# Multi-Objective Optimisation in Multi-QoS Routing Strategy for Software-Defined Satellite Network
## 5 Proposed Methodology
### Routing Strategy  
(1) Control plane: In this paper, we use virtual topology strategy to shield the dynamic topology of LEO satellite network. The satellite network topology is unchanged in each slot and the satellite movement is cyclical. In each hot, location servers send control information and update routing tables of LEO satellites through GEO satellites transmitting control information. When updating routing tables, the proposed interval type-2 fuzzy set decision routing algorithm is adopted based on the information received by the former network. (2) Data plane: After location servers receive the packets from users, add the application attributes in the header of the packets to distinguish the kind of traffic class. When a location server send a packet to a LEO satellite, the LEO satellite put it into corresponding packet queues based on the properties of the packet header. The packets of traffic Class A is put in \(Q_{1}\) queue. The packets of traffic Class B is put in \(Q_{2}\) queue. The packets of traffic Class C is put in \(Q_{3}\) queue. The packets of traffic Class D is put in \(Q_{4}\) queue. When packetsare transmitted between LEO satellites, the sending satellites send packets to the next hop based on their latest routing table. The next hop puts packets into corresponding packet queues based on the properties of the packet header and transmit them according to the routing table until the transmission is completed. (3) Routing algorithm: When sender send a packet, the packet is placed in the corresponding queue of the sending buffer. The corresponding port is selected according to the routing table. The update of the routing table is based on Algorithm 1. ```
1:input: \(L_{A}\), \(L_{B}\), \(L_{C}\), \(L_{D}\)
2:output: Routing Table
3:Initialize all computing period (\(\Delta\)t) and timer(t) in this algorithm. 4:Every LEO satellite collects the \(L_{A}\), \(L_{B}\), \(L_{C}\), \(L_{D}\) and sends them to GEO satellites. 5:Every GEO satellite sends packets (\(L_{A}\), \(L_{B}\), \(L_{C}\), \(L_{D}\)) to ground servers. 6:The ground servers calculate the control information. 7:The ground servers send the control information to GEO satellites. 8:Every GEO satellite sends the control information to LEO satellites. 9:Every LEO satellite adjusts its transmission mode and updates its Routing Table. In the case of step6, the procedure of fuzzing the network state information (\(L_{A}\), \(L_{B}\), \(L_{C}\), \(L_{D}\)) not only take the form of expert ratings, but also can be defined by the membership function. In this paper, the fuzzy class number of each criteria is 8 and we divide the value range of each criteria into eight fuzzy classes by using the trapezoidal membership function method. ```  
**Algorithm 1** Routing algorithm based on the Interval type-2 fuzzy set  
The trapezoidal membership functions are as follows:  
\[g^{\text{1}}(x)=\left\{ \begin{array}{lr}1&x\leq\overline{\lambda_{1}}\\ \frac{\lambda_{2}-x}{\lambda_{1}}&\overline{\lambda_{1}}<x\leq\underline{ \lambda_{2}}\\ 0&x\geq\underline{\lambda_{2}}\end{array} \right.\]  
\[g^{\text{k}}(x)=\left\{ \begin{array}{lr}\frac{x-\overline{\lambda_{k-1}}}{ \underline{\lambda_{k}}-\overline{\lambda_{k-1}}}&x\in[\overline{\lambda_{k-1 }},\underline{\lambda_{k}}]\\ 1&x\in[\underline{\lambda_{k}},\overline{\lambda_{k}}]\\ \frac{\lambda_{k+1}-x}{\underline{\lambda_{k+1}}-\overline{\lambda_{k}}}&x \in[\overline{\lambda_{k}},\underline{\lambda_{k+1}}]\\ 0&x\
otin[\overline{\lambda_{k-1}},\underline{\lambda_{k+1}}]\end{array} \right. (k=2,3,4,5,6,7)\]  
\[g^{\text{8}}(x)=\left\{ \begin{array}{lr}0&x\leq\overline{\lambda_{7}}\\ \frac{x-\overline{\lambda_{7}}}{\underline{\lambda_{8}}-\overline{\lambda_{7}} }&x\in[\overline{\lambda_{7}},\underline{\lambda_{8}}]\\ 1&x\geq\underline{\lambda_{8}}\end{array} \right.\]  
The membership functions are in Table 2.  
After the evaluation of every criteria is obtained, find corresponding IT2 HFNs. According to all the queue data and weight coefficient, evaluate all schemes.