# DCO-MAC: A Hybrid MAC Protocol for Data Collection in Underwater Acoustic Sensor Networks
## 1 Introduction  
In the last decade, underwater acoustic sensor networks (UASNs) have attracted enormous research attention in the academia and industry [1; 2; 3], as UASNs can be used in many applications, such as ocean currents monitoring, and oceanographic data collection, submarine detection, and so on. Unlike terrestrial wireless sensor networks, radio and light are not suitable for underwater communication because of the severe attenuation in this environment. Hence, sound wave is the preferred choice for the underwater communication scenario. Designing an appropriate medium access control (MAC) protocol is important for the UASN. In this paper, we focus on the MAC protocol in the UASN for data collection mission. However, the special characteristics of the underwater acoustic channel and network, such as long propagation delay, high bit-error-rate (BER), limited bandwidth, and sparse network topology, pose a great challenge to underwater MAC protocol design. Moreover, as an application-oriented network, the MAC protocol designing in the UASN should take the requirements of the applications into consideration. In this paper, we consider a data-collection-oriented UASN (DCO-UASN), consisting of a sink node (SN) and many sensor nodes. In this network, the data packets generated at the sensor nodes are transmitted to the SN hop-by-hop. Thus, the traffic load in the DCO-UASN is non-uniformly distributed. That is, the closer to the SN, the more data packets are transmitted by the sensor node. In recent years, many MAC protocols have been proposed in the UASNs. These MAC protocols can be classified into three types, contention-based, schedule-based, and hybrid MAC protocols. In contention-based MAC protocols [4; 5; 6; 7; 8; 9; 10], sensor nodes need to compete for the channel to send data packets. The contention-based MAC protocol for the UASN achieves a small end-to-end delay in the case of a low network traffic load. However, the successful probability of the channel competition decreases rapidly as the network traffic load increases, which results in the decrease of the network throughput. In order to achieve a high network throughput, the schedule-based MAC protocols have been proposed for UASNs [11; 12; 13]. In the schedule-based MAC protocols, the transmissions of senders are scheduled to avoid the packet collisions. Hence, the schedule-based MAC protocols in the UASN achieve a high network throughput with a high network traffic load. However, the end-to-end delay of the schedule-based MAC protocols is large, especially when the network traffic load is low. In addition, the non-uniformly distribution of the network traffic load in the DCO-UASN is not considered in both the contention-based and schedule-based MAC protocols. Combining the advantages of the contention-based and schedule-based MAC protocols, the hybrid MAC protocols [14; 15] are adaptive to the network traffic load by providing multiple modes, where different protocols are adopted in different modes. One finds, in the work of [PERSON] and [PERSON] [14], that the hybrid MAC protocol performs well in the single-hop DCO-UASN. However, the sender-receiver collision occurs when the protocol is extended directly to multi-hop DCO-UASN, because some nodes may carry out several MAC protocols in the same time. In the work of [PERSON] et al. [16], a hybrid MAC protocol is proposed for a cluster-based DCO-UASN, where the intra-cluster communication and inter-cluster communication are carried out periodically, to avoid the sender-receiver collision. However, in this protocol, a contention-based MAC protocol is adopted for the inter-cluster communication with a high network load, which results in a poor network throughput performance. Therefore, we have studied the hybrid MAC protocol for the DCO-UASN with a non-uniformly distributed traffic load in this work. On the other hand, with the development of autonomous underwater vehicle (AUV) technology, AUV is widely used in oceanographic data collection.