## 1 Introduction  
Overcoming interference and energy holes in underwater wireless sensor networks (UWSNs) usually guarantees reliable data transfer from a source to a destination. However, addressing these issues is linked with addressing the inherent challenges of underwater communications: low available bandwidth, greater propagation delay than terrestrial radio frequency communications and limited battery power [1]. However, the performance metrics of these networks are the same as for the terrestrial networks [2; 3; 4; 5]. These networks find applications in offshore exploration, leak detection, seismic and equipment monitoring [6], military surveillance, underwater navigation, disaster prevention and environmental monitoring [7]. Underwater routing protocols that involve the mitigation of interference and energy holes are unique for a number of reasons. Interference results in packet collision that, in consequence, leads to packet loss. In a similar fashion, the formation of energy holes disconnects the routing traffic from a source to a destination, which also results in data loss. Such losses are unbearable in underwater communications, where sensor nodes already operate on limited battery power. Therefore, protocols coping with these issues provide the reliable delivery of data from a source to a destination. Such data delivery is particularly important in time-sensitive and military applications [8]. Specifically, when data loss due to interference is overcome, the limited battery power of nodes is also utilized in an effective and efficient fashion. The power that is lost against interference is then utilized to deliver more data packets. Likewise, when a forwarder node between a sender and a receiver dies and becomes an energy hole, it leads to a loss of data from the sender to the receiver. The data loss causes unnecessary power consumption of the sender node. Therefore, overcoming this energy hole ensures reliable data delivery as well as efficient power utilization. The conventional routing protocols that cope with energy holes require that the localization information of an energy hole is known [9; 10]. However, localization is a cumbersome and challenging task, as nodes change their positions with water currents. This leads to inaccuracy in the measurement of the position of an energy hole. Furthermore, an energy hole may change its position, and nodes may not detect it early because of the long delay in underwater communications. As a result, false position detection of all the energy holes may compromise the performance of the network. The protocols addressing the interference select routing paths that involve the least number of neighbors of a forwarder node [11; 12]. However, with the least number of neighbors, a forwarder may not forward packets further when its neighbors die. In other words, the death of the least number of neighbors of a forwarder node results in the formation of energy holes. This also results in overall degradation of the network performance; in particular, the number of packets that reach the final destination decreases significantly. This is contrary to the routing protocols in which forwarders do not select the routing paths on the basis of the least number of neighbors and, therefore, have higher interference. There are a number of challenges associated with the design of interference and energy holes minimization routing protocols. The underwater medium carries unpredictable and severe conditions that challenge underwater communications. These include noise, the mobility of sensor nodes with water, interference from underwater objects, shadow zones and attenuation of the desired signal [13; 14]. Specifically, the movement of nodes with water currents challenges the communications among nodes. This is because it becomes difficult to locate the positions of nodes when they are not stationary [15]. This becomes critically important for circumstances in which nodes die and live nodes have to replace their positions. This work addresses some of these challenges.