## 6 Related Work  
The energy balance dissipation problem has been well studied in terrestrial sensor networks. Since the terrestrial sensors are inexpensive, the algorithms for those networks use dense network model and mainly try to achieve energy balance among different clusters or slices, but without considering the energy consumption per sensor [9; 13; 14; 34].  
Some clustering protocols use cluster head rotation to balance the energy consumption inside each cluster [35; 36]. However, the clusters far from the sink bear heavier energy burden than other clusters and these protocols also have to change communication topologies dynamically in order to distribute the energy consumption evenly. [PERSON] and [PERSON] define the energy balanced property of networks and propose an energy balanced algorithm for sorting in WSNs [37]. However, they only take a single-hop sensor networks into account. [PERSON] and [PERSON] propose an energy balanced algorithm for data propagation by using probabilistic method [13]. They cover the network area by a cycle sector, and the cycle sector is divided into ring slices. In each step, data packet generated by an event within one slice is either propagated to the next slice or sent to the sink directly based on the probability of the slice. However, the energy balance of the same slice is not considered in the algorithm. [PERSON] and [PERSON] consider the varying emission range of nodes for the different slices [14]. They try to find the appropriate values of the emission range so as to maximize the networks lifetime. They also mainly consider the energy balance problem among the slices.  
Some of the schemes have considered balanced energy consumption per node. [PERSON] and [PERSON] [7] extend the work of [13] by considering the energy consumption per sensor. They use a spreading technique to balance the energy consumption per sensor in the same slice. But, they do not compute  
Figure 17: Energy assignment with different frequency in shallow water.  
the ejection probabilities at the sensor node level. [PERSON] and [PERSON] use the concept of hybrid transmission method similar to our approach EBH [8]. They balance the routed data density with the energy consumption rate in the network through the combination of direct transmission and multi-hop transmission protocols. Each node transmits one part of data directly to the base station and the other part to the next hop according to data density and transmission distance. Our hybrid transmission algorithm EBH is different from [8], because we directly deal with node's residual energy. The advantage of our scheme is that whatever the reason of energy consumption, such as data transmissions, packet collisions, packet retransmissions or other reasons, it eventually affects the residual energy of the node. Using node's graded residual energy to change node's working mode can achieve even consumption of nodes in the entire networks.  
There are few literatures addressing the energy consumption in UWA-SNs [15; 16]. As we mentioned in Section 1, they consider the total energy consumption of networks, without considering the energy balance of individual nodes. For sparsely deployed UWA-SNs, the energy consumption of individual node is very important [17], because the death of a single node may cause the networks to disconnect or even collapse. In this paper, we present two energy balanced strategies to solve the energy balance problem per-node in sparsely deployed UWA-SNs.