# A B5G Non-Terrestrial-Network (NTN) and Hybrid Constellation Based Data Collection System (DCS)
## 5 Traffic Balance Design  
In the B5G system, the QoS guarantee is crucial. For DCS equipment, data receiving capability is the most important KPI of the QoS guarantee. As described in Section 3, traffic density is related to geographic location. And traffic congestion is more likely to occur in traffic hotspot. A geolocation-based traffic forecasting model is essential for traffic balance and QoS guarantee. The distribution of traffic data obeys the global population density. As shown in Figure 5 [29], the population is mainly concentrated near the equator. Traffic density will be greater in areas of high population density. Traffic burden is related to the latitude of regions. A traffic estimation can be defined as:  
\[T_{b}(lat)=\left\{ \begin{array}{ll}110-|lat|+\bigtriangleup\,I&|lat|\leq 35^{ \circ}\\ 100-|lat|+\bigtriangleup\,I&35^{\circ}<|lat|<50^{\circ}\\ 95-|lat|+\bigtriangleup\,I&|lat|\geq 50^{\circ}\\ \end{array} \right. \tag{1}\]  
Figure 4: B5H network structure. \[\triangle l= \begin{cases}\frac{90}{|lat|}&lat>0\\ 0&lat\leq 0\end{cases}  \tag{2}\]  
where _lat_ is the latitude of region, \(t\) is the local time. The throughput of a CubeSat can be defined as:  
\[T_{p}(t)=BW(t)\cdot CD(t) \tag{3}\]  
where \(BW(t)\) is the residual bandwidth of the CubeSat and \(CD(t)\) is the connect duration between the specific CubeSat and the covered region. Once the constellation topology is designed, the connect duration can be predicted. It is determined by the access between satellites and sensors. In order to increase communication efficiency, \(CD(t)\) should be dynamically adjusted according to traffic demand. A traffic cycle (_TC_) can be defined as:  
\[TC(lat,t)=\frac{T_{b}(lat)}{T_{b}(t)} \tag{4}\]  
To predict the \(BW(t)\), a virtual topology (VT) technology is used. In VT, the whole operation period is evenly divided into a lot of time slots (\(T_{s}\)). In each \(T_{s}\), the constellation topology and network mode are considered static. \(I_{n}\), \(O_{n}\) and \(L_{n}\) are defined as input flow, output flow and queuing length in \(n\)._Ts. \(I_{avg}\) and \(O_{avg}\) are time balance value of input flow and output flow. \(\lambda_{i}\), \(\lambda_{o}\) and \(\lambda_{l}\) are memory factor. \[I_{avg}=(1-\lambda_{i})\cdot I_{n-1}+\lambda_{i}\cdot I_{n} \tag{5}\]  
\[O_{avg}=(1-\lambda_{o})\cdot O_{n-1}+\lambda_{o}  
where \(BW(t)\) is relate to \(BW(t-\Delta t)\) and \(L_{n}\)\(\lambda_{b}\) is the adjust factor, \(L_{max}\) is the maximum storage space in each satellite. There are three operation state defined as:  
\[State= \begin{cases}Idle&L_{n}\leq L_{\max}-2\cdot(I_{avg}-O_{avg})\\ Busy&L_{\max}-2\cdot(I_{avg}-O_{avg})<L_{n}\leq L_{\max}-I_{avg}+O_{avg}\\ Occupied&L_{n}>L_{\max}-I_{avg}+O_{avg}\end{cases}  \tag{9}\]  
In an _idle_ state, satellites will normally receive data and relay it; in a _busy_ state, satellites will degenerately receive data and normally relay; and in an _occupied_ state, satellites will stop receiving data and only relay data. Load balancing can be achieved by this traffic control strategy. The value range of \(\lambda_{i}\), \(\lambda_{o}\), \(\lambda_{I}\) and \(\lambda_{b}\) is between 0 and 1. The selection of these factors will affect the results of traffic estimation. In this paper, a satisfaction goal function (SGF) is introduced as the optimization objective, and four factors are defined as adjusted values. \[SGF=\frac{BW(t)}{BW_{total}}+\frac{L_{n}}{L_{\max}}+\frac{I_{avg}+O_{avg}}{C} \tag{10}\]  
where \(BW_{total}\) is the total bandwidth resource of the satellite, \(C\) is power consumption of sending and receiving unit data flow. \(SGF\) consists of three parts which represent spectrum resource, queue delay and power consumption respectively. In order to get more detailed optimization results, four factors are divided into two steps. In the first step, factors are set to a step of 0.1, and the value ranges from 0 to 1. And traverse all combinations to find the minimum value of \(SGF\).