Identification of landmark nodes in complex networks has been of great interest but the parameters based on which these nodes are selected have been different in different cases. We believe that Landmarks are those nodes that occur most frequently while we explore or navigate a network. We propose 2 methods and efficient algorithms to identify these nodes. We identify these nodes using centrality measures and random walks. We show that the methods proposed are both, effective and efficient. Our approach has been extensively evaluated using synthetic environments. The results obtained verify its robustness along with its applicability.