  In wireless sensor networks (WSNs), simulation practices, system models,
algorithms, and protocols have been published worldwide based on the assumption
of randomness. The applied statistics used for randomness in WSNs are broad in
nature, e.g., random deployment, activity tracking, packet generation, etc.
Even though with adequate formal and informal information provided and pledge
by authors, validation of the proposal became a challenging issue. The
minuscule information alteration in implementation and validation can reflect
the enormous effect on eventual results. In this proposal, we show how the
results are affected by the generalized assumption made on randomness. In
sensor node deployment, ambiguity arises due to node error-value ($\epsilon$),
and it's upper bound in the relative position is estimated to understand the
delicacy of diminutives changes. Moreover, the effect of uniformity in the
traffic and contribution of scheduling position of nodes also generalized. We
propose an algorithm to generate the unified dataset for the general and some
specific applications system models in WSNs. The results produced by our
algorithm reflects the pseudo-randomness and can efficiently regenerate through
seed value for validation.
