计算机工程
計算機工程
계산궤공정
COMPUTER ENGINEERING
2015年
5期
38-44,55
,共8页
云计算%MapReduce分布式编程%蚁群优化%航路规划%无人机%Hadoop分布式文件系统
雲計算%MapReduce分佈式編程%蟻群優化%航路規劃%無人機%Hadoop分佈式文件繫統
운계산%MapReduce분포식편정%의군우화%항로규화%무인궤%Hadoop분포식문건계통
cloud computing%MapReduce distributed programming%Ant Colony Optimization(ACO)%route planning%Unmanned Aerial Vehicle(UAV)%Hadoop Distributed File System(HDFS)
航路规划是提高无人机生存能力的有效途径，可使其安全、快速到达目的地。为在云计算环境中分布式并行地求解航路规划问题，应用云计算技术提出基于MapReduce和多目标蚁群算法的航路规划算法( RPMA)。设计多目标蚁群算法，并采用多种优化策略对传统算法进行改进。 RPMA能预先规划出多条航迹，可根据不同的飞行任务选择不同的航路，并在飞行过程中根据不同需要临时确定合适的飞行航路。仿真实验结果表明， RPMA求解航路问题是可行、有效的，具有较好的收敛性和扩展性，以及对大规模数据的处理能力。
航路規劃是提高無人機生存能力的有效途徑，可使其安全、快速到達目的地。為在雲計算環境中分佈式併行地求解航路規劃問題，應用雲計算技術提齣基于MapReduce和多目標蟻群算法的航路規劃算法( RPMA)。設計多目標蟻群算法，併採用多種優化策略對傳統算法進行改進。 RPMA能預先規劃齣多條航跡，可根據不同的飛行任務選擇不同的航路，併在飛行過程中根據不同需要臨時確定閤適的飛行航路。倣真實驗結果錶明， RPMA求解航路問題是可行、有效的，具有較好的收斂性和擴展性，以及對大規模數據的處理能力。
항로규화시제고무인궤생존능력적유효도경，가사기안전、쾌속도체목적지。위재운계산배경중분포식병행지구해항로규화문제，응용운계산기술제출기우MapReduce화다목표의군산법적항로규화산법( RPMA)。설계다목표의군산법，병채용다충우화책략대전통산법진행개진。 RPMA능예선규화출다조항적，가근거불동적비행임무선택불동적항로，병재비행과정중근거불동수요림시학정합괄적비행항로。방진실험결과표명， RPMA구해항로문제시가행、유효적，구유교호적수렴성화확전성，이급대대규모수거적처리능력。
Route planning is an effective way to improve the ability to survive of Unmanned Aerial Vehicle( UAV) ,for which can make the UAV reach the destination safely and fast. In this paper, the route planning algorithm based on MapReduce and multi-objective Ant Colony Optimization ( ACO ) is put forward, which named RPMA. The multi-objective ACO algorithm is designed in the RPMA and different varieties of optimization strategies are used to improve the RPMA. The RPMA uses cloud computing technology and makes it solve the route planning problems in distributed cloud computing environment and parallel technology. A number of paths are planned in advance. The RPMA is able to make the UAV choose different routes according to different missions or choose the appropriate route according to different temporary needs. The preferable result is got in the simulation experiment,which indicates that the RPMA is an efficient way to solve the route planning problems and has the qualities of convergence and scalability. In addition,the RPMA has the handling abilities of large-scale data.
