采用主成分策略的传感器网络路由评估算法
发布时间：2018-07-20 21:04
【摘要】：针对传感器网络路由在最优性评估过程中呈现的排序问题,提出了一种采用主成分策略的路由评估算法(OREPCA)。首先利用蚁群策略寻找传感器网络中的样品路由;接着再根据实际的布网环境构建出相应的路由评价指标集;然后对样品路由按指标集中各指标出现的顺序进行逐项打分获得评价指标向量;最后借助主成分策略构造一个传输路由综合评价指标函数,从而实现在不同的监测环境中对网络路由的多元化评价,规避了人为选取权重因子带来的主观随意性。仿真结果表明,与基于负载均衡策略的路由优化算法及基于多目标优化的交互式路由算法相比,OREPCA算法能将网络寿命提高14%,并能有效降低网络的通信延迟。
[Abstract]:A routing evaluation algorithm (OREPCA) based on principal component strategy (PCA) is proposed to solve the scheduling problem of sensor network routing in the process of optimality evaluation. First, the ant colony strategy is used to find the sample routing in sensor networks, and then the corresponding routing evaluation index set is constructed according to the actual network environment. Then, the sample routing is graded according to the order of each index in the index set, and the evaluation index vector is obtained. Finally, a comprehensive evaluation index function of transmission route is constructed by means of the principal component strategy. In order to realize the diversified evaluation of network routing in different monitoring environments, the subjective randomness brought by the artificial selection of weight factors is avoided. The simulation results show that the OREPCA algorithm can increase the network lifetime by 14% and reduce the communication delay effectively compared with the load balancing strategy and the interactive routing algorithm based on multi-objective optimization.
【作者单位】： 河南师范大学数学与信息科学学院;西安电子科技大学数学与统计学院;
【基金】：国家自然科学基金资助项目(61373174,U1404105) 河南省科技攻关计划资助项目(142102210058) 河南省高等学校重点科研资助项目(16A510006) 河南师范大学青年基金资助项目(2015QK02,2013QK02)
【分类号】：TN929.5;TP212.9
，
本文编号：2134770
[Abstract]:A routing evaluation algorithm (OREPCA) based on principal component strategy (PCA) is proposed to solve the scheduling problem of sensor network routing in the process of optimality evaluation. First, the ant colony strategy is used to find the sample routing in sensor networks, and then the corresponding routing evaluation index set is constructed according to the actual network environment. Then, the sample routing is graded according to the order of each index in the index set, and the evaluation index vector is obtained. Finally, a comprehensive evaluation index function of transmission route is constructed by means of the principal component strategy. In order to realize the diversified evaluation of network routing in different monitoring environments, the subjective randomness brought by the artificial selection of weight factors is avoided. The simulation results show that the OREPCA algorithm can increase the network lifetime by 14% and reduce the communication delay effectively compared with the load balancing strategy and the interactive routing algorithm based on multi-objective optimization.
【作者单位】： 河南师范大学数学与信息科学学院;西安电子科技大学数学与统计学院;
【基金】：国家自然科学基金资助项目(61373174,U1404105) 河南省科技攻关计划资助项目(142102210058) 河南省高等学校重点科研资助项目(16A510006) 河南师范大学青年基金资助项目(2015QK02,2013QK02)
【分类号】：TN929.5;TP212.9
，
本文编号：2134770
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