• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.431-443
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• 2003

This paper presents an efficient method to evaluate the performance of an extended stochastic Petri net by simple algebraic operations. The reachability graph is derived from an extended stochastic Petri net, and then converted to a timed stochastic state machine, using a semi-Markov process. The n-th moments of the performance index are derived by algebraic manipulations with each of the n-th moments of transition time and transition probability. For the derivation, three reduction rules are introduced on the transition trajectories in a well-formed regular expression. Efficient computation algorithms are provided to automate the suggested method. The presented method provides a proficient means to derive both the numerical and the symbolic solutions for the performance of an extended stochastic Petri net by simple algebraic manipulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.301-308
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• 2007

In this paper, we propose a new efficient multi-receiver identity-based encryption scheme from Bilinear Pairing. The proposed scheme eliminates pairing computation to encrypt a message for multiple receivers and only need one pairing computation to decrypt the ciphertext. Moreover, we show how to properly transform our scheme into a highly efficient stateless public key broadcast encryption scheme based on the subset-cover framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1523-1545
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• 2019

Cloud computing is now a widespread and economical option when data owners need to outsource or share their data. Designing secure and efficient data access control mechanism is one of the most challenging issues in cloud storage service. Anonymous broadcast encryption is a promising solution for its advantages in the respects of computation cost and communication overload. We bring forward an efficient anonymous identity-based broadcast encryption construction combined its application to the data access control mechanism in cloud storage service. The lengths for public parameters, user private key and ciphertext in the proposed scheme are all constant. Compared with the existing schemes, in terms of encrypting and decrypting computation cost, the construction of our scheme is more efficient. Furthermore, the proposed scheme is proved to achieve adaptive security against chosen-ciphertext attack adversaries in the standard model. Therefore, the proposed scheme is feasible for the system of data access control in cloud storage service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2646-2659
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• 2017

Equipped with the advantages of flexible access control and fine-grained authentication, attribute based signcryption is diffusely designed for security preservation in many scenarios. However, realizing efficient key evolution and reducing the calculation costs are two challenges which should be given full consideration in attribute based cryptosystem. In this paper, we present a key-policy attribute based signcryption scheme (KP-ABSC) with delegated computation and efficient key updating. In our scheme, an access structure is embedded into user's private key, while ciphertexts corresponds a target attribute set. Only the two are matched can a user decrypt and verify the ciphertexts. When the access privileges have to be altered or key exposure happens, the system will evolve into the next time slice to preserve the forward security. What's more, data receivers can delegate most of the de-signcryption task to data server, which can reduce the calculation on client's side. By performance analysis, our scheme is shown to be secure and more efficient, which makes it a promising method for data protection in data outsourcing systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.878-894
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• 2013

Secure multimedia multicast applications involve group communications where group membership requires secured dynamic key generation and updating operations. Such operations usually consume high computation time and therefore designing a key distribution protocol with reduced computation time is necessary for multicast applications. In this paper, we propose a new key distribution protocol that focuses on two aspects. The first one aims at the reduction of computation complexity by performing lesser numbers of multiplication operations using a ternary-tree approach during key updating. Moreover, it aims to optimize the number of multiplication operations by using the existing Karatsuba divide and conquer approach for fast multiplication. The second aspect aims at reducing the amount of information communicated to the group members during the update operations in the key content. The proposed algorithm has been evaluated based on computation and communication complexity and a comparative performance analysis of various key distribution protocols is provided. Moreover, it has been observed that the proposed algorithm reduces the computation and communication time significantly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4081-4098
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• 2022

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.5-7
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• 1991

We have developed an efficient and robust image reconstruction algorithm for static impedance imaging. This improved Newton-Raphson method produced more accurate images by reducing the undesirable effects of the ill-conditioned Hessian matrix. We found that our electrical impedance tomography (EIT) system could produce two-dimensional static images from a physical phantom with 7% spatial resolution at the center and 5% at the periphery. Static EIT image reconstruction requires a large amount of computation. In order to overcome the limitations on reducing the computation time by algorithmic approaches, we implemented the improved Newton-Raphson algorithm on a parallel computer system and showed that the parallel computation could reduce the computation time from hours to minutes.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.639-642
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• 2005

Motion Estimation(ME) is an important part of video compression, because it requires a large amount of computation. Half-pixel and quarter-pixel motion estimation allows high video compression rates but it also has high computation complexity. In this paper we suggest a new and efficient motion estimation algorithm for half-pixel and quarter-pixel motion estimation using SAD values. In the method, an integer-pixel motion vector is found and then only three neighboring points of the integer-pixel motion vector is evaluated to find the half-pixel motion vector. The quarter-pixel motion vector is also found by using a similar method. Experimental results of our method shows 20% reduction in computation time, when compared with those of a conventional method, while producing same quality motion vectors.