• 제목/요약/키워드: Efficient Network selection algorithm

검색결과 132건 처리시간 0.02초

A Bandwidth Adaptive Path Selection Scheme in IEEE 802.16 Relay Networks

  • Lee, Sung-Hee;Ko, Young-Bae
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제5권3호
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    • pp.477-493
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    • 2011
  • The IEEE 802.16 mobile multi-hop relay (MMR) task group 'j' (TGj) has introduced the multi-hop relaying concept in the IEEE 802.16 Wireless MAN, wherein a relay station (RS) is employed to improve network coverage and capacity. Several RSs can be deployed between a base station and mobile stations, and configured to form a tree-like multi-hop topology. In such architecture, we consider the problem of a path selection through which the mobile station in and outside the coverage can communicate with the base station. In this paper, we propose a new path selection algorithm that ensures more efficient distribution of resources such as bandwidth among the relaying nodes for improving the overall performance of the network. Performance of our proposed scheme is compared with the path selection algorithms based on loss rate and the shortest path algorithm. Based on the simulation results using ns-2, we show our proposal significantly improves the performance on throughput, latency and bandwidth consumption.

The Improved Energy Efficient LEACH Protocol Technology of Wireless Sensor Networks

  • Shrestha, Surendra;Kim, Young Min;Jung, Kyedong;Lee, Jong-Yong
    • International Journal of Internet, Broadcasting and Communication
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    • 제7권1호
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    • pp.30-35
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    • 2015
  • The most important factor within the wireless sensor network is to have effective network usage and increase the lifetime of the individual nodes in order to operate the wireless network more efficiently. Therefore, many routing protocols have been developed. The LEACH protocol presented by Wendi Hein Zelman, especially well known as a simple and efficient clustering based routing protocol. However, because LEACH protocol in an irregular network is the total data throughput efficiency dropped, the stability of the cluster is declined. Therefore, to increase the stability of the cluster head, in this paper, it proposes a stochastic cluster head selection method for improving the LEACH protocol. To this end, it proposes a SH-LEACH (Stochastic Cluster Head Selection Method-LEACH) that it is combined to the HEED and LEACH protocol and the proposed algorithm is verified through the simulation.

무선 센서 네트워크상에서 센서간의 밀도를 고려한 클러스터 헤드 선정 알고리즘 (A Cluster Head Selection Algorithm Adopting Sensor Density on Wireless Sensor Networks)

  • 정의현;이성호;박용진;황호영;허문행
    • 정보처리학회논문지C
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    • 제13C권6호
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    • pp.741-748
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    • 2006
  • 센서 기술의 발전으로 무선 센서 네트워크는 빠르게 발전하고 있으며, 다양한 분야의 적용이 예상되고 있다. 무선 센서 네트워크에서 가장 중요한 요소 중의 하나는 네트워크를 에너지 효율적으로 운용하는 것이다. 이러한 목적을 위해 에너지 효율적인 라우팅 프로토콜에 대한 많은 연구가 진행되고 있다. 본 논문에서는 LEACH-C에서 제안한 클러스터 헤드 선정 알고리즘에 노드들의 밀도를 같이 고려한 향상된 클러스터 헤드 선정 알고리즘을 제안하고 시뮬레이션 하였다. 제안된 알고리즘은 LEACH-C와 실행 속도는 거의 유사하면서 11% 이상의 성능 향상 결과를 제공하였다. 본 논문의 시뮬레이션 결과는 클러스터 헤드 선정 시에 헤드와 다른 노드들 간의 거리 뿐 아니라 밀도를 고려하는 것이 센서네트워크의 에너지 이용에 보다 효율적임을 보여주었다.

Efficient Message Scheduling for WDM Optical Networks with Minimizing Flow Time

  • Huang, Xiaohong;Ma, Maode
    • Journal of Communications and Networks
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    • 제6권2호
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    • pp.147-155
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    • 2004
  • In this paper, we propose an efficient sequencing technique, namely minimum Row time scheduling (MFTS), to manage variable-Iength message transmissions for single-hop passive starcoupled WDM optical networks. By considering not only the message length but also the state of the receivers and the tuning latency, the proposed protocol can reduce the average delay of the network greatly. This paper also introduces a new channel assignment technique latency minimizing scheduling (LMS), which aims to reduce the scheduling latency. We evaluate the proposed algorithm, using extensive discrete-event simulations, by comparing its performance with shortest job first (SJF) algorithm. We find that significant improvement in average delay could be achieved by MFTS algorithm. By combining the proposed message sequencing technique with the channel selection technique, the performance of the optical network could be further improved.

