张胜, 姚明辉, 黄毅, 刘颖. 基于层次分析法的机会网络移动模型评价探索[J]. 南昌航空大学学报(自然科学版), 2017, 31(3): 15-22,55. DOI: 10.3969/j.issn.1001-4926.2017.03.003
引用本文: 张胜, 姚明辉, 黄毅, 刘颖. 基于层次分析法的机会网络移动模型评价探索[J]. 南昌航空大学学报(自然科学版), 2017, 31(3): 15-22,55. DOI: 10.3969/j.issn.1001-4926.2017.03.003
Zhang Sheng, Yao Ming-hui, Huang Yi, Liu Ying. An Exploration of Evaluation of Mobility Model based on Analytic Hierarchy Process in Opportunistic Network[J]. Journal of nanchang hangkong university(Natural science edition), 2017, 31(3): 15-22,55. DOI: 10.3969/j.issn.1001-4926.2017.03.003
Citation: Zhang Sheng, Yao Ming-hui, Huang Yi, Liu Ying. An Exploration of Evaluation of Mobility Model based on Analytic Hierarchy Process in Opportunistic Network[J]. Journal of nanchang hangkong university(Natural science edition), 2017, 31(3): 15-22,55. DOI: 10.3969/j.issn.1001-4926.2017.03.003

基于层次分析法的机会网络移动模型评价探索

An Exploration of Evaluation of Mobility Model based on Analytic Hierarchy Process in Opportunistic Network

  • 摘要: 移动模型是机会网络基础研究之一。移动模型的好坏直接影响到路由算法和网络拓扑结构。在分析影响移动模型质量的主要因素以及相互关系的基础之上,提出了移动模型评价指标体系;以层次分析法理论为基础提出了量化的移动模型评估方法。首先,将模型评价分为目标层,准则层,方案层;其次,求得每一层元素对上一层元素的权重;最后,通过加权和的方法求得方案层对目标层的最终权重,从而得出不同模型的排序。该方法实现了对移动模型的量化评估,不仅为移动模型评价提供新的思路和方法,而且为移动节点建模提供帮助和保证。最后,以经典随机移动模型random Gauss-Markov(GM),random waypoint model(RWP),random walk model(RW),random direction model(RD)为例验证了评价方法的有效性。

     

    Abstract: Mobility model is one of the basic researches of opportunistic network. The quality of the mobility model has a direct impact on the routing algorithm and network topology. Based on the analysis of the main factors affecting the quality of mobility model and their relationship, evaluation index system of mobility model is proposed. Based on the analytic hierarchy process (AHP), a quantitative evaluation method of mobility model is proposed. First of all, the model evaluation is divided into target layer, criterion layer and scheme layer. Secondly, the weight of each element on the upper layer is obtained. Finally, the weighted sum method is used to obtain the final weight of the scheme layer to the target layer, so as to obtain the sorting of different models. This method realizes the quantitative evaluation of the mobility model. It not only provides new ideas and methods for mobility model evaluation, but also provides help and guarantee for mobile node modeling. Finally, the validity of the evaluation method is validated by taking the classic random mobility model (random Gauss-Markov (GM), random waypoint model (RWP), random walk model (RW), random direction model (RD)) as an example.

     

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