• ETRI Journal
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• v.26 no.6
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• pp.535-544
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• 2004

With video compression standards such as MPEG-4, a transmission error happens in a video-packet basis, rather than in a macroblock basis. In this context, we propose a semantic error prioritization method that determines the size of a video packet based on the importance of its contents. A video packet length is made to be short for an important area such as a facial area in order to reduce the possibility of error accumulation. To facilitate the semantic error prioritization, an efficient hardware algorithm for face tracking is proposed. The increase of hardware complexity is minimal because a motion estimation engine is efficiently re-used for face tracking. Experimental results demonstrate that the facial area is well protected with the proposed scheme.

• The Journal of the Acoustical Society of Korea
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• v.29 no.5
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• pp.347-353
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• 2010

In VoIP system, the speech quality is seriously degraded due to packet loss, and the degree of degradation by each packet loss depends on the characteristics of the corresponding packet. Therefore, it is possible to improve the speech quality of VoIP by selectively controlling the packet to be lost during transmission based on the expected degradation by the loss of each packet. In this paper, a new scheme to improve speech quality of DiffServ-based VoIP by assigning priority to each packet is proposed, and a method to determine the priority of each packet is developed. The performance of proposed method was measured in packet loss environment based on Gilbert model, and it was verified both objectively and subjectively that the speech quality is improved by the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.129-137
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• 2010

In this paper, we propose a packet prioritization scheme using preamble signal and backoff time which is designed to provide a differentiated channel occupation with a packet priority in wireless sensor networks. This scheme aims at enabling QoS such as fast delivery of high priority packets by reducing their backoff time as well as thus securing higher channel occupation. We expect that it could also improve the channel utilization of the entire network by avoiding unnecessary channel contention. For the purpose, we add new features of multiple queue and preamble modification to the TinyOS based B-MAC. This scheme achieves 82-88% reduction in delivery time of high priority packets, thus it enables realtime support for urgent applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2333-2353
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• 2020

This paper proposes a novel data prioritization and transmission mechanism to minimize the number of packets transmitted and reduce network overload using the constrained application protocol (CoAP) in resource-constrained networks. The proposed scheme adopts four classification parameters to classify and prioritize data from a sensor. With the packet prioritization scheme, the sensed data having the lowest priority is only delivered using the proposed keep-alive message notification to decrease the number of packets transmitted. The performance evaluation demonstrates that the proposed scheme shows the improvement of resource utilization in energy consumption, and bandwidth usage compared with the existing CoAP methods. Furthermore, the proposed scheme supports quality-of-service (QoS) per packet by differentiating transmission delays regarding priorities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1435-1440
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• 2014

Nodes in WSNs must operate under limited energy resource. Controlling access to the channel in WSNs plays a key role in determining channel utilization and energy consumption. This paper introduces a priority-based time slot allocation protocol for hybrid TDMA/CSMA MAC in WSNs. This protocol combines both TDMA and CSMA techniques while introducing prioritization by (m,k)-firm constraint. The performance of this protocol is obtained through simulations for various number of nodes and show significant improvements in delay and packet delivery ratio compared to S-MAC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.733-750
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• 2019

Software Defined Networking (SDN) is a new network paradigm, allowing administrators to manage networks through central controllers by separating control plane from data plane. So, one or more controllers must locate outside switches. However, this separation may cause delay problems between controllers and switches. In this paper, we therefore propose a Priority-based Scheduling policy for OpenFlow (PSO) to reduce the delay of some significant traffic. Our PSO is based on packet prioritization mechanisms in both OpenFlow switches and controllers. In addition, we have prototyped and experimented on PSO using a network simulator (ns-3). From the experimental results, PSO has demonstrated low delay for targeted traffic in the out-of-brand control network. The targeted traffic can acquire forwarding rules with lower delay under network congestion in control links (with normalized load > 0.8), comparing to traditional OpenFlow. Furthermore, PSO is helpful in the in-band control network to prioritize OpenFlow messages over data packets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2793-2803
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• 2013

In H.264, three different data partition types are used, which have unequal importance to the reconstructed video quality. To improve the performance of H.264 video streaming transmission over IEEE 802.11e Wireless Local Area Networks, a prioritization mechanism that categorizes different partition types to different priority classes according to the calculated distortion within one Group of Pictures. In the proposed scheme, video streams have been encoded based on the H.264 codec with its data partition enabled. The dynamic scheduling scheme based on Enhanced Distributed Channel Access has been configured to differentiate the data partitions according to their distortion impact and the queue utilization ratio. Simulation results show that the proposed scheme improves the received video quality by 1dB in PSNR compared with the existing Enhanced Distributed Channel Access static mapping scheme.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.