• 한국인터넷방송통신학회논문지
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• 제10권6호
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• pp.269-273
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• 2010

MMOG는 네트워크 가상 환경의 다양한 응용 중 하나이며, 수백 명 이상의 사용자들이 동시에 가상 세계에서 상호작용한다. P2P MMOG에서 대역폭 소비를 줄이기 위하여 VON 기법이 제안되었으며, Message Forwarding을 이용하여 성능을 개선한 Vorocast 기법도 있다. 본 논문에서는 Forwarding 모델 상에서 메시지를 발생하는 노드가 더 많은 이웃 노드들에게 위치 갱신 (Position Update) 메시지를 전달하는 방법으로써 적은 일관성이나 높은 지연성과 같은 문제를 개선한 동적 관심영역 (AOI : Area Of Interest) 관리기법을 제안한다. 제안 기법은 Direct-Connection 모델과 Vorocast 모델을 결합함으로써 기존의 기법과 비교해서 보다 높은 일관성을 제공하고 지연성을 감소시킨다. 시뮬레이션을 통하여 제안 기법의 성능을 보였다.

• ETRI Journal
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• 제35권1호
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• pp.41-50
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• 2013

Network Mobility (NEMO) handles mobility of multiple nodes in an aggregate manner as a mobile network. The standard NEMO suffers from a number of limitations, such as inefficient routing and increased handoff latency. Most previous studies attempting to solve such problems have imposed an extra signaling load and/or modified the functionalities of the main entities. In this paper, we propose a more secure and lightweight route optimization (RO) mechanism based on exploiting the firewall in performing the RO services on behalf of the correspondent nodes (CNs). The proposed mechanism provides secure communications by making an authorized decision about the mobile router (MR) home of address, MR care of address, and the complete mobile network prefixes underneath the MR. In addition, it reduces the total signaling required for NEMO handoffs, especially when the number of mobile network nodes and/or CNs is increased. Moreover, our proposed mechanism can be easily deployed without modifying the mobility protocol stack of CNs. A thorough analytical model and network simulator (Ns-2) are used for evaluating the performance of the proposed mechanism compared with NEMO basic support protocol and state-of-the-art RO schemes. Numerical and simulation results demonstrate that our proposed mechanism outperforms other RO schemes in terms of handoff latency and total signaling load on wired and wireless links.

• 대한전자공학회논문지TC
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• 제43권2호
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• pp.16-21
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• 2006

Internet Engineering Task Force(IETF)는 효율적인 이동성 지원을 위해 Hierarchical Mobile IPv6(HMIPv6)를 제안하였다. HMIPv6는 Mobility Anchor Point(MAP) 도메인 내에서 기존 Mobile IP(MIP)에서 모바일 노드의 이동시 마다 필수적이었던 시그널링 오버헤드와 Binding Update(BU)로 인한 지연을 줄 일수 있는 방법을 제공한다 하지만 MAP과 MAP사이를 이동하는 사용자에 대해서는 아무런 대비책을 제시하지 않고 있기 때문에 실시간 응용프로그램의 사용에 있어서 이 경우 상당한 지연이 발생한다. 본 논문은 MAP과 MAP사이를 이동하는 사용자에 대해서도 사용자의 통신에 대한 영향을 최소화할 수 있도록 핸드오프 지연시간을 단축할 수 있는 고속 핸드오프를 제안하고 수학적 모델을 통하며 기존의 HMIPv6와 비교하였다.

• Journal of Communications and Networks
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• 제18권4호
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• pp.610-618
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• 2016

A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

• 한국멀티미디어학회논문지
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• 제25권8호
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• pp.1075-1084
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• 2022

Internet of Things(IoT) has become a key available technology for efficiently implementing device to device(D2D) services in various domains such as smart home, healthcare, smart city, agriculture, energy, logistics, and transportation. A lightweight publish/subscribe(Pub/Sub) messaging protocol not only establishes data dissemination pattern but also supports connectivity between IoT devices and their applications. Also, a Pub/Sub broker is deployed to facilitate data exchange among IoT devices. A scalable edge-based publish/subscribe (Pub/Sub) broker overlay networks support latency-sensitive IoT applications. In this paper, we design a hypercube grid quorum(HGQ) for distributed Pub/Sub systems based IoT applications. In designing HGQ, the network of hypercube structures suitable for the publish/subscribe model is built in the edge layer, and the proposed HGQ is designed by embedding a mesh overlay network in the hypercube. As their applications, we propose an HGQ-based mechansim for dissemination of the data of sensors or the message/event of IoT devices in IoT environments. The performance of HGQ is evaluated by analytical models. As the results, the latency and load balancing of applications based on the distributed Pub/Sub system using HGQ are improved.

• 대한임베디드공학회논문지
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• 제18권1호
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• pp.31-40
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• 2023

Recent advances in flash technologies, such as 3D processing and multileveling schemes, have successfully increased the flash capacity. Unfortunately, these technology advances significantly degrade flash's reliability due to a smaller cell geometry and a finer-grained cell state control. In this paper, we propose an asymmetric BER-aware reliability optimization technique (aBARO), new flash optimization that improves the flash reliability. To this end, we first reveal that bit errors of 3D NAND flash memory are highly skewed among flash cell states. The proposed aBARO exploits the unique per-state error model in flash cell states by selecting the most error-prone flash states and by forming narrow threshold voltage distributions (for the selected states only). Furthermore, aBARO is applied only when the program time (tPROG) gets shorter when a flash cell becomes aging, thereby keeping the program latency of storage systems unchanged. Our experimental results with real 3D MLC and TLC flash devices show that aBARO can effectively improve flash reliability by mitigating a significant number of bit errors. In addition, aBARO can also reduce the read latency by 40%, on average, by suppressing the read retries.

