In this proposed system, distance based ant colony optimization (ACO) algorithm proposed. Here most energy-efficient distance and most energy-balanced distance are implemented for high energy efficiency. For efficient running of wireless sensor network applications, energy conservation of the sensors becomes a prime paradigm for prolonging lifetime of the network. Second, contrary to typical communication networks, almost all applications of sensor networks require the flow of sensed data from multiple regions (sources) to a particular base station. Third, the generated data traffic has significant redundancy since multiple sensors may generate same data within the vicinity of a phenomenon. Implement the network model based on the concentric coronas with thickness and number of sectors. Data volumes and distance are measured for every sectors according to node density, network size, corona thickness, maximal transmission level. The search is performed by ACO, where there is an ant on every sector initially. After that, every ant moves from a sector to another towards the sink according to a specific probability. Finally the network lifetime can be evaluated by initial energy of each node and the per node average energy consumption (PNAEC) of each sector. So, such pheromone updating rule can guide ants to select an efficient path with minimal value of the maximal PNAEC of different sectors, and accordingly achieve network lifetime maximization.