SDRT: A reliable data transport protocol for underwater sensor networks

Abstract

In this paper, we investigate the reliable data transfer problem in underwater sensor networks. Underwater sensor networks are significantly different from terrestrial sensor networks in two aspects: acoustic channels are used for communications and most sensor nodes are mobile due to water current. These distinctions feature underwater sensor networks with low available bandwidth, large propagation delay, highly dynamic network topology, and high error probability, which pose many new challenges for reliable data transfer in underwater sensor networks. In this paper, we propose a protocol, called segmented data reliable transfer (SDRT), to achieve reliable data transfer in underwater sensor network scenarios. SDRT is essentially a hybrid approach of ARQ and FEC. It adopts efficient erasure codes, transferring encoded packets block by block and hop-by-hop. Compared with traditional reliable data transfer protocols, SDRT can reduce the total number of transmitted packets significantly, improve channel utilization, and simplify protocol management. In addition, we develop a mathematic model to estimate the expected number of packets actually needed in SDRT with SVT codes. Based on this model, we devise a new window control mechanism to further reduce energy consumption which is introduced by large propagation delay of acoustic channels. Moreover, this model enables us to set the appropriate size of the block to address the mobility of the nodes in the network. We conduct simulations to evaluate our model and SDRT. The results show that our model can closely predict the number of packets actually needed, and SDRT is energy efficient, and can achieve high channel utilization.

Introduction

Sensor networks have been envisioned as powerful solutions for many applications, such as monitoring, surveillance, measurement, control and health care. Recently, applying sensor networks in aquatic environments (i.e., building underwater sensor networks) has received growing interests [1], [18], [25], [26], [27], [28]. Compared with traditional techniques used in underwater activities such as scientific exploration and commercial exploitation, underwater sensor networks empower us to monitor or detect phenomena more accurately and timely in extended areas.

In underwater sensor networks, most sensors are not fixed, and can passively float with water current. This feature is common in a wide range of aquatic applications, such as estuary monitoring and submarine detection. Empirical observation suggests that water current moves at the speed of 3–6 km/h in a typical underwater condition. Moreover, different water currents have different directions. For example, in the estuary environment, the water current near the surface is downstream, while the water current near the bottom is upstream. In such application scenarios, most sensor nodes, except some fixed nodes equipped with surface-level buoys, are mobile due to water current. It is reported in [26] that underwater objects move at speed 1–3 m/s.

The mobility of underwater sensor nodes results in a highly dynamic network topology. For example, if the transmission range is 1500 m, the initial distance between two nodes are 750 m. These two nodes will be out of transmission range of each other in about 375 s if they move in opposite directions even with 1 m/s. In this work, we call the time period that two nodes are in transmission range of each other neighborhood time period. Underwater sensor networks are feathered with very limited neighborhood time period due to the complex node movement. Moreover, in the targeted underwater sensor networks, in order to save the energy consumptions, the nodes are working in medium transmission range (less than 1500 m) and data are forwarded hop-by-hop from data source to data destination.

Different from terrestrial sensor networks, acoustic channels are used for communications in underwater sensor networks. The propagation speed of acoustic signals in water is about 1.5 × 10³ m/s, five orders of magnitude lower than the radio propagation speed (3 × 10⁸ m/s). In addition, the available bandwidth of underwater acoustic channels is limited and depends on both transmission range and frequency [5], [6], [23], [29]. According to [8], nearly no research and commercial system can exceed 40 km × kbps as the maximum attainable range × rate product. Moreover, underwater acoustic channels are affected by many factors such as path loss, noise, multi-path, and Doppler spread. All these cause high error probability in acoustic channels. Furthermore, most popular acoustic modems are half-duplex and the transition time between the transmitting and the receiving mode is long [37].

For mission critical applications with high reliability requirements such as submarine detection, reliable data transfer is indispensable. An efficient reliable data transfer protocol must effectively address the new challenges of the underwater environment, such as large propagation delay, low communication bandwidth, high error probability, and limited neighborhood period. In addition, since nodes in underwater sensor networks are usually powered by batteries, high energy efficiency is also desired for the reliable data transfer protocol.

The new characteristics of underwater environments make many existing methods in reliable data transfer undesirable for underwater sensor networks.

The conventional end-to-end based reliable data transfer is inefficient in underwater sensor networks. This is because compared with radio channels, underwater acoustic channels feature with much higher error rate. The end-to-end approaches will bring about too many end-to-end retransmission. Recent studies in [9], [15], [17] show that the end-to-end approach is even infeasible for sensor networks because of its low efficiency. For sensor networks, hop-by-hop reliable data transfer, which guarantee the reliable data transfer per hop, is more promising.

