Abstarct: Nowadays, wireless sensor networks are highly employed for collecting data from an environment where sensors are distributed in. Wireless sensor networks are used widely with various scales. In these days, using clustering methods for WSN’s has made our network disciplined and caused our sensors binding to a clusterhead. The clusterhead nodes are responsible for tasks such as collecting raw data and sending these accumulated data to a baxse station with GPRS lixnks for processing. Therefore, consumption of Energy in this type of nodes are higher than ordinary nodes. When a sensor network tries to use a protocol which its energy consumption is not fairly distributed, the nodes quickly run out of energy and they finally die. One of the useful methods for clustering nodes in a WSN is BLAC algorithm which considers battery level of nodes. Furthermore, it takes some predefined criteria into consideration for electing clusterheads. So that, network lifetime is improved in comparison to different kinds of traditional methods. Albeit BLAC algorithm represents promising results on improving network lifetime, other different parameters must be taken into consideration, such as the average ratio of packet delivery, average hop count to destination (clusterhead node) and stability of the networks. These named parameters are remembered as the efficiency of a network. However, BLAC just aims at improving network lifetime. In this research, we try to represent a newly developed version of the BLAC algorithm which uses a novel efficiency metrics, so that clusterhead nodes will be chosen more optimized. In our proposed methods, in addition to the lifetime, several network efficiency parameters have been improved. In order to achieve this purpose, new criteria are taken into consideration such as the clustering coefficient and node ranking. Furthermore, weighting criteria are also used in the proposed method. Simulation result shows that using the suggested metrics may lead to increase network lifetime up to 34 percent comparing to the BLAC Algorithm. Moreover, the proposed criteria optimize the average ratio of packet delivery and hop count to clusterhead. Also, these suggested criteria lead to control Stabilization and the number of clusters and which are made by these criteria in an acceptable manner in our network.