# Two-Tier Cooperation Based High-Reliable and Lightweight Forwarding Strategy in Heterogeneous WBAN
## 3 Two-Tier Collaboration Based High-Reliable and Lightweight Forwarding (TTCF) Mechanism for WBAN
### Forwarding Model Based on Multi Factor Dynamic Fusion in TTCF  
(1) Forwarding Decision Factors and Utility  
Although reducing the amount of transmitted data can reduce the energy consumption of medical physiological data forwarding to a certain extent, the actual energy consumption of WBAN data forwarding is also affected by many other important factors such as residual energy of sensors, sampling frequency, and the nodal status in the network, which have essentially different effects on forwarding. The main reason is that most sensor nodes in WBAN have heterogeneous structures, and the energy consumption ratio of heterogeneous devices is different, so the contribution of each factor to sensor energy consumption and its relay capability is also different. For example, among the different types of medical data collected by WBAN sensors, vital data such as ECG and blood pressure must always be guaranteed, while information such as body temperature can be interrupted or delayed. That is, the importance of medical data collected by different sensors varies greatly, and the residual energy of sensors carrying important data must be kept at a high enough level to deal with emergencies. Thus, such nodes are not suitable to be used as relays; namely, they will not play a prominent role in WBAN data forwarding. Similarly, sensor nodes with higher sampling frequency usually consume more energy, so such nodes are not suitable for relay. That is, the sampling frequency of sensors is proportional to its energy consumption and inversely proportional to its forwarding capacity. Therefore, it is not accurate to directly use the above factors to evaluate the forwarding capability of relay nodes. Moreover, as a special carrier of WBAN, the human body is always in the state of lying, sitting, standing, walking and different limb movements, which make WBAN maintain a dynamic environment. Meanwhile, due to the particularity of medical applications, some data acquisition can be completed soon, but there is still energy in these nodes, which can provide data forwarding services for other nodes. Thus, priority should be given to using their residual energy to make use of the residual energy of these nodes as early as possible, which can effectively improve the overall energy-saving effect of WBAN data forwarding and prolong its life. Therefore, considering the main factors affecting the energy consumption of medical sensors, combined with the different motion states of the human body, the research on the WBAN data forwarding model will be more in line with the needs of actual medical applications. On the basis of Section 3.1 and on the premise of making full use of the nodes that will exit the network, this section takes the influence factors of sensor's sampling frequency, residual energy and its importance in the network as a decision-making value to measure the basic forwarding capacity of dynamic WBAN relay nodes, and selects the highest value as the best relay, so as to achieve the balance of the sensor energy consumption, extension of network life, and WBAN energy-saving transmission scheme with high forwarding efficiency. _Firstly_, for the nodes that are about to exit the network, different characteristic flags are set for them to have a higher forwarding priority. The process is as follows. Add the working time attribute \(t_{j}\) to node \(j\). When \(t_{j}\) reaches the expected working time \(T_{j}\), node \(j\) only forwards data. Therefore, when a node sends a status message, it judges the time parameter. If \(t_{j}>T_{j}\), the residual energy influence factor value of node \(j\) is set to the maximum value 1, so that it can be selected as a relay node first. _Then_, an appropriate mathematical model is constructed for each forwarding decision-making factor.