Abstract: A method for implementing a many-to-one concurrent transmission medium access control (MAC) protocol for underwater acoustic networks, including: initializing a network; setting a timer; initiating, by a receiving node, a control frame to perform handshakes with multiple nodes; exchange ID, level and location of the receiving node and a sending node, and counting the number of nodes that generate a sending notification (SN) message before timeout; and planning, by the receiving node, a receiving scheduling time of data from different nodes according to the number of successful handshake nodes, distance from each sending node to the receiving node, and data packet size; and performing data transmission.

Abstract: A data encoding and decoding method for underwater acoustic networks (UANs) based on an improved online fountain code, including: in a build-up phase, subjecting all original packets to sequential encoding according to their serial numbers to generate and send encoded packets with degree 2; merging k original packets to k/8 connected components with a size of 8; performing random encoding until a largest connected component is successfully decoded; in a completion phase, sending, by a receiver, a feedback packet according to a current decoding graph; according to a feedback packet containing decoding states of all the original packets, sending, by a sender, encoded packets with degree m; and randomly selecting original packets for recursive encoding to generate and send encoded packets with degree 1 or 2; and setting, by the receiver, a threshold to restrict the number of feedback packets.

Abstract: This application relates to underwater wireless sensor networks, and more particularly to a node positioning method for an underwater wireless sensor network (UWSN) based on zeroing neural dynamics (ZND), including: (S1) defining a time-varying problem of node positioning of the UWSN based on an angle of arrival (AOA) algorithm and a time difference of arrival (TDOA) algorithm; (S2) performing modeling for the time-varying problem to acquire a mathematical model of a linear dynamic matrix equation; (S3) establishing a modified zeroing neural dynamics (MZND) model with a nonlinear activation function; and (S4) solving the time-varying problem by utilizing the MZND model to complete the node positioning of the UWSN.

Abstract: A depth and distance-based single-path routing method, in which location information of nodes in network is gathered after initialization is completed, and a location table of whole-network nodes maintained by the sink node is generated. The update mechanism of the uplink Location frame is switched to a unicast triggering update mechanism to execute a depth and energy-based uplink routing algorithm. For a downlink control packet arriving at a specified ID, location information of a node is obtained through the location table to execute a distance and energy-based downlink routing policy. The distance and energy-based downlink routing policy for a downlink control packet arriving at a specified location and a downlink control packet arriving at the specified ID is executed, and a routing recovery algorithm is executed when an “open area” occurs.