End-to-end delay reduction via in-network computation in cognitive radio sensor networks

To potentially alleviate the spectrum shortage for sensor networks of tremendous number of nodes, cognitive radio technology, and thus multi-hop opportunistic and concurrent transmissions overlaying with the primary system suggest an attractive facilitation of large-scale sensor networks. However, it is shown to result in significant end-to-end delay to prohibit practical applications. Noting the nature of traffic in sensor networks, with the aid of distributed source coding and broadcasting in wireless communication, we develop in-network computation to reduce requisite transmissions and to accommodate more concurrent transmissions within given spectrum. Without end-to-end table to significantly save control signaling, a greedy networking algorithm schedules traffic among cooperative relay paths and achieves great delay reduction under various communication scenarios. Such in-network computation further suggests a new design paradigm of communication-computation tradeoff in multi-hop cognitive sensor networks and thus machine-to-machine communications.