• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.661-672
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• 2008

Mobile Ad-hoc NETwork is a kind of self-controlled network composed only of mobile hosts. Since its range of use is gradually expanding into various sections applicable to practical lives, active researches are being conducted on it. However, as it depends on cooperation of nodes composing the entire network, due to weakness of wireless link and lack of its central infrastructure, so it is exposed to more serious risk than general network in security. Therefore, this paper proposes Cluster-Based Dynamic Authentication that enables only reliable nodes to participate in communication, by solving lack of centralized infrastructure, using hierarchical Mobile Ad hoc NETwork structure based on cluster, and by complementing security weakness through mutual authentication between hierarchical nodes. Simulation shows that the proposed scheme can complement security weakness of Mobile Ad hoc NETwork and that it is more adequate in reliability and expandability than the existing schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2699-2707
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• 2013

We proposed the context-awareness routing algorithm DDV (Dynamic Direction Vector)-hop algorithm at Mobile Ad-hoc Network(MANET). MANET has problem about dynamic topology, the lack of scalability of the network by mobile of node. By mobile of node, energy consumption rate is different. So it is important choosing routing algorithms for the minium of energy consumption rate. DDV-hop algorithms considers of the attribute of mobile node, create a cluster and maintain. And it provides a path by searching a route more energy efficient. We apply mobile of node by direction and time, the alogorighm of routning path and energy efficiency clustering is provided, it is shown the result of enery consumption that is optimized for the network.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.33-40
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• 2009

Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.179-184
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• 2006

An intuitive understanding of the dynamic pattern generation in asymmetric networks may be considered an essential component in developing models for the dynamic information processing. It has been reported that the neural network with cyclic connections generates multiple limit cycles. The dynamics of discrete time network with cyclic connections has been investigated intensively. However, the dynamics of a cyclic connection neural network in continuous-time has not been well-known due to the considerable complexity involved in its calculation. In this paper, the dynamic behavior of a continuous-time cyclic connection neural network, in which each neuron is connected only to its nearest neurons with binary synaptic weights of ${\pm}1$, has been investigated. Furthermore, the dynamics and stability of the network have been analyzed using a piece-wise linear approximation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.503-509
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• 2014

In this paper, a PID controller with adaptive neural network compensator is proposed to control the formations of mobile robot. The control system is composed of a kinematic controller based on the leader-following robot and dynamic controller for considering the dynamics of the mobile robot. The dynamic controller is constituted by a PID controller and the adaptive neural network compensator for improving the performance and compensating the change in dynamic characteristics. Simulation results show the performance of the PID controller and the neural network compensator for the circular trajectory and linear trajectory. And it is verified that by improving the performance of a PID controller via the adaptive neural network compensator, the following robot's tracking performance is improved.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.333-341
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• 2006

Recently, Random Constant worm is increasing The worm retards the availability of the overall network by exhausting resources such as CPU resource and network bandwidth, and damages to an uninfected system as well as an infected system. This paper analyzes the Power-Law network which possesses the preferential characteristics to restrain the worm from spreading. Moreover, this paper suggests the model which dynamically controls the spread of the worm using information about depth distribution of the delivery node which can be seen commonly in such network. It has also verified that the load for each node was minimized at the optimal depth to effectively restrain the spread of the worm by a simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.593-600
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• 2007

In this paper, we composed several road network and evaluated the network for the performance of the network with protocols. The protocols we applied were the MANET routing protocols such as AODV(Ad-hoc On-Demand Distance Vector) and DSR(Dynamic Source Routing) protocols. Generally, the AODV performs better than the DSR. However, in my ad-hoc vehicular network, the performance of the DSR is the better than the AODV when there are more vehicles in the road environment than there are the less vehicles. For the simulation, we composed 4-lane road with vehicles and simulated in the OPNET.

• Smart Media Journal
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• v.9 no.1
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• pp.23-29
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• 2020

This paper presents an approach for dynamic hand gesture recognition by using algorithm based on 3D Convolutional Neural Network (3D_CNN), which is later extended to 3D Residual Networks (3D_ResNet), and the neural network based key frame selection. Typically, 3D deep neural network is used to classify gestures from the input of image frames, randomly sampled from a video data. In this work, to improve the classification performance, we employ key frames which represent the overall video, as the input of the classification network. The key frames are extracted by SegNet instead of conventional clustering algorithms for video summarization (VSUMM) which require heavy computation. By using a deep neural network, key frame selection can be performed in a real-time system. Experiments are conducted using 3D convolutional kernels such as 3D_CNN, Inflated 3D_CNN (I3D) and 3D_ResNet for gesture classification. Our algorithm achieved up to 97.8% of classification accuracy on the Cambridge gesture dataset. The experimental results show that the proposed approach is efficient and outperforms existing methods.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.53-62
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• 2011

With the steady growth of mobile technology and applications, demand for more storage in mobile devices has also increased. A lightweight block-level protocol, Internet Advanced Technology Attachment (iATA), has been developed to deliver a cost-effective storage network solution for mobile devices to obtain more storage. This paper seeks to contribute to designing and implementing Load Balancing (LB), Network Monitoring (NM) and Write Replication (WR) modules to improve the protocol's scalability and data availability. LB and NM modules are invoked to collect system resources states and current network status at each associate node (server machine). A dynamic weight factor is calculated based on the collected information and sent to a referral server. The referral server is responsible to analyze and allocate the most ideal node with the least weight to serve the client. With this approach, the client can avoid connecting to a heavily loaded node that may cause delays in subsequent in-band I/O operations. Write replication is applied to the remaining nodes through a WR module by utilizing the Unison file synchronization program. A client initially connected to node IP A for write operations will have no hindrances in executing the relevant read operations at node IP B in new connections. In the worst case scenario of a node crashing, data remain recoverable from other functioning nodes. We have conducted several benchmark tests and our results are evaluated and verified in a later section.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.614-620
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• 2006

Today the automobile has been changed from a mechanical system to an electronic control system fly the development of the electronic technology. In the automobile body, most of these electronic control devices are networked and managed fully by the CAN protocol. But, when a network system is overloaded, unexpected transmission delay for relative low priority objects occurs due to the static priority definition of the CAN protocol. To resolve this problem, this paper proposes a dynamic precedence queue mechanism that creates a queue for the low priority object and its relevant objects to be transmitted, which becomes urgent in an overloaded network system to keep the maximum allowable time delay. For the generated queue, the highest priority is assigned to transmit the queued objects within the shortest time. The mechanism is implemented in the logical link layer of CAN, which does not require any modification of the old CAN hardware. Effectiveness of the proposed mechanism is verified by the real experiments with an automobile network system.