In-network data aggregation route strategy based on energy balance in WSNs

In-network data aggregation in wireless sensor networks (WSNs) can reduce data redundancy in the process of data gathering and therefore decrease energy consumption. Since aggregation cost sometimes can not be neglected in some realistic applications, it is important how to construct an effective route strategy which optimizes not only communication cost but also aggregation cost. In addition, we further study how to adaptively adjust route structure to avoid some nodes´ premature death. To solve the above problems, we introduce heuristic algorithms based on discrete particle swarm optimization (DPSO). And the notions of mutation and crossover operators in genetic algorithm are incorporated into the discrete procedure of PSO, which can not only keep the diversity of population, but also make offspring population maintain the preferable characteristics. Experimental results show that our algorithms can effectively reduce energy consumption and trade off energy consumption and network lifetime, compared with other tree routing algorithms.