In recent years, Underwater Acoustic Sensor Networks (UASNs) have gained considerable attention for their unique role in detecting and monitoring the underwater environment. However, due to the long propagation time, high bit error rate, and limited bandwidth of underwater acoustic systems, the design of media access control (MAC) protocols is extremely complex, especially for the power consumption of UASNs. Therefore, this paper proposes an energy-efficient MAC protocol for three-dimensional UASNs with time synchronization and power control (TDTSPC-MAC). The proposed protocol is a hybrid access scheme for three-dimensional UASN using techniques such as time synchronization, power control, clustering, layering, and sleep mechanisms. Moreover, the TDTSPC-MAC protocol uses the hierarchical concept and distributed clustering algorithm to divide the three-dimensional space, and combines time synchronization and power control strategies to avoid collisions. Besides, energy consumption is reduced through monitoring and sleep mode. Simulation results demonstrate that the proposed TDTSPC-MAC protocol has reasonable data transmission delay time, throughput, energy consumption, and other performance.

The UASNs are widely used in underwater communications and monitoring, and many applications require accurate information regarding the position of nodes. However, intentional attacks against devices or information transmission may exist in the network, and the localization process is periodic, so it is necessary to quickly address attacks and optimize the network structure. This paper proposed an anchor node self-adaptive adjustment localization scheme (ASAL), in which the anchor node can adjust the state and depth of its participation. Two filters were used to adjust the states of referable nodes. The first filter was based on the distance difference of reverse information transmission after direct localization based on anchor nodes. The second was based on the error of the anchor node’s reverse localization after network localization was completed. In addition, a depth-adjustment mechanism of anchor nodes was proposed to optimize the network structure, the virtual force vector was introduced to describe the cost of depth adjustment, and the whale optimization algorithm was used to converge to the depth with the minimum total cost. The simulation results showed that the scheme can ensure localization accuracy and coverage in attack scenarios and reduce localization energy consumption.

The precise localization of sensor nodes is a key link in underwater wireless sensor networks (UWSNs) applications. Furthermore, the nodes in UWSNs should be able to independently determine their relative positions before they begin to receive and transmit data to each other. Most of the existing underwater localization algorithms are based on the anchor nodes with known locations, and the rest of the nodes can be calculated by the anchor nodes. The iterative localization process has been proposed for the localization of UWSNs, in which some positioned nodes as reference nodes are selected for iterative localization. However, in real scenarios, some anchor nodes may be destroyed naturally or artificially damaged or even used to convey misleading information to interfere with the precise localization of other nodes underwater. This paper proposes a computationally efficient localization algorithm that can accurately locate the sensor nodes underwater to resist such network attacks. The proposed algorithm achieves better localization accuracy by iteratively removing misleading information transmitted from interfering nodes based on the Time Difference of Arrival ranging mapping and combining selective minimum gradient of AdaDelta gradient descent (AGD). The simulation results prove that the proposed algorithm performs better under network attacks than the existing algorithms.