• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.111-117
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• 2011

In this paper, we propose an QoS aware multi-layer MAC(QAML-MAC) protocol in a wireless sensor networks. Since the proposed protocol is based on the sleep-awake architecture, which save node's energy to prolong the entire network lifetime. For this purpose the QAML-MAC first classifies incoming data according to their transmission urgency and then saves them. The protocol also adapts the cross-layer concept to re-arrange the order of transmission with the same destination. So the delay can be decreased, which can not be obtained with the previous related protocols. And high priority data such as real-time multimedia or critical value in the field monitoring applications can be transmitted quickly, Furthermore the proposed protocol has advantage of decreasing transmitted data collisions using multiple layers of idle listening when there is no high-priority data. So energy consumptions of sensor nodes can be saved and the network lifetime can be prolonged.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.30-45
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• 2014

Recently, multimedia application users who demand for ubiquitous computing environment are rapidly increasing, and wireless mesh network is receiving attention as a cost-effective key technology for next generation wireless networking. When multiple flows are transmitting data at the same time in the network, routing for path selection of each flow and link resource allocation for data transmission of each flow are one of the key factors that influence to the effectiveness of the network directly. In this paper, we consider problems for path discovery and resource allocation of links at the same time and we propose an algorithm based on mathematical modeling using a technique for cross-layer optimization design in STDMA-based wireless mesh networks that can enhance transfer performance for each flow. We show by performance analysis that the proposed algorithm can enhance the throughput performance by maximally utilizing given bandwidth resources when the number of flows increase in multi-hop wireless mesh networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.2
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• pp.95-101
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• 2014

Scalable video coding (SVC) encodes multimedia data into a base layer and enhancement layers to cope with variable network conditions in an adaptive manner. In SVC, enhancement layers can be decoded only when the base layer is successively received. However, existing works on SVC transmissions in IEEE 802.11 WLANs do not fully investigate this characteristic and thus their performance can be degraded. In this paper, we propose a SVC-aware retransmission (SAR) scheme in IEEE 802.11 WLANs. The SAR scheme applies different retransmission policies for base and enhancement layers by obtaining the optimal number of frames to be retransmitted. As a result, the SAR scheme can reduce unnecessary retransmissions and minimize the transmission latency. Simulation results demonstrate that the SAR scheme can reduce unnecessary data transmission by 12.6% and the transmission latency by 6.6~19.1% compared to conventional retransmission schemes.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1425-1430
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• 2018

In this paper, we propose a CNN based deep learning algorithm for semantic segmentation of images. In order to improve the accuracy of semantic segmentation, we combined pixel level object classification and image level object classification. The image level object classification is used to accurately detect the characteristics of an image, and the pixel level object classification is used to indicate which object area is included in each pixel. The proposed network structure consists of three parts in total. A part for extracting the features of the image, a part for outputting the final result in the resolution size of the original image, and a part for performing the image level object classification. Loss functions exist for image level and pixel level classification, respectively. Image-level object classification uses KL-Divergence and pixel level object classification uses cross-entropy. In addition, it combines the layer of the resolution of the network extracting the features and the network of the resolution to secure the position information of the lost feature and the information of the boundary of the object due to the pooling operation.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.979-987
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• 2021

Multiple Sclerosis (MS) can be early diagnosed by detecting lesions in brain magnetic resonance images (MRI). Unsupervised anomaly detection methods based on autoencoder have been recently proposed for automated detection of MS lesions. However, these autoencoder-based methods were developed only for 2D images (e.g. 2D cross-sectional slices) of MRI, so do not utilize the full 3D information of MRI. In this paper, therefore, we propose a novel 3D autoencoder-based framework for detection of the lesion volume of MS in MRI. We first define a 3D convolutional neural network (CNN) for full MRI volumes, and build each encoder and decoder layer of the 3D autoencoder based on 3D CNN. We also add a skip connection between the encoder and decoder layer for effective data reconstruction. In the experimental results, we compare the 3D autoencoder-based method with the 2D autoencoder models using the training datasets of 80 healthy subjects from the Human Connectome Project (HCP) and the testing datasets of 25 MS patients from the Longitudinal multiple sclerosis lesion segmentation challenge, and show that the proposed method achieves superior performance in prediction of MS lesion by up to 15%.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1301-1306
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• 2018

