However, in such sensor networks, sensed data are usually routed to sinks and such centralized data transmissions lead to unbalanced energy consumption which refers to as the \"energy hole\" problem. This may partition the whole networks and make sub-regions uncovered or even collapse the entire networks [6]. The \"energy hole\" problem has been well studied in terrestrial sensor networks [6; 7; 8; 9]. However, UWA-SNs have unique characteristics very different from terrestrial sensor networks, and these algorithms can not be directly applied to the UWA-SNs. First, the energy consumption of acoustic modem in UWA-SNs is quite different from those of typical radio transceivers, for the transmit power is dependent on both distance and frequency. Furthermore, transmit power is often 100 times more expensive than that of the receive mode in UWA-SNs [10; 11]. For example, the typical receive power of the WHOI micro-modem is about 80 mW, but the transmit power is 10 W [12]. Second, the algorithms in terrestrial networks use dense network model and mainly try to achieve energy balance among different clusters or slices, without considering energy balance of individual nodes [13; 14]. However, in UWA-SNs, node deployment is generally sparse because of economic considerations [3]. Therefore, the energy balance of individual nodes become very important in such networks. Several literatures address the energy consumption in UWA-SNs. In [15], the author estimates the battery lifetime and power costs of shallow water in terms of four independent parameters: distance, frequency, frequency of data updates and number of nodes in cluster. In [16], the author analyzes the energy consumption in UWA-SNs considering routing protocols such as packet relaying, direct transmission and clustering in both shallow and deep water. However, both [15] and [16] just consider the total energy consumption of networks, and do not take the energy balance of individual nodes into account. Though the total energy consumption is a significant energy efficiency metric, the energy consumption of individual node is more important for sparsely deployed UWA-SNs because the death of a single node in such networks may cause the networks to become disconnected or collapse the entire networks [17]. In this paper, we focus on the energy balance problem and try to achieve energy balance among individual nodes considering two types of sparsely deployed UWA-SNs: underwater moored monitoring systems and sparsely deployed two-dimensional UWA-SNs. We first analyze the reasons of unbalanced energy consumption in such networks, then we propose two different energy balanced strategies: Energy Balanced Hybrid (EBH) data propagation algorithm and Differential Initial Battery (DIB) assignment to achieve balanced energy consumption of individual nodes. EBH is a hybrid data propagation algorithm which alternately changes node's transmit mode between multi-hop and direct transmission based on node's residual energy gradation to achieve energy balance among sensor nodes. DIB takes another strategy to deal with the unbalanced energy consumption problem, in which it pre-assigns differential battery power level according to node's traffic loads before deployment in two-tier hierarchical networks. We evaluate the proposed strategies extensively by simulations and the results show both EBH and DIB can achieve balanced energy consumption per-node, and at the same time maximize the lifetime of such networks in both shallow and deep water. The main contributions of our work are:  
1. We have theoretically analyzed the energy balanced consumption of individual nodes in a linear sensor network for both shallow and deep water. 2. We proposed two different energy balanced strategies: EBH and DIB to maximize the lifetime of sparsely deployed UWA-SNs. The rest of this paper is organized as follows. Section 2 describes the network model and underwater acoustic propagation. Section 3 analyzes the reasons of unbalanced energy consumption in linear sensor networks.