支持入侵容忍的网络距离选举计算模型
doi: 10.3724/SP.J.1146.2012.01402
A Voter Model Supporting Intrusion-tolerance for Network Distance Estimation
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摘要: 为了增强非可信环境下网络坐标系统生存能力,该文重新解释了经典模型中锚节点作用力的物理意义,以锚节点信誉代替距离预测误差作为权值,提出了网络距离选举计算模型,并将其归结为l1损失函数优化问题求解。针对目标函数的不可微特性,基于增量次梯度算法搜索目标函数极优值,并利用比例控制器实现了迭代步长的负反馈控制。实验证明,在计算代价可接受的前提下,模型不仅实现了可信环境下更高的计算精度,而且体现了远较基准算法为优的入侵容忍能力,在严重非可信环境下仍能提供质量尚可的网络距离计算服务。Abstract: To enhance the survivability of Network Coordinate System (NCS) in un-trusted environment, the physical meaning of anchor nodes spring force in classic model is re-explained, weight vector is taken for anchor nodes reputations instead of their prediction errors. Thus a voter model is proposed for network distance prediction and this model is categorized as a kind of method to solve a l1-loss function minimizing problem. By taking the objective functions non-differentiability into consideration, the incremental sub-gradient descending algorithm is used to minimize this function, and a proportional regulator is used to control the iterative step factor with negative feedback. The experiments show that the proposed model is more accurate than classic model in trusted environment with acceptable computing cost. Furthermore, it can also estimate network distance with moderate accuracy in serious un-trusted environment, and shows a stronger intrusion-tolerance capability than classic model.
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