• Journal of information and communication convergence engineering
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• 제7권2호
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• pp.199-202
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• 2009

Adaptive memory management is a serious issue in data stream management. Data stream differ from the traditional stored relational model in several aspect such as the stream arrives online, high volume in size, skewed data distributions. Data skew is a common property of massive data streams. We propose the predicted allocation strategy, which uses predictive processing to cope with time varying data skew. This processing includes memory usage estimation and indexing with timestamp. Our experimental study shows that the predictive strategy reduces both required memory space and latency time for skewed data over varying time.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2018년도 춘계 종합학술대회 논문집
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• pp.511-512
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• 2018

Virtual machine technology enables multiple hosts to share the same LUN(Logical Unit Number) and the same storage, but if too many hosts share the same LUN, it will increase the delay. In this paper we propose a performance model, get several values of scalable storage performance in virtual environment, and present the results examined the effects of I/O queuing in a virtual infrastructure. This results show how to make the most effective use of our storage resources.

• 동의신경정신과학회지
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• 제10권1호
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• pp.17-38
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• 1999

The effects of Sahyangsohapwon on the affective reactivity of rats were studied with open-field behavior. Sample group was treated with the medicine for 8 weeks, whereas control group was treated with the vehicle. The effects of Sahyangsohapwon on the enhancement of learning and memory of AD model rats were studied with two-way avoidance task. Sample group electrically lesioned on nbM(nucleus basalis of Meynert) was treated with the medicine for 8 weeks, whereas control group with nbM lesion and sham group with the sham operation were treated with the vehicle. 1. In the open-field behavior task, the start latency from start box was measured $27.08{\pm}7.51sec$ in control group, $23.15{\pm}5.98sec$ in sample group. Rats in sample group showed a tendency of shortened latency going out to a strange place compared with those in control group, but with no statistical significance(p>0.05). 2. In the open-field behavior task, the number of locomotion crossing the grid lines was measured $84.54{\pm}3.55$ in control group, $116.93{\pm}6.41$ in sample group. There was an increased locomotion in sample group compared with control group with statistical significance(p<0.01). This can be interpreted as rats in sample group showed lowerd anxiety under a strange environment. 3. In the open-field behavior task, the rearing number was measured $7.46{\pm}0.57$ in control group, $10.13{\pm}0.95$ in sample group. There was an increased rearing in sample group compared with control group with statistical significance(p<0.05). This can also be interpreted as rats in sample group showed lowerd anxiety under a strange environment. 4. In the open-field behavior task, the number of crossing behavior was measured $5.54{\pm}1.50$ in control group, $9.20{\pm}1.67$ in sample group. There was a increasing tendency of crossing behavior in sample group compared with control group, but with no statistical significance(p<0.05). 5. In the open-field behavior task, the total activity was measured $97.54{\pm}4.70$ in control group, $136.27{\pm}792$ in sample group. There was an increased total activity in sample group compared with control group with statistical significance(p<0.01). This can also be interpreted as rats in sample group showed lowerd anxiety under a strange environment. 6. In the analysis of effects on the learning and memory in AD model rats with two-way avoidance task, the response latency was measured $6717{\pm}134msec$ in the 1st session, $5416{\pm}160msec$ in the 2nd session, $5252{\pm}148msec$ in the 3rd session in control group. It was measured $6724{\pm}155msec$ in the 1st session, $4642{\pm}139msec$ in the 2nd session, $4914{\pm}148msec$ in the 3rd session in sample group and $4357{\pm}144msec$ in the 1st session, $3125{\pm}115msec$ in the 2nd session, $3091{\pm}98msec$ in the 3rd session in sham group. There were differences between sham group and nbM lesioned groups with statistical significance in post hoc analysis(p<0.000). And in the 2nd session, there was a reduction of latency in sample group compared with control group with statistical significance (p<0.000). This showed that sample group had better learning capacity than control group. 7. In the analysis of effects on the learning and memory in AD model rats with two-way avoidance task, the number of avoidance response was measured $5.85{\pm}1.41$ in the 1st session, $14.23{\pm}2.89$ in the 2nd session, $15.69{\pm}2.56$ in the 3rd session in control group. It was measured $7.92{\pm}1.94$ in the 1st session, $16.83{\pm}2.29$ in the 2nd session, $15.42{\pm}2.81$ in the 3rd session in sample group and $14.38{\pm}1.62$ in the 1st session, $22.88{\pm}0.89$ in the 2nd session, $23.88{\pm}1.64$ in the 3rd session in sham group. There were differences between sham group and nbM lesioned groups with statistical significance in post hoc analysis(p<0.001). But between control and sample group, there was no significant difference. With the experimental results above, Sahyangsohapwon can be supposed to have the enhancing effects on the affect reactivity and learning with memory of AD model rats induced by electrolyte injury of nbM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1188-1203
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• 2020

The human expression contains a lot of information that can be used to detect complex conditions such as pain and fatigue. After deep learning became the mainstream method, the traditional feature extraction method no longer has advantages. However, in order to achieve higher accuracy, researchers continue to stack the number of layers of the neural network, which makes the real-time performance of the model weak. Therefore, this paper proposed an expression recognition framework based on densely concatenated convolutional neural networks to balance accuracy and latency and apply it to humanoid robots. The techniques of feature reuse and parameter compression in the framework improved the learning ability of the model and greatly reduced the parameters. Experiments showed that the proposed model can reduce tens of times the parameters at the expense of little accuracy.