it should be part of any numerical computation verifying that L(s, χ) > 0 for s > 0 for real Dirichlet characters χ. To date, this verification for real, even and primitive Dirichlet characters has been done only for conductors less than 2·10⁵.

• 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 the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1428-1434
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• 2006

In this paper, we propose the scheme solving privacy infringement in RFID systems with improving the scalability of back-end server. With RFID/USN becoming important subject, many approaches have been proposed and applied. However, limits of RFID, low computation power and storage, make the protection of privacy difficult. The Hash Chain scheme has been known as one guaranteeing forward security, confidentiality and indistinguishability. In spite of that, it is a problem that requires much of computation to identify tags in Back-End server. In this paper, we introduce an efficient key search method, the Hellman Method, to reduce computing complexity in Back-End server. Hellman Method algorism progresses pre-computation and (re)search. In this paper, after applying Hellman Method to Hash chain theory, We compared Preservation and key reference to analyze and apply to parallel With guaranteeing requistes of security for existing privacy protecting Comparing key reference reduced computation time of server to reduce computation complex from O(m) to $O(\frac{m{^2/3}}{w})$ than the existing form.

• Journal of KIISE
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• v.42 no.6
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• pp.707-712
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• 2015

Mobile cloud computing is a technology that uses cloud services to overcome resource constrains of a mobile device, and it applies the computation offloading scheme to transfer a portion of a task which should be executed from a mobile device to the cloud. If the communication cost of the computation offloading is less than the computation cost of a mobile device, the mobile device commits a certain task to the cloud. The previous cost analysis models, which were used for separating functions running on a mobile device and functions transferring to the cloud, only considered the amount of data transfer and response time as the offloading cost. In this paper, we proposed a new task partitioning scheme that considers the frequency of function calls and data synchronization, during the cost estimation of the computation offloading. We also verified the energy efficiency of the proposed scheme by using experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2422-2443
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• 2020

This paper studies a single-user Mobile Edge Computing (MEC) system where mobile device (MD) includes an application consisting of multiple computation components or tasks with dependencies. MD can offload part of each computation-intensive latency-sensitive task to the AP integrated with MEC server. In order to accomplish the application faultlessly, we calculate out the optimal task offloading strategy in a time-division manner for a predetermined execution order under the constraints of limited computation and communication resources. The problem is formulated as an optimization problem that can minimize the energy consumption of mobile device while satisfying the constraints of computation tasks and mobile device resources. The optimization problem is equivalently transformed into solving a nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method. And the proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation. In the outer Bi-Section Search, the proposed algorithm searches for the optimal Lagrangian multiplier variable between the lower and upper boundaries. The inner Bi-Section Search achieves the Lagrangian multiplier vector corresponding to a given variable receiving from the outer layer. Numerical results demonstrate that the proposed algorithm has significant performance improvement than other baselines. The novel scheme not only reduces the difficulty of problem solving, but also obtains less energy consumption and better performance.

• Journal of the Korean Chemical Society
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• v.23 no.3
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• pp.125-131
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• 1979

A method for calculation of two center overlap integrals for a pair of Slater type orbitals was developed by Mulliken et al. In this method the spherical polar coordinates for a pair of Slater type orbitals located at two different points are required to be transformed into a spheroidal coordinate set for calculation of two center overlap integrals. A new method, the expansion method for spherical harmonics, in which Slater type orbitals, located at two different points, are expressed in a common coordinate system has been applied for computation of two center overlap integrals. The new method for computation of two center overlap integrals is required to translate Slater type orbitals centered at two different points into the reference point for computation of two center overlap integrals. This work has been expanded the expansion method for spherical harmonics for computation of two center overlap integrals to $|3s{\g}$, $|5s{\g}$ and $|5s{\g}$. Master formulas for two center overlap integrals are derived for these orbitals, using the general expansion formulas. The numerical values of the two center overlap integrals evaluated for a hypothetical NO molecule are in agreement with those of the previous works.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.7
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• pp.70-77
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• 2010

Motion estimation occupies most of the required computation in video compression, and many fast search algorithms were propsoed to reduce huge computation. SAD (sum-of-absolute difference) calculation is the most computation-intensive process in the motion estimation. Early termination is widely used in SAD calculation, where SAD calculation is terminated and it proceeds to next search position if partial SAD during SAD calculation exceeds current minimum SAD. In this paper, we proposed a modified 3-step search algorithm for effective early termination where only search order of search positions are adaptive rearranged. Simulation results show that the proposed motion estimation algorithm reduces computation by 17~30% over conventional 3-step search algorithm without extra computation, while maintaining same performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.10
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• pp.791-798
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• 2018

The CFAR algorithm is mainly used for target detection in radar systems. In particular, OS CFAR is used in a non-uniform noise environment. However, it requires a large amount of computation, because it should sort reference cells in ascending order. This makes it difficult to apply the radar system in real time. In this paper, we describe how to reduce the computational burden of OS CFAR. We compared the power of the test cell and reference cell to determine only the presence or absence of target detection. The common reference cells overlapping in the reference cells of the three test cells are obtained. We first compare the test cell with the highest power value among the three test cells to the common reference cells. Next, we compare each test cell to general reference cells, excluding the common reference cells. The computation time is shortened by reducing the power comparison computation amounts.