UW-HARQ: An Underwater Hybrid ARQ Scheme: Design, Implementation and Initial Test

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1 UW-HARQ: An Underwater Hybrid ARQ Scheme: Design, Implementation and Initial Test Haining Mo, Ahmet Can Mingir, Hesham Alhumyani, Yusuf Albayram, and Jun-Hong Cui Computer Science & Engineering Department, University of Connecticut, Storrs, CT, USA {haining.mo, canmingir, hesham.alhumyani, yusuf.albayram, Abstract In this paper, we investigate reliable end-to-end data transfer in Underwater Acoustic Networks. A hybrid ARQ scheme, named UW-HARQ is proposed, which combines FEC coding and ARQ. For the FEC coding, Random Binary Linear Coding is employed due to its low coding and decoding complexity. An adaptive coding ratio estimation scheme, which incorporates the PER information, is proposed to minimize the number of retransmissions between the source and the destination. For the ARQ, NACK packets are utilized to inform the source node how many and which packets to send out in a retransmission and ACK packets are used as indications of data packet recovery success. We implemented UW-HARQ on real UAN nodes by leveraging our hardware and software platform. Initial lab test results show that UW-HARQ achieves a larger throughput than TCP-like approaches with a comparable overhead. I. INTRODUCTION Underwater Acoustic Networks (UANs) have recently attracted rapidly growing research interests [1], [2], [3] and significant efforts have been devoted to almost every layer of the protocol stack [4], [5], [6], [7], [8]. Reliable data transfer in UANs, as an unresolved problem, is facing two major challenges imposed by the harsh underwater environment. First, due to the multi-path fading, fish movement and highly dynamic underwater network nodes, acoustic channels suffer from high data error rates, Which causes a high probability of data retransmission in UANs, especially when there exists multiple hops in the network. Second, a retransmission over multiple hops can significantly increase the overall end-to-end delay of data transmission in UANs. The underlying reason is that acoustic signal rather than radio is employed as the medium for signal transmission in the water, which leads to long propagation delays in UANs. Automatic Repeat Request (ARQ) is a well studied technique to guarantee reliable data transfer in terrestrial networks. In case of packet loss, a Negative Acknowledgement (NACK) is sent back from the receiver to the sender and the sender will send out more data packets. This process repeats until an ACK is received by the sender. ARQ has also been applied to reliable data transfer in UANs. In [9], a simple stop and wait protocol is chosen as the ARQ scheme and the paper proposes that acknowledgement can be achieved both explicitly and implicitly. However, the fundamental problem with ARQ is that it has no data redundancy and therefore in UANs with high error probabilities, multiple retransmissions are required, which leads to a significant increase in overall end-to-end delay. To reduce the number of retransmissions, Forward Error Correction (FEC) coding is usually employed. FEC generally transmits both the original data packets and some additional encoded packets to provide data redundancy. In case of packet loss, there exists a high probability that the received data packets and encoded packets are still able to recover all the original data packets. Along this direction, Segmented Data Reliable Transport (SDRT) [10] is proposed which employs a Simplified Tornado Code and ACK to achieve multi-hop reliable data transfer in UANs. In SDRT, the sender first divides packets into multiple blocks. It then encodes each block and transmits packets fast inside a Window. The expectation is that the packets (including original data packets and encoded packets) in the Window are enough to recover the original data packets at the receiver. After that, it slows down data transmission, waiting for the response from the receiver. If the sender does not obtain an ACK from the receiver, it will send one and only one encoded packet to the receiver after it times out. This procedure continues until an ACK is received. The problem with SDRT is that, with only ACK employed, if retransmission needed, the sender has no idea which data packets are lost at the receiver and how many more data or encoded packets it should send out in a retransmission, which can lead to another data transmission failure. To address the above issues with conventional ARQ and FEC schemes, in this paper, we propose Underwater Hybrid ARQ (UW-HARQ), a hybrid ARQ scheme for reliable data transfer in UANs, which combines FEC coding and ARQ. For the FEC coding, we utilize Random Binary Linear Coding to minimize the coding and decoding complexity, which suits the low computation capability and power storage of the UAN nodes. For the ARQ, instead of using only ACK, we employ NACK packets to allow the receiver to notify the sender the data packets missing at the receiver and therefore the sender can decide how many and which packets to send out for the retransmissions. UW-HARQ has two advantages. Compared with pure ARQ method, it provides data redundancy and therefore largely reduces the chance of data retransmissions. On the other hand, compared with SDRT, it allows the sender to get feedback from the receiver in order to retransmit the right packets when a retransmission is required. Besides the design of UW-HARQ, a major contribution of this paper is that we implemented UW-HARQ on real UAN nodes utilizing an underwater network protocol stack framework Aqua-NET [11] and an underwater acoustic modem: Teledyne

