Abstract
This paper proposes a throughput-aware routing algorithm for enhancing throughput and decreasing end-to-end delay in industrial cognitive radio sensor networks (ICRSNs). In ICRSNs, the throughput is downgraded by interference from primary networks; consequently, end to end delay is increased. The proposed routing algorithm is targeted at large-scale networks where data are forwarded through different clusters on their ways to the sink. By estimating the maximum throughput for each path, the data can be forwarded through the most optimal path. Simulation results show that our scheme can decrease end-to-end delay.
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