论文部分内容阅读
多点中继(MPR)是移动自组网中用来降低网络开销所采用的一种机制,但由于最小MPR集的选取属于NP完全问题,传统的贪心算法往往难以取得较好的结果.本文将蚁群优化用于最小MPR集选取问题的求解,给出了一种基于候选解的改进蚁群算法CSACO.通过使用候选解集进行信息素的更新,提高了算法的收敛速度,同时避免了算法陷入早熟.模拟实验表明,CSACO可以有效降低MPR集的大小,同时在较短的时间内收敛到最优解,提高网络性能.
Multipoint relay (MPR) is a mechanism used to reduce network overhead in mobile ad hoc networks. However, since the selection of the minimum MPR set belongs to the NP complete problem, the traditional greedy algorithm is often difficult to obtain good results. The ant colony optimization is used to solve the minimum MPR set selection problem, and an improved ant colony algorithm CSACO based on candidate solution is proposed. By using the candidate solution set to update the pheromone, the convergence speed of the algorithm is improved, The algorithm gets into precocity.Modeling experiments show that CSACO can effectively reduce the size of MPR set and converge to the optimal solution in a short time and improve the network performance.