• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.7
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• pp.9-19
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• 2004

WLAN (Wireless Local Area Networks) needs error recovery and flow control schemes to support reliable multicast protocol. Limited wireless bandwidth, as well as queuing losses caused by the asymmetric wired/wireless interactions, demands more effective approaches for reducing packet losses. Moreover, since the wireless channel is a shared broadcast medium, if sender receives feedback information simultaneously from several receivers, the feedback delays data frame transmission of forward direction by introducing channel congestion and burden at the sender. Therefore, it is important to minimize the amount of feedback information from receivers. In this paper, we propose an ARS(Adaptive Redundancy Scheme) that combines FEC(Forward Error Correction) using channel state estimation and ARQ(Automatic Repeat Request) both to reduce the amount of feedback information and the number of retransmissions and to guarantee high data reliability in a WLAN multicast environment. Performance of the proposed scheme is evaluated by means of analysis and simulations in AWGN and Rayleigh fading channels. The results show that the proposed scheme reduces the amount of feedback information and the number of retransmissions and guarantees high data reliability, while keeping throughput efficiency similarly with the conventional FEC and ARQ scheme.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.311-318
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• 2021

With the rapid development of the Internet of Things(IoT) technology recently, multi-access edge computing(MEC) is emerged as a next-generation technology for real-time and high-performance services. High mobility of users between MECs with limited service areas is considered one of the issues in the MEC environment. In this paper, we consider a vehicle edge computing(VEC) environment which has a high mobility, and propose a task migration algorithm to decide whether or not to migrate and where to migrate using DQN, as a reinforcement learning method. The objective of the proposed algorithm is to improve the system throughput while satisfying QoS(Quality of Service) requirements by minimizing the difference between queueing delays in vehicle edge computing servers(VECSs). The results show that compared to other algorithms, the proposed algorithm achieves approximately 14-49% better QoS satisfaction and approximately 14-38% lower service blocking rate.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.12
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• pp.73-82
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• 2008

There are several approaches for reducing the ROB(Reorder Buffer) complexity in processors. The one technique that makes the simplest ROB ports relies on a distributed implementation that spreads the centralized ROB structure across the functional units(FUs). Each distributed buffers are decided on the size of them by workload of the functional units. The performance of the processor depends on the size of distributed ROB. However, most of previous works have depended on the simulation results to decide the optimsize of distributed ROB. In this Paper, we use an analytical model based on the M/M/1 Queuing theory to determine the optimum size of each distributed ROB. Our schemes are evaluated by using the simulation performed by the CPU2000 benchmarks. We are able to choose the optimum size of distributed ROB showing the 99.2% performance compared with existing superscalar processors. We can save 82% hardware resources in ports and reduce more than 30% of delay when ROB and distributed ROB proposed in this paper are designed by HDL.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.489-498
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• 2012

Recently, as the interest in Green IT is exponentially increased, EPON with sleep mode has been studied to reduce energy consumption in access network. In oder to guarantee cyclic sleep for ONU(Optical Network Units), EPON with sleep mode transmits upstream and downstream data at the same time. However, since conventional algorithms for sleep mode in EPON allocate bandwidth to each ONU according to upstream bandwidth request, the QoS of downstream data is not guaranteed when the offered load of OLT is larger than that of ONU. In this paper, we propose a bandwidth allocation algorithm for improving QoS in EPON with sleep mode. The proposed algorithm compares its size with an upstream request of ONU when a downstream buffer in the OLT exceeds a QoS threshold. And then it allocates selectively a bandwidth that satisfies the required QoS between the bandwidth request of ONU and OLT. Therefore, the proposed algorithm can save energy through cyclic sleep of ONUs while guaranteeing the QoS of up/downstream data. In order to evaluate the proposed algorithm, we perform simulation in terms of total sleep time of ONUs, queueing delay between OLT and ONU, and the utilization of allocated bandwidth at OLT through OPNET.