Artificial intelligence is one of the key technologies of the Fourth Industrial Revolution. This paper introduces the diverse kinds of approaches to subjects that tackle diverse kinds of research fields such as model-based MS approach, deep neural network model, image edge detection approach, cross-layer optimization model, LSSVM approach, screen design approach, CPU-GPU hybrid approach and so on. The research on Superintelligence and superconnection for IoT and big data is also described such as 'superintelligence-based systems and infrastructures', 'superconnection-based IoT and big data systems', 'analysis of IoT-based data and big data', 'infrastructure design for IoT and big data', 'artificial intelligence applications', and 'superconnection-based IoT devices'.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1297-1308
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• 2009

The life time of a wireless sensor network composed of numerous sensor nodes depend on ones of its sensor nodes. The energy efficiency operation of nodes, therefore, is one of the crucial factors to design the network. Researches based on the hierarchical network topology have been proposed and evolved in terms of energy efficiency. However, in existing researches, application layer data obtained from sensor nodes are not considered properly to compose cluster, including issue that nodes communicate with their cluster heads in TDMA scheduling. In this paper, we suggest an energy-efficient topology control scheme based on application layer data in wireless sensor networks. By using application layer data, sensor nodes form a section which is defined as the area of adjacent nodes that retain similar characteristics of application environments. These sections are further organized into clusters. We suggest an algorithm for selecting a cluster head as well as a way of scheduling to reduce the number of unnecessary transmissions from each node to its cluster head, which based on the degree and the duration of similarity between the node's data and its head's data in each cluster without seriously damaging the integrity of application data. The results show that the suggested scheme can save the energy of nodes and increase the life time of the entire network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1182-1191
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• 2011

In this paper, we propose a network-based IP mobility management scheme, called Access Independent Mobile Service with IPv4/IPv6 Dual Stack (AIMS-DS), which can provide high-quality multimedia services to IPv4/IPv6 dual-stack mobile nodes (MNs) without any interruption over various wireless/wired access networks. The proposed scheme provides an MN with a fast and reliable mobility service among heterogeneous wireless access networks through the network-based control, the complete separation method of control and data plane, the cross-layer (layer2 and layer3) interworking method for handover control acceleration, etc, In addition, the proposed AIMS-DS can provide seamless mobility service to an MN under the environments of IPv4/IPv6 coexisting networks through the home address mobility support and transport network support. Through performance evaluation with computer simulations, we have shown the superiority of the proposed AIMS-DS in terms of handover latency, packet 1085 and packet delivery latency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1151-1168
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• 2009

Improving packet loss does not necessarily coincide with the improvement in user perceivable QoS because each frame carries different degree of importance. We propose Significance-aware packet scheduling (SAPS) to maximize user perceivable QoS. SAPS carries out two fundamental issues of packet scheduling: "What to transmit" and "When to transmit?" To adapt to the available bandwidth, it is necessarily to transmit the subset of the data packets if the entire set of packets can not be transmitted. "Packet Significance" quantifies the importance of the frame by elaborately incorporating frames' dependency. Greedy approach is used in selecting packets and transmission schedule is determined based on the Packet Significance. The proposed scheme is tested using publicly available MPEG-4 video clips. Decoding engine is embedded in the simulation software and user perceivable QoS is exposeed in termstermiSNR. Throughout the simulation based experiment, the performance of the proposed scheme is compared two other schemes: Size-based packet scheduling and Bit-rate based best effort packet scheduling. SAPS successfully incorporates the semantics of a packet and improves user perceivable QoS significantly. It successfully provides unequal protection to more important packets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.906-912
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• 2012

A ship ad-hoc network (SANET) can provide ships with diverse multimedia services by replacing expensive satellite communications. While ITU-R M. 1842-1, standards for maritime VHF band digital communications, can be used as the specifications of physical layer for SANETs, no standards are specified for higher layers of SANETs. In this paper, we propose a ship ad-hoc communication (SAC) protocol for SANETs, based on medium access control (MAC) and routing protocols for terrestrial ad-hoc networks. SAC protocol is a cross-layer protocol which combines MAC and routing into one algorithm and considers maritime environments, including the existence of neighboring ships, the possibility of routing to a destination, and changing the communication mode in case of VHF channel failure.