Sensors play a prominent role in the industrialized society of today and a world without sensors is inconceivable as most of the electronic applications are based on it. Various applications including in the fields like military control in battlefield surveillance, industrial automation, health monitoring, security systems and many more utilizes wireless sensors, which reveals its prominence and deployment perspective. Such sensor nodes are becoming more common as the technology for wireless communication is becoming increasingly affordable. This thesis deals with the estimation of battery life for the selected algorithms where a specific industrial application is considered, utilizing wireless battery powered sensor nodes in order to measure indoor temperature in buildings as part of a heating control system. This application can accommodate only two batteries and sometimes it is to be placed in highly restricted areas, which makes it difficult to replace the batteries often. Hence saving the battery life is an intrinsic issue which needs to be overcome by any industrial manufacturer. So far, various algorithms have been implemented to solve this issue but have not succeeded completely. In our research we introduced a new approach to choose the best suited algorithm based on the requirements of specific industrial application. Also, by implementing those algorithms and considering the time interval of 15, 30 and 60 min, the battery life is estimated for any network. The purpose of the paper is to study and compare different power conservation algorithms for wireless sensor networks in relation to the specific constraints found in this heating control system. The different algorithms are evaluated on the basis of their ability to preserve power while simultaneously fulfilling these specific constraints. Three different algorithms are selected and studied through simulations and their individual operational behavior in relation to the specific industrial application is shown. Finally, this report demonstrates the total energy consumed per message, average distance calculations from source node to sink node, by performing simulations in MATLAB (v7.9.0). This paper also exhibits the behavior of PEGASIS, EEAR and SPIN-1 algorithms considering node number variation, node range and different communication intervals as parameters. By performing quantitative analysis of obtained results, at the end one can find the sustainability of the battery life. For 200 nodes network, it is lasting longer when PEGASIS algorithm (high energy efficient) is used. But for the same number of deployed nodes, the EEAR based network sustains smaller than PEGASIS based network (considering two batteries) as EEAR could accomplish self organizing technique, similarly SPIN-1 based networks lasts very small as they could implement both self organizing and self-healing techniques. Hence it is to conclude that, for this specific industrial application, the researchers as well as manufacturers can incorporate these results directly in their application.