Mechanism and Analysis on Fine-Grain Gradient Sinking Model in Wireless Sensor Networks
基于精细化梯度的无线传感器网络汇聚机制及分析

Data sinking is one of the typical transmission patterns in WSN (wireless sensor network). There is inherent unbalanced traffic load distribution in such funnel like transmission. A case in hop-based sinking (HBS) model is found more intricate than simple thought that inner nodes burden more forwarding tasks, showing the inverse direction within the same hop level comparing with global trend. With global trend. With a simple weighted average mechanism, a continuous gradient parameter is introduced, which will be dedicated to instructing how to forward data to sink in place of hop count, namely fine-grain gradient sinking (FGS). Through traffic analysis and detailed simulation, in FGS model network turns out to be smoother on traffic load distribution and more efficient on data forwarding than that HBS model.