We also developed a procedure to identify unique nodes more precisely based on the expected coverage for each sub-graph and considered very low-coverage nodes by determining an appropriate threshold to remove error nodes.
In this case, error from node 2 is minimal and the SPEB of node 1 is minimal.
In Fig. 1, the location error for node 5 is probably greater than the location error for node 7. The algorithm attempt to mitigate propagated errors by ignoring the worst references.
Figure 3 Algorithm location error by node density for 2. 4 GHz.
In this set of simulations, we evaluate the robustness of VBF against packet loss (or channel error) and node failure.
Where all distance measurements are available, the average error per node from actual, GPS-surveyed, distances is 0.2 m.
and ε i is the average probability of error at node i which is also assumed to be available at the destination.
To eliminate the unavoidable predicting error, each node should keep its recent and recalculate it when error occurs, then notify it with its current remaining energy to the other nodes on the route.
The experiments were conducted and the experimental results were analyzed according to ranging errors, anchor node density, communication radius, moving speed, and node localization errors.
The localization results of KF, LSSVR, and KF-LSSVR algorithms are compared according to ranging errors, anchor node density, communication radius, moving speed, and node localization errors.
