## 4 Results: MVLL Scheme for Route Verification Task  
As position verification methods may combine GPS, lidar, and computer vision systems, the route planning and the tracking estimation for mobile agents involves the problem of precision of data [76], influenced by the speed of mobile agents and satellites disposition. The controlled range for space coordinates can vary from centimeters up to thousands of km, and it is necessary to provide enough accuracy for all possible distances. First variant here is to apply correlated variables in the discrete \(k\)-valued logic model of AGA [18; 19], where one can represent space coordinate \(x\) e.g., as 1560 m = 1 km + 500 m + 60 m+.... by the summation  
\[x=x^{(1)}\times 1+x^{(2)}\times 10+\ldots x^{(p)}\times 10^{p}. \tag{10}\]  
However, for the MVLL in route verification task there is the second possible scheme to apply purely formal representation excluding summation as in Exp. (13). It is based on the fact, that the distributed backup storage of MVLL should only measure and approve the correctness of data, as the value of coordinates discrepancy is required further at the stage of decision-making. Thus, verification or comparison of data from different storages mainly includes formal checks equal/non-equal, and further procedures are the another task. So that if unique GPS coordinates are represented [77] by a popular format, say, 57\"45,4682, one can write it e.g., as the set of numbers [57], [45], [4682] = #(00111001)b, #(00101101)b, #(00010010; 010010101)b, fixing by default the position of separating tags. Advantage of formal AGA model is that for any bit format of space coordinates they can be quickly represented by several bytes in logic expressions with known by default rules for reverse reconstruction of geographical degrees, minutes, and seconds. For the route veification task the difference between the given and the real route should be finally described by the deviation function \(F_{real}\), which should estimate the difference between space coordinates \(x,y\) for the planned route and measured coordinates \(x^{(e)},y^{(e)}:\)\(F_{eval}=F(N_{agent},\)\(N_{license}\)\(,x,y,x^{(e)},y^{(e)})\). Close case here is the comparison of coordinates obtained by different GPS receivers, installed in navigation systems of the check-point and the mobile agent. Then the simplest way is to use MVLL with formal representation of coordinates. Realistic version of 8-bit MVLL seems to be represented by the entry described by Exp. (11)  
\[e_{m}=\{m,t,ID_{agent},N_{lic},\)\(x^{(1)},x^{(2)},\)\(x^{(3)},x^{(4)},H^{(int)},x^{(e1)},x^{(e2)},x^{(e3)},x^{(e4)},\)\(h_{1},\ldots,h_{Q}\}, \tag{11}\]  
where \(m\) is the entry number in the ledger, \(t\)--time of registration by the first of external verifying nodes, \(ID_{agent}\)--digital identifier of the agent (for simplicity we suppose it to be 1 byte), \(N_{lic}\)--license number (also 1 byte), \(x^{(1)},x^{(2)},\)\(x^{(3)},x^{(4)}\) describe 4 bytes of space coordinates, and data marked by (*) refer to another source of data, e.g., to the check-point. Here every set \(x^{(1)},x^{(2)},\)\(x^{(3)},x^{(4)}\) includes both the latitude and the longitude (N and E) in NMEA-0183 [78]). Variable \(H^{(int)}\) in Exp. (11) describes values of internal hash function. Thus, entry \(e_{m}\) in AGA can be written as the logic product term Exp. (12):  
\[