Maximizing Lifetime of Data-Gathering Trees with Different Aggregation Modes in WSNs
We study the problem of maximizing the lifetime of data-gathering tree for wireless sensor networks (WSNs). Both data routing and aggregation are considered at the same time to improve the energy efficiency for data collection in WSNs. With different data-aggregation methods, three aggregation modes are studied: full aggregation, non-aggregation, and a hybrid partialaggregation using Compressive Sensing. For each mode, an exact solution based on Mixed-integer linear programming (MIP) is proposed to find the optimal data-gathering tree. Although nonlinear relation exists between the sensor node lifetime and the number of data units that receives or transmits in each time slot, we succeed to express it by a set of linear equations. Performance results demonstrate that the lifetime of data-gathering tree can be increased tenfold with efficient data aggregation methods.