• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3496-3514
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• 2015

One of the challenging tasks in Mobile Ad hoc Network is to discover precise optimal routing solution due to the infrastructure-less dynamic behavior of wireless mobile nodes. Ant Colony Optimization, a swarm Intelligence technique, inspired by the foraging behaviour of ants in colonies was used in the past research works to compute the optimal path. In this paper, we propose a Recurrent Ant Colony Optimization (RECACO) that executes the actual Ant Colony Optimization iteratively based on recurrent value in order to obtain an optimal path convergence. Each iteration involves three steps: Pheromone tracking, Pheromone renewal and Node selection based on the residual energy in the mobile nodes. The novelty of our approach is the inclusion of new pheromone updating strategy in both online step-by-step pheromone renewal mode and online delayed pheromone renewal mode with the use of newly proposed metric named ELD (Energy Load Delay) based on energy, Load balancing and end-to-end delay metrics to measure the performance. RECACO is implemented using network simulator NS2.34. The implementation results show that the proposed algorithm outperforms the existing algorithms like AODV, ACO, LBE-ARAMA in terms of Energy, Delay, Packet Delivery Ratio and Network life time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2231-2252
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• 2012

With the prevalence of diverse services-oriented applications, such as IPTV systems and on-line games, the current underlying communication networks face more and more challenges on the aspects of flexibility and adaptability. Therefore, an effective and efficient multicast routing mechanism, which can fulfill different requirements of different personalized services, is critical and significant. In this paper, we first define the neighbor gradient, which is calculated based on the weighted sum of attributes such as residual link capacity, normalized hop count, etc. Then two distributed multicast routing algorithms which are neighbor Gradient-based Multicast Routing for Static multicast membership (GMR-S) and neighbor Gradient-based Multicast Routing for Dynamic multicast membership (GMR-D), are proposed. GMR-S is suitable for static membership situation, while GMR-D can be used for the dynamic membership network environment. Experimental results demonstrate the effectiveness and efficiency of our proposed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3683-3703
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• 2018

Wireless sensor networks (WSNs) consist of set of sensor nodes. These sensor nodes are deployed in unattended area which are able to sense, process and transmit data to the base station (BS). One of the primary issues of WSN is energy efficiency. In many existing clustering approaches, initial centroids of cluster heads (CHs) are chosen randomly and they form unbalanced clusters, results more energy consumption. In this paper, an energy efficient clustering protocol to prevent unbalanced clusters based on firefly and midpoint algorithms called EEC-FM has been proposed, where midpoint algorithm is used for initial centroid of CHs selection and firefly is used for cluster formation. Using residual energy and Euclidean distance as the parameters for appropriate cluster formation of the proposed approach produces balanced clusters to eventually balance the load of CHs and improve the network lifetime. Simulation result shows that the proposed method outperforms LEACH-B, BPK-means, Park's approach, Mk-means, and EECPK-means with respect to balancing of clusters, energy efficiency and network lifetime parameters. Simulation result also demonstrate that the proposed approach, EEC-FM protocol is 45% better than LEACH-B, 17.8% better than BPK-means protocol, 12.5% better than Park's approach, 9.1% better than Mk-means, and 5.8% better than EECPK-means protocol with respect to the parameter half energy consumption (HEC).

• 스마트미디어저널
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• 제9권1호
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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.

• 융합신호처리학회논문지
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• 제15권4호
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• pp.155-161
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• 2014

본 논문에서는 비교적 밀도가 높게 전개되는 무선 센서네트워크에서 센서노드들의 에너지를 균형있게 소비할 수 있는 클러스터-기반 에너지 소비 균형을 위한 라우팅 프로토콜을 제안하였다. 본 프로토콜은 계층적 구조를 가지는 클러스터-기반으로 구현된다. 클러스터는 위치적으로 가까운 거리에 있는 센서노드들로 형성되며, 해당 클러스터 멤버들 중에서 잔류 에너지가 가장 높은 노드가 헤드노드로 선정된다. 경로 선정에서, 이웃하는 클러스터와 통신의 범위가 중첩되게 하여 그 공통영역 내에 있는 하나의 노드를 중계노드로 선택하여, 통신에너지 소비의 균형을 고려하여 노드들의 수명을 연장할 수 있게 하였다.

