Although the MLE derived in the previous chapter is not computationally very complex, WSNs can still benefit from some simplified schemes to estimate the clock parameters specially when the synchronization accuracy constraints are not extremely stringent but the energy conservation constraints are. In addition, to estimate both the clock offset and skew in the Gaussian noise case, knowledge of the fixed portions of delay d was required, which is not usually available beforehand. Therefore, in this chapter, two simple algorithms will be developed to estimate the clock offset and skew regardless of the distribution of the delays, and these are very suitable for the low-power-demanding regime of WSNs. The proposed estimators can be implemented using simple steps and present remarkably low complexity. These estimators and the derived performance bounds are targeting practical applications, and are of much significance due to their robustness to the actual distribution of network delays.

The main topics in this chapter are as follows. In the first proposed estimation scheme, the clock skew is estimated using only the first and the last data samples, since the difference between timestamps is largest between those two samples for any distribution, and then maximum-likelihood-like estimators (MLLEs) and Cramer–Rao-like lower bounds are derived for the clock skew. Subsequently, the data are processed to remove the effect of skew and then the clock offset is estimated, which just requires a few computations. The second proposed clock offset estimation scheme fits a line between two points, the differences between the first and the fourth timestamps, that are at a minimum distance apart, yielding both the clock offset and skew regardless of the underlying actual distribution.