Time efficient data aggregation scheduling in Cognitive Radio Networks

Abstract

Cognitive Radio Networks (CRNs) have been proposed as a promising technology to alleviate the spectrum shortage and under-utilization problem. A large amount of research effort has been put on CRNs. However, little attention has been paid to data aggregation problem, one of the most important communication protocols in wireless networks due to its efficiency in both energy conservation and latency reduction. In this paper, we investigate the minimum latency data aggregation scheduling problem in CRNs. Considering the difficulty of this problem, two practical distributed algorithms under the Unit Disk Graph interference model and the Physical Interference Model are proposed. Extensive simulation results indicate that the proposed algorithms have good latency performance in various network scenarios.