2 2 Benthos modem [12]. We also conducted some initial lab tests using real UAN nodes and got some promising performance results of UW-HARQ. The rest of the paper is organized as follows. In Section II, we present the design of UW-HARQ, including the Random Binary Linear encoding and decoding as well as the ARQ procedure. In Section III, we describe the implementation details of UW-HARQ. Section IV gives the initial lab test results and demonstrates the advantages of UW-HARQ. Related works are discussed in Section V. We finally conclude the paper and discuss our future works in Section VI. II. PROTOCOL DESIGN UW-HARQ is a combination of FEC coding and ARQ. FEC coding is employed to reduce the number of retransmissions between the source node and the destination node by adding data redundancy in data transmission to alleviate the negative effects imposed by packet loss in underwater acoustic channels. In this paper, we employ Random Binary Linear Coding (RBLC) as the FEC coding scheme due to its low encoding and decoding complexity. By setting an appropriate coding ratio, we can guarantee with a high probability that the packets received at the destination node are enough to recover the original data packets despite the channel erasure. ARQ is utilized to guarantee the reliable data delivery at the destination node. A NACK packet is sent back to the sender to indicate a data recovery failure and request more packets while an ACK is sent back as an indication of data recovery success. In UW-HARQ, ARQ has another important purpose: to notify the sender of the Packet Error Rate (PER) between the source node and the destination node, which is an information carried over by the ACK and NACK packets. Utilizing the PER information, the sender can set a more accurate coding ratio to maximize the data recovery success probability at the destination node. A. Random Binary Linear Coding There are various candidates for FEC coding scheme including Tornado Coding, Fountain Coding and Random Linear Coding. In this paper, we choose RBLC as the coding scheme since its low computation complexity is suitable for UAN nodes, which are characterized by limited processing capability and power supply. In RBLC, each encoded packet is a random linear combination of multiple data packets. Here we use {x 1,x 2,..., x k } to denote k original data packets and {y 1,y 2,..., y n } to denote n encoded packets, then: y j = a j1 x 1 a j2 x 2... a jk x k = k a ji x i i=1 j [1,n] a ji = {0, 1} (1) In this paper, C = n k 1 is defined as the RBLC coding ratio. Coding ratio C is critical for the performance of UW- HARQ. If we assign a too small value for C, due to the packet loss, retransmissions are going to be incurred to recover all the k data packets at the destination node, which can significantly increase overall end-to-end delay between the source and the destination. On the other hand, a too large C is going to cause the source node to send out unnecessary encoded packets, which leads to a larger energy consumption. Obviously, in order to minimize the overall end-to-end delay, we need to guarantee that each transmission of n encoded packets between the source node and the destination node is able to recover k data packets with a high probability. [13] points out that using RBLC, the optimal coding ratio C can be set using the following equation: k 1 1 (1 2 i (1+C) k ) δ (2) i=0 Here k is the number of the data packets and δ is defined as the decoding failure probability, which should be set to a very small value to minimize the number of retransmissions. However, the above optimal coding ratio C is obtained with the assumption that there is no packet loss between the source node and the destination node. In the real world UANs with a non-negligible PER, the actual coding ratio C needs to be larger than C in Eq. 2 to counter the packet loss of the acoustic channels. UW-HARQ incorporates the theoretically optimal coding ratio C and the PER information to estimate the actual optimal coding ratio C. The PER information is obtained via the ACK/NACK packets. Whenever the destination node sends back an ACK or NACK packet to the source node, it embeds the number of packets received in the last transmission of encoded packets. Upon receiving an ACK or NACK, the source node can calculate the PER using this piece of information and the recorded total number of encoded packets sent out in the last transmission. Then