Most hop-by-hop based reliable data transfer protocols for terrestrial radio networks still do not work in underwater environments. The naive Stop-and-Wait automatic repeat request technique (ARQ) protocol is undesirable in underwater sensor networks. Stop-and-Wait ARQ results in extremely low channel utilization if applied in underwater sensor networks due to the low propagation speed of acoustic signal. In addition, this protocol is not energy efficient because for every data packet, an ACK will be generated.

Even though some pipelined ARQ protocols, such as Go-Back-N ARQ and Selective Repeat ARQ, can achieve higher channel utilization than the Stop-and-Wait ARQ protocol, these protocols are not efficient in underwater sensor networks. First, most of these protocols assume the full-duplex operation on every node, which is not supported by existing half-duplex underwater acoustic modems. Second, since multiple packets are sent together in these protocol, a long time (including retransmission) is needed for every interaction between the sender and the receiver, which may exceed the limited neighborhood time period. Moreover, these protocols have to address the problems resulted from ACKs such as timeout problem and synchronization between transmission of data and ACKs. All these problems are further complicated by the long propagation delay of underwater acoustic channels.

Some reliable data transfer protocols resort to pure Forward-Error-Correcting (FEC). In a FEC approach, the sender keeps sending encoded packets, and the receiver keeps receiving encoded packets. At the receiver side, lost packets are ignored, and original data packets can be reconstructed after enough number of encoded packets successfully received. The management of feedback-free protocols using FEC is usually simple in that encoding and decoding are the only additional overhead introduced to the sender and receiver, respectively. However, FEC essentially exploits redundancy for reliability. In other words, additional energy is always used for reliable data transfer irrespective of the channel conditions. In sensor networks, due to energy constraints, pure FEC scheme is not a good choice [36].

Summarizing the above discussions, we want to design a reliable data transfer protocol for underwater sensor networks, with the goals of energy efficiency, high channel utilization and simple protocol management. In this paper, we propose a protocol called, Segmented Data Reliable Transfer (SDRT). It is essentially a hybrid approach, exploring both FEC and ARQ.

The target sensor networks are relatively dense, with nodes working in medium transmission range (less than 1500 m). The maximum data rate in such networks can reach about 10 kbps [10]. SDRT assumes that receivers can detect corrupted packets. This can be done by adding some redundant information in each packet. When a packet is unrecoverable from corruption, this packet is treated as lost. In this paper, we are interested in reconstructing lost packets, not error correction within packets.

In SDRT, the data source first groups data packets into blocks. The data packets are delivered from the source to the destination block by block, and hop-by-hop. An intermediate node encodes each data block using an efficient erasure codes. (In this work, a simple variant of Tornado codes [11], referred to as SVT codes, is proposed for SDRT.) and pumps encoded packets into its channel. When a receiver receives the encoded packets, it decodes and reconstructs the original block. After the reconstruction is done, the receiver encodes the block again and relays the block to the nodes in next hop. For each relay of a block, the sender keeps pumping encoded packets until receiving a positive feedback from next hop.

Our contributions can be summarized are follows:

• We design a reliable data transfer protocol, SDRT, which can well satisfy the harsh requirements in underwater sensor networks: efficient erasure codes enable SDRT to improve channel utilization significantly and relieve both senders and receivers of handling excessive feedbacks as in pure ARQ; along with SDRT, we propose SVT codes, simplified Tornado codes, which have easy and quick encoding and decoding algorithms, making it practical to encode and decode data packets hop-by-hop.

• We develop a novel window control mechanism to reduce the unnecessary data transmission caused by the large RTT and half-duplex acoustic modem. A mathematical model for the sender to estimate the expected number of needed packets is proposed for SDRT with SVT codes. This model also enables the sender to address the dynamic network topology problem. SDRT controls the transmission time of each block by setting an appropriate block size, which loosens the stability requirement for the underlying network topology.

• We conduct simulations to evaluate the performance of SDRT and our theoretical model. The results show that our SDRT is energy efficient and can achieve high channel utilization. And our simulations also verify our theoretical analysis.

The rest of this paper is organized as follows. We first present our SDRT protocol in Section 2 and give a brief review of our SVT codes in Section 3. After that, we develop a mathematical model to estimate the number of packets actually needed in Section 4. We then conduct simulations to evaluate our model and SDRT, and present the results in Section 5. Finally we discuss related work in Section 6. We conclude our paper in Section 7.