# A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks
## 2 Related Work  
The technology to improve connectivity and reliability of sensor networks is a hot topic nowadays. There are several kinds of methods aiming to improve connectivity and reliability to meet the requirement of applications, such as the algorithms for the routing layer and MAC layer [12; 13; 14; 15; 16], the nodes complement about dynamic nodes and static nodes [17; 18; 19] and so on. In this section, we provide a review on research works on this topic. Communication link restoration and network topology maintenance problems exist in a variety of network designs from the viewpoint of routing and the MAC layer. A centralized (C-TCSIC) and a distributed topology control algorithm (D-TCSIC) are proposed in [12]. C-TCSIC and D-TCSIC integrate power control with channel allocation to create a bidirectional and a collision-free channel connection in cognitive radio networks (CRNs). Theoretical analysis shows that the algorithm can guarantee two-channel connectivity without conflicts. However, this algorithm cannot effectively complete the restoration of link disruption among nodes for the complex environment in UASNs. Some problems arise if the transmission power is only adjusted according to the communication channel condition among adjacent nodes to restore the link disruption. This is because the disruption of communication in two nodes is not only caused by the increase of communication distance, so merely increasing the transmission power not only causes a large energy overhead but also easily causes interference to other nodes and reduces the channel capacity. For sparse networks, the authors in [16] propose a network analytic model and designed an any-to-any communication scheme. The model considers the problem of real-time message-delivery which is solved by integer linear programming and heuristics. The model proposed in [16] can reduce the complexity and improve the efficiency of networks and it is helpful for network simulation. With distributed beacons, the authors in [13] propose a novel cooperative opportunistic routing (OVAR) scheme for UASNs and build a contiguity graph at each hop and select a forwarding set that maintains the best balance between reliability and energy efficiency. OVAR can also choose a forwarding set from any direction of the sender, which increases its flexibility to bypass any type of hole and has the least deviation from the best path. In addition to the research on such routing and MAC layers, there are many related studies on network topology optimization from the perspective of node deployment [8; 20; 21; 22]. Node deployment can be divided into static deployment and dynamic deployment. Static deployment consists of random deployment and deterministic deployment. However, whether it is random deployment or deterministic deployment, underwater acoustic channels will dynamically change with the water environment, resulting in disrupted links and network partitioning. In [17], aiming at the problem of link disruption in sensor networks, the network performance is restored by sowing second-generation nodes. Although some positive results are obtained, considering the uncertainty of node spreading, a larger node redundancy will result. A two-node deployment method is proposed in [18] for network partitioning phenomenon in multi-hop UASNs, which repairs the disrupted links by adjusting the depth of nodes. This method does not produce more node redundancy like that in [17]. However, it requires nodes to automatically adjust their depth, which requires much more flexibility from nodes. Similarly, Ref. [19] makes use of the virtual force algorithm to make the nodes cover the network connection holes. The algorithm can reduce the node redundancy, but requires a higher computational capability and self-mobility capability and the driving force of node movement also generates a large energy expenditure. However, the method has a great limitation for underwater sensor nodes due to the difficulty of charging and replacing the battery of common sensor nodes.