Cross-Layer Duty Cycle Scheduling with Data Aggregation Routing in Wireless Sensor Networks

Well-scheduled communications, in conjunction with the aggregation of data reduce the energy waste on idle listening and redundant transmissions. In addition, the adjustable radii and the number of retransmissions are considered to reduce the energy consumption. Thus, to see that the total energy consumption is minimized, we propose a mathematical model that constructs a data aggregation tree and schedules the activities of all sensors under adjustable radii and collision avoidance conditions. As the data aggregation tree has been proven to be a NPcomplete problem, we adopt a LR method to determine a near-optimal solution and furthermore verify whether the proposed LR-based algorithm, LRA, achieves energy efficiency and ensures the latency within a reasonable range. The experiments show the proposed algorithm outperforms other general routing algorithms, such as SPT, CNS, and GIT algorithms. It improves energy conservation, which it does up to 9.1% over GIT. More specifically, it also improves energy conservation up to 65% over scheduling algorithms, such as S-MAC and T-MAC.