In this context, range-based algorithms [8] rely on distance between nodes, which is usually measured with received signal strength indicator (RSSI -time of aRSSI -timeA)-time differential of arrival (TOA -timeangle of arrival (AOA)-based TOA -times.
Here, A ( r ( t ) ) = ( a i j ( r ( t ) ) ) N × N describes the linear coupling configuration of the network at time t at mode r ( t ), and is defined as a i j ( r ( t ) ) ≥ 0, for i ≠ j, a i i ( r ( t ) ) = − ∑ j = 1, j ≠ i N a i j ( r ( t ) ), i = 1, 2, …, N. Γ = diag { γ 1, γ 2, …, γ n } is the weighted inner-coupling matrix between nodes, which is positive definite.
Moreover, this approach allows developers to establish the desired reliability level (in a quantitative way) between two nodes which are N hops far away from each other.
Quadratic cost functions for network coverage and backbone connectivity are defined in terms of the square distance between neighbor nodes, which are related to the actual energy usage of the network system.
Thus, the model is inaccurate in estimating the number of hops between the nodes which are randomly placed.
Intuitively, the link between two nodes which are close to each other has a high delivery rate.
As can be seen from (28), (33), (34), (35), (36), and (37) the optimal energy distribution factor is a function of distances between the nodes which are assumed to be known at all the relay and source nodes.
In our case, each node of V corresponds to a single country, while the set of edges X contains trade linkages between the nodes, which are weighted by C&T-trade volumes (w_{ih}).
Moreover, it is necessary to exchange information between the nodes which are not directly connected (n-step neighbors; ) because they contain some information (also known as negative information [24]) about the distance between them.
