A combinatorial algorithm for the Maximum Lifetime Data Gathering And Aggregation problem in sensor networks

The maximum lifetime data gathering and aggregation (MLDA) problem is concerned with maximizing the system lifetime T so that we can perform T rounds of data gathering with in-network aggregation, given the initial available energy of the sensors. A solution of value T to the MLDA problem consists of a collection of aggregation trees together with the number of rounds each such tree should be used in order to achieve lifetime T. We describe a combinatorial iterative algorithm for finding an optimal continuous solution to the MLDA problem that consists of up to n-1 aggregation trees and achieves lifetime T_o, which depends on the network topology and initial energy available at the sensors. We obtain an alpha-approximate optimal integral solution by simply rounding down the optimal continuous solution, where alpha = (T_o-n+1)/T_o. Since in practice T_o Gt n, alpha ap 1. We get asymptotically optimal integral solutions to the MLDA problem whenever the optimal continuous solution is omega(n). Furthermore, we demonstrate the efficiency and effectiveness of the proposed algorithm via extensive experimental results.