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Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an energy efficient and stable weight based clustering (EE-SWBC) algorithm that elects clusterheads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using grey decision method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. In result, EE-SWBC fairly selects potential nodes with less overhead. The simulation results show that EE-SWBC maintains less average number of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.