• 한국통신학회논문지
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• 제23권9A호
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• pp.2289-2304
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• 1998

For the performance analysis and traffic control of ATM networks carrying video sequences, need an appropriate video traffic model. In this paper, we propose a new traffic model for MPEG compressed videos which are widely used for any type of video applications at th emoment. The proposed modeling scheme uses scene-based traffic characteristics and considers the correlation between frames of consecutiv GOPs. Using a simple scene detection algorithm, scene changes are modeled by state transitions and the number of GOPs of a scene state is modeled by a geometric distirbution. Frames of a scene stte are modeled by mean I, P, and B frame size. For more accurate traffic modeling, quantization errors (residual bits) that the state transition model using mean values has are compensated by autoregressive processes. We show that our model very well captures the traffic chracteristics of the original videos by performance analysis in terms of autocorrelation, histogram of frame bits genrated by the model, and cell loss rate in the ATM multiplexer with limited buffers. Our model is able to perrorm translations between levels (i.e., GOP, frame, and cell levels) and to estimate very accurately the stochastic characteristics of the original videos by each level.

• 한국산업정보학회논문지
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• 제10권1호
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• pp.49-57
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• 2005

ATM 포럼은 ATM 네트워크에서 TCP 트래픽에게 MCR을 보장하고, 여분의 대역폭을 공정하게 공유할 수 있도록 GFR 서비스를 정의하였다 GFR 스위치 구현 방법은 F-GCRA 알고리즘과 프레임 전달 메커니즘으로 이루어진다. F-GCRA 알고리즘은 MCR 보장에 적합한 프레임을 분류한다. 프레임 전달 메커니즘은 F-GCRA의 분류 정보에 따라 프레임 단위로 셀을 저장하고, 스케줄링 기법에 따라 출력 단자로 저장된 셀을 전달한다 전역 임계값을 갖는 공유 버퍼로 이루어진 단순 GFR 메커니즘은 단순한 구조로 인해 구현이 용이 하지만, MCR를 보장하는데 충분치 않다고 알려져 있다 본 논문은 단순 GFR 메커니즘을 갖는 ATM 스위치에서 TCP 트래픽을 위한 GFR 서비스 성능을 평가한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 추계학술대회
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• pp.580-581
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• 2018

에너지 하베스팅 무선센서네트워크에서 end-to-end delay를 줄이기 위해 멀티홉 라우팅기법을 적용한 매체접근제어 프로토콜 들이 연구되었다. 실제 환경에서는 소비되는 에너지 보다 충분히 많은 에너지 수집이 어려운 상황이 많이 발생하게 된다. 따라서 멀티홉 전송에서 전력이 고갈되지 않고 노드들이 안정적으로 데이터를 릴레이 할 수 있도록 하는 MAC프로토콜의 설계가 요구된다. 본 논문에서는 네트워크 수명을 증가시키기 우해 잔여전력과 에너지 수집율에 따라 릴레이노드를 선택할 수 있는 전력효율적인 MAC프로토콜을 제안하고 시뮬레이션을 통해 그 성능을 비교분석하였다.

• ETRI Journal
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• 제42권2호
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• pp.230-238
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• 2020

Human-object interaction (HOI) detection is a popular computer vision task that detects interactions between humans and objects. This task can be useful in many applications that require a deeper understanding of semantic scenes. Current HOI detection networks typically consist of a feature extractor followed by detection layers comprising small filters (eg, 1 × 1 or 3 × 3). Although small filters can capture local spatial features with a few parameters, they fail to capture larger context information relevant for recognizing interactions between humans and distant objects owing to their small receptive regions. Hence, we herein propose a three-stream HOI detection network that employs a context convolution module (CCM) in each stream branch. The CCM can capture larger contexts from input feature maps by adopting combinations of large separable convolution layers and residual-based convolution layers without increasing the number of parameters by using fewer large separable filters. We evaluate our HOI detection method using two benchmark datasets, V-COCO and HICO-DET, and demonstrate its state-of-the-art performance.

• 상하수도학회지
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• 제31권3호
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• pp.237-248
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• 2017

The estimation method of economical leakage management target utilized upon planning business for improvement of revenue water ratio in South Korea is presented and applicability of methods developed in this study is assessed through application on site. With a consideration of revenue water ratio in application target area, estimation method of long-term economical leakage management target is applied. Three leakage reduction methods such as replacement of residual aged pipe, leakage investigation and restoration and water pressure management are applied with a consideration of characteristics of site. Due to difficulty of obtaining data, analysis of cost/benefit by leakage reduction methods is performed by applying method of leakages estimation equation among statistical methods. As a result of application, revenue water ratio corresponding to long-term economical leakage management target is 91.6 %.