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    Artificial Bee Colony 알고리즘을 적용한 Broadcast Scheduling 최적 설계

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    https://www.riss.kr/link?id=A82571606

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    The basic objective of broadcast scheduling is to get the smallest length TDMA frame, where many nodes are allowed to transmit simultaneously in a single time slot in a conflict-free manner. The secondary objective is to maximize the number of such transmissions for maximum use of the channel. An Artificial Bee Colony (ABC) with ranking strategy is proposed in this paper for the broadcast scheduling problem. Our proposed method is very efficient for generating initial and neighbor feasible solutions. We can get the best number of time slots and transmission utilization comparing to previous researches.
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    The basic objective of broadcast scheduling is to get the smallest length TDMA frame, where many nodes are allowed to transmit simultaneously in a single time slot in a conflict-free manner. The secondary objective is to maximize the number of such tr...

    The basic objective of broadcast scheduling is to get the smallest length TDMA frame, where many nodes are allowed to transmit simultaneously in a single time slot in a conflict-free manner. The secondary objective is to maximize the number of such transmissions for maximum use of the channel. An Artificial Bee Colony (ABC) with ranking strategy is proposed in this paper for the broadcast scheduling problem. Our proposed method is very efficient for generating initial and neighbor feasible solutions. We can get the best number of time slots and transmission utilization comparing to previous researches.

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    목차 (Table of Contents)

    • Abstract
    • 1. 연구의 배경 및 목적
    • 2. BSP 평가함수와 제약식
    • 3. ABC를 적용한 BSP 최적화 방법
    • 4. 실험 결과 및 분석
    • Abstract
    • 1. 연구의 배경 및 목적
    • 2. BSP 평가함수와 제약식
    • 3. ABC를 적용한 BSP 최적화 방법
    • 4. 실험 결과 및 분석
    • 5. 결론
    • 참고문헌
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    참고문헌 (Reference)

    1 Wu, "Solving optimum TDMA broadcast scheduling in mobile ad hoc networks:a competent permutation genetic algorithm approach" 152 (152): 780-788, 2005

    2 Ephremides, "Scheduling broadcasts in multihop radio networks" 38 : 456-460, 1990

    3 Wang, "PSO-based Hybrid Algorithm for Multi-objective TDMA Scheduling in Wireless Sensor Networks" 2007

    4 Wang, "Optimal Broadcast Scheduling in Packet Ratio Networks Using Mean Field Annealing" 15 (15): 250-260, 1997

    5 Karaboga, "On the performance of artificial bee colony algorithm" 8 (8): 687-697, 2008

    6 Chakraborty, "Genetic Algorithm to solve optimum TDMA transmission schedule in broadcast packet radio networks" 52 (52): 765-777, 2004

    7 Gunasekaran, "Efficient algorithms to solve Broadcast Scheduling problem in WiMAX mesh networks" 33 : 1325-1333, 2010

    8 Shen, "Broadcast scheduling in wireless sensor networks using fuzzy Hopfield neural network" 34 : 900-907, 2008

    9 Shi, "Broadcast scheduling in wireless multihop networks using a neuralnetwork- based hybrid algorithm" 18 : 765-771, 2005

    10 Yeo, "An efficient broadcast scheduling algorithm for TDMA ad-hoc networks" PERGAMON-ELSEVIER SCIENCE LTD 29 (29): 1793-1806, 2002

    1 Wu, "Solving optimum TDMA broadcast scheduling in mobile ad hoc networks:a competent permutation genetic algorithm approach" 152 (152): 780-788, 2005

    2 Ephremides, "Scheduling broadcasts in multihop radio networks" 38 : 456-460, 1990

    3 Wang, "PSO-based Hybrid Algorithm for Multi-objective TDMA Scheduling in Wireless Sensor Networks" 2007

    4 Wang, "Optimal Broadcast Scheduling in Packet Ratio Networks Using Mean Field Annealing" 15 (15): 250-260, 1997

    5 Karaboga, "On the performance of artificial bee colony algorithm" 8 (8): 687-697, 2008

    6 Chakraborty, "Genetic Algorithm to solve optimum TDMA transmission schedule in broadcast packet radio networks" 52 (52): 765-777, 2004

    7 Gunasekaran, "Efficient algorithms to solve Broadcast Scheduling problem in WiMAX mesh networks" 33 : 1325-1333, 2010

    8 Shen, "Broadcast scheduling in wireless sensor networks using fuzzy Hopfield neural network" 34 : 900-907, 2008

    9 Shi, "Broadcast scheduling in wireless multihop networks using a neuralnetwork- based hybrid algorithm" 18 : 765-771, 2005

    10 Yeo, "An efficient broadcast scheduling algorithm for TDMA ad-hoc networks" PERGAMON-ELSEVIER SCIENCE LTD 29 (29): 1793-1806, 2002

    11 Karaboga, "A powerful and efficient algorithm for numerical function optimization:artificial bee colony algorithm" 39 (39): 459-471, 2007

    12 Funabiki, "A gradual neural network algorithm for broadcast scheduling problems in packet radio networks" E82-A (E82-A): 815-824, 1999

    13 Liao, "A discrete version of particle swarm optimization for flowshop scheduling problems" 34 : 3099-3111, 2007

    14 Karaboga, "A comparative study of Artificial Bee Colony algorithm" 214 (214): 108-132, 2009

    15 Mao, "A TDMA scheduling scheme for many-to-one communications in wireless sensor networks" 30 : 863-872, 2007

    16 Chen, Wang, "A Novel Broadcast Scheduling Strategy using Factor Graphs and the Sum-Product Algorithm" 5 (5): 1241-1249, 2006

    17 Wang, "A Gradual Noisy Chaotic Neural Network for Solving the Broadcast Scheduling Problem in Packet Radio Networks" 17 (17): 989-1000, 2006

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    2021-01-01 등재 등재학술지 유지 (재인증) KCI등재
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    2016 0.59 0.59 0.62
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.63 0.63 0.998 0.07
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