# A Comprehensive Survey of Recent Routing Protocols for Underwater Acoustic Sensor Networks
## 1 Introduction  
Unlike terrestrial sensor networks, underwater sensor networks are faced with some unique challenges, such as the absence of GPS, three-dimensional node deployment, and mobility of nodes with water currents [1; 2]. In addition to these challenges, the infeasibility of using radio waves as an underwater communication medium poses further challenges. Radio waves can propagate only short distances in water, as they fade quickly inside water, due to absorption. Long distance communication using radio waves requires very large antennae, which becomes a limiting factor in node design. Therefore, acoustic waves, which enable long distance communication inside water, are used as a medium of communication. However, the underwater acoustic channel also poses some challenges, such as higher levels of noise, Doppler effect, higher propagation delays, and higher bit error rates [3; 4]. In order to be effective, protocol designs for underwater sensor networks must consider these characteristics of the underwater acoustic channel. Figure 1 shows a generalized architecture of underwater sensor networks [5]. Sensor nodes, equipped with acoustic transceivers, are deployed underwater. These nodes can be static or mobile. The sensor nodes route data to the surface sink nodes, mostly using sensors at lower depth levels as relays. Alternatively, autonomous underwater vehicles (AUVs) can be employed to collect data directly from sensors. AUV-based routing requires efficient path planning for AUV travel. Moreover, employing AUVs incurs extra cost. Routing protocols hold a key position in the design of UWSNs. These protocols are responsible for determining efficient paths and route data along those paths from the sensor nodes to the stations where the data can be meaningfully interpreted. In order to achieve optimal performance, these protocolsmust be robust against the harsh underwater channel conditions. For example these protocols should efficiently deal with energy constraints, node mobility, high SINR, high end to end delays etc. Many surveys have been conducted on routing in underwater sensor networks [6; 7; 8; 9]. However, most of these surveys do not focus on the recent work. Moreover, some of them do not discuss routing strategies and the merits and demerits of the protocols being surveyed. An account of these parameters is vital for the readers to attain a basic understanding of the protocols being reviewed. In this work, we present a review of recently proposed routing algorithms for underwater sensor networks. We analyze the protocols extensively, and identify their merits and demerits. In addition, our analysis includes an extensive set of evaluation parameters that have a direct impact on protocol performance. Moreover, we briefly explain the routing strategy of every protocol to familiarize the reader with the basic design of the protocol. The protocols are categorized based on location requirement: i.e., whether the protocol needs location estimates to carry out its operations or not. The protocols in each category are further divided based on mobility consideration i.e., whether a protocol considers node mobility or not. In the following text, we briefly explain the issues a routing protocol design should address:  
_Energy Constraints:_ Energy is a constraint in UWSN, as batteries can neither be recharged nor replaced easily. Therefore protocol designs must consider energy conservation. _Connectivity Void Avoidance:_ Connectivity voids are created if a node, which lies on a packet's route from source to destination, goes down, due to energy drainage or some malfunction. A good routing protocol should avoid the creation of voids by load balancing. Moreover if voids are created, it should have strategies to work around the void regions, to successfully deliver packets to the destination node. _Location Estimation_: Due to the unavailability of GPS underwater, location estimation becomes a challenging and communication intensive task.