무선 센서 네트워크에서의 에너지 효율적인 클러스터 헤드 선출 알고리즘 (ECS : Energy efficient Cluster-head Selection algorithm in Wireless Sensor Network)

  • 최경진;윤명준;심인보;이재용
    • 한국통신학회논문지
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    • 제32권6B호
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    • pp.342-349
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    • 2007
  • 무선 센서 네트워크에서 클러스터링은 클러스터 헤드(cluster head) 노드가 클러스터 멤버 노드의 데이터를 병합(aggreation)하여 싱크(Sink)로 전송함으로써 노드 간 통신의 양을 줄이게 하고 클러스터 내부적으로는 TDMA 스케줄에 기반하여 클러스터 헤드가 클러스터 멤버 노드의 스케줄을 조정함으로써 노드의 슬립타임을 연장하게 한다. 제안하는 ECS(Energy efficient Cluster-head Selection) 알고리즘은 에너지가 제한되는 센서 네트워크의 수명 향상을 위하여 노드 자신의 요소(factor) 즉, 자신의 초기 에너지 및 현재 에너지, 클러스터 헤드에 의해 병합된 클러스터 내 노드들의 데이터가 싱크로 전송되는 각 라운드, 노드 자신이 클러스터 헤드로 선출(selection) 된 수를 이용하여 확률적인 방법으로 클러스터 헤드를 자가 선출한다.

무선 센서 네트워크에서 에너지 효율적 클러스터 헤드 선정 기법 (Energy-Efficient Cluster Head Selection Method in Wireless Sensor Networks)

  • 남춘성;장경수;신호진;신동렬
    • 한국인터넷방송통신학회논문지
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    • 제10권2호
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    • pp.25-30
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    • 2010
  • 무선 센서 네트워크는 제한된 자원을 가지고 특정한 지역에 임의로 뿌려진 센서 노드가 자가 구성적으로 형성하는 네트워크를 말한다. 센서 네트워크의 확장성(scalability), 로드 밸런싱(load balancing) 그리고 네트워크 라이프타임(network lifetime)을 보장하기 위해서 네트워크를 지역적으로 관리하는 클러스터링 알고리즘이 필요하다. 이전의 클러스터링 알고리즘에서 클러스터 헤드를 선정할 때 노드의 위치 및 에너지를 알아내기 위해 추가적인 통신비용이 발생하고, 클러스터 간 불균형이 클러스터 헤드에게 과부하를 유발한다. 따라서 본 논문은 이러한 문제점들을 해결하기 위해 추가적인 통신비용과 클러스터 불균형을 고려하는 새로운 클러스터 헤드 선정 알고리즘을 제안한다. 제안된 알고리즘은 실험결과를 통해 기존의 방법보다 에너지 측면에서 효율적임을 보여준다.

Effective Hand Gesture Recognition by Key Frame Selection and 3D Neural Network

  • Hoang, Nguyen Ngoc;Lee, Guee-Sang;Kim, Soo-Hyung;Yang, Hyung-Jeong
    • 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.

Error Estimation Method for Matrix Correlation-Based Wi-Fi Indoor Localization

  • Sun, Yong-Liang;Xu, Yu-Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권11호
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    • pp.2657-2675
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    • 2013
  • A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

Global Optimization for Energy Efficient Resource Management by Game Based Distributed Learning in Internet of Things

  • Ju, ChunHua;Shao, Qi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권10호
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    • pp.3771-3788
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    • 2015
  • This paper studies the distributed energy efficient resource management in the Internet of Things (IoT). Wireless communication networks support the IoT without limitation of distance and location, which significantly impels its development. We study the communication channel and energy management in the wireless communication network supported IoT to improve the ability of connection, communication, share and collaboration, by using the game theory and distributed learning algorithm. First, we formulate an energy efficient neighbor collaborative game model and prove that the proposed game is an exact potential game. Second, we design a distributed energy efficient channel selection learning algorithm to obtain the global optimum in a distributed manner. We prove that the proposed algorithm will asymptotically converge to the global optimum with geometric speed. Finally, we make the simulations to verify the theoretic analysis and the performance of proposed algorithm.

CASPER: Congestion Aware Selection of Path with Efficient Routing in Multimedia Networks

  • Obaidat, Mohammad S.;Dhurandher, Sanjay K.;Diwakar, Khushboo
    • Journal of Information Processing Systems
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    • 제7권2호
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    • pp.241-260
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    • 2011
  • In earlier days, most of the data carried on communication networks was textual data requiring limited bandwidth. With the rise of multimedia and network technologies, the bandwidth requirements of data have increased considerably. If a network link at any time is not able to meet the minimum bandwidth requirement of data, data transmission at that path becomes difficult, which leads to network congestion. This causes delay in data transmission and might also lead to packet drops in the network. The retransmission of these lost packets would aggravate the situation and jam the network. In this paper, we aim at providing a solution to the problem of network congestion in mobile ad hoc networks [1, 2] by designing a protocol that performs routing intelligently and minimizes the delay in data transmission. Our Objective is to move the traffic away from the shortest path obtained by a suitable shortest path calculation algorithm to a less congested path so as to minimize the number of packet drops during data transmission and to avoid unnecessary delay. For this we have proposed a protocol named as Congestion Aware Selection Of Path With Efficient Routing (CASPER). Here, a router runs the shortest path algorithm after pruning those links that violate a given set of constraints. The proposed protocol has been compared with two link state protocols namely, OSPF [3, 4] and OLSR [5, 6, 7, 8].The results achieved show that our protocol performs better in terms of network throughput and transmission delay in case of bulky data transmission.