  For network scientists, it has always been an interesting problem to identify
the influential nodes in a given network. The k-shell decomposition method is a
widely used method which assigns a shell-index value to each node based on its
influential power. The k-shell method requires the global information of the
network to compute the shell-index of a node that is infeasible for large-scale
real-world dynamic networks. In this work, we propose a method to estimate the
shell-index of a node using its local information. We also propose
hill-climbing based approach to hit the top-ranked nodes in a small number of
steps. We further discuss a method to estimate the rank of a node based on the
proposed estimator.
