CAJ | 학술논문

在蚁群算法基础上引入模糊理论的概念，提出基于模糊理论和蚁群BFTAC（ Based on Fuzzy Theory and Ant Colony）的路由算法。 BFTAC算法前向蚂蚁在路径探索中，通过模糊综合评判法选择下一跳节点；信息素更新过程中，成功到达汇聚节点转化的后向蚂蚁根据对应的前向蚂蚁携带的网络信息增强路径信息素，而未成功到达的要削弱信息素；数据传输时，采用低能量节点休眠工作机制，以此达到均衡网络节点的能耗的目的。仿真实验表明，与基于能量有效蚁群算法（ EEABR ）进行比较，相同条件下BFTAC算法有效地减少了网络平均能量消耗，增强了网络节点的存活率。
재의군산법기출상인입모호이론적개념，제출기우모호이론화의군BFTAC（ Based on Fuzzy Theory and Ant Colony）적로유산법。 BFTAC산법전향마의재로경탐색중，통과모호종합평판법선택하일도절점；신식소경신과정중，성공도체회취절점전화적후향마의근거대응적전향마의휴대적망락신식증강로경신식소，이미성공도체적요삭약신식소；수거전수시，채용저능량절점휴면공작궤제，이차체도균형망락절점적능모적목적。방진실험표명，여기우능량유효의군산법（ EEABR ）진행비교，상동조건하BFTAC산법유효지감소료망락평균능량소모，증강료망락절점적존활솔。
Based on ant colony algorithm we introduced the concept of fuzzy theory, and proposed a routing algorithm which is based on fuzzy theory and ant colony.In the algorithm, the forward ant selects the next hop node using fuzzy comprehensive evaluation method when exploring the path.In the update process of pheromone, the backward ants whom successfully reach the aggregation node and converted will enhance the path pheromones according to the network information carried by the forward ants, while whom failed to reach have to weaken the pheromone.In data transmission the algorithm uses low energy nodes dormant working mechanism to achieve the goal of balancing the energy consumption of network nodes.Simulation results showed that comparing with energy-efficient ant-based routing ( EEABR) algorithm, this algorithm effectively reduced the average energy consumption of the network and enhanced the survival of network nodes under the same condi-tions.