the actual optimal coding ratio C can be set as: C C = (3) 1 PER The coding ratio estimation scheme of UW-HARQ is more adaptable to the dynamic link qualities of the underwater acoustic channels by incorporating the PER information. It also achieves a very small communication overhead since the only additional information transmitted is the number of packets received, which is carried over by the ACK and NACK packets. B. ARQ The purpose of ARQ in UW-HARQ are in two folds. On one hand, the ACK and NACK packets sent back contain the number of packets received and therefore can be leveraged by the sender to estimate the current PER between the source and the destination. On the other hand, different from SDRT, UW-HARQ utilizes NACK to inform the source how many and which data packets are missing at the destination and therefore the source node can make the right decision on which encoded packets to send out in a retransmission to guarantee the destination is able to recover the missing data packets. The ARQ procedure of UW-HARQ is shown in Fig. 1. First, the source node groups k data packets into one block and

3 3 Encoded Packets N Step 1 NACK ACK # of packets received, # of packets needed N Step 2 More Encoded Packets N Step Fig. 1. # of packets received 3 N Step Final Illustration of ARQ in UW-HARQ encodes them into C k encoded packets using RBLC. C is decided by Eq. 3 and we set the initial PER to be 0. Instep 2, if the destination node fails to recover the k data packets from the received encoded packets, it sends back a NACK to the source node. The NACK packet contains the number of encoded packets received, which is leveraged by the source node to update the PER information, and n, which is the number of encoded packets still needed to recover the missing data packets. In step 3, utilizing the updated PER and n,the source node can decide how many and which encoded packets to send out in the retransmission. This procedure continues until an ACK packet is received at the source node, indicating all the k data packets have been successfully recovered at the destination node. Therefore, by employing RBLC and the adaptive coding ratio estimation scheme, UW-HARQ can guarantee with a high probability that one transmission of encoded packets is enough to recover all the original data packets at the destination node and therefore minimize the number of retransmissions. UW- HARQ also utilizes ARQ not only to guarantee reliable data delivery but also to notify the source node about the PER and the missing data packets, which is leveraged by the source node to determine how many and which encoded packets to send out in a retransmission. III. PROTOCOL IMPLEMENTATION In order to verify the design and evaluate the performance, we implemented UW-HARQ on real UAN nodes. In this section, we describe the hardware and software platform as well as the implementation details of UW-HARQ. A. Hardware and Software Platform The hardware platform of a UAN node is composed of a Gumstix [14], which is the controller of the UAN node, and a Teledyne Benthos Modem [12], which conducts the acoustic communications in order to send and receive packets. The software platform of a UAN node include Embedded Linux, which is the operating system running on Gumstix, and an underwater network protocol stack: Aqua-NET [11]. Aqua- NET is a layered protocol stack including the physical layer, MAC layer, routing layer, transport layer and application layer. Using Aqua-NET, a developer can easily and seamlessly plug in one protocol running as a single layer or multiple protocols running on different layers. As an end-to-end reliable data Fig. 2. Poisson Traffic UW-HARQ Static Routing Broadcast MAC Benthos Driver Embedded Linux Gumstix Benthos Modem Aqua-NET UAN OS UAN Controller UAN Software UAN Hardware UAN Communication Device Hardware and software architecture of UW-HARQ =1 =2 =3 Fig. 3. Encoding Vector received received Encoded Message still needed NULL NULL Packet types in UW-HARQ transfer protocol, we implemented UW-HARQ on the transport layer of Aqua-NET. For the other layers, we use Poisson Traffic Generator on the application layer, which generates traffic with time interval between every two packets following a Poisson distribution, Static Routing on the routing layer, Broadcast MAC on the MAC layer, and Benthos modem driver on the physical layer. The architecture of UW-HARQ implementation is shown in Fig. 2. B. Implementation Details UW-HARQ defines three types of packets: DATA, NACK and ACK, as shown in Fig. 3. One byte in the transport layer header is utilized to indicate the packet type. For the data packet, the encoding vector is embedded in the transport layer header and therefore the destination node can retrieve the encoding vectors to decode the original data packets. The NACK packet header contains the number of packets received in the last transmission, which is to be retrieved by the source node to update the PER information, and the number of packets still needed to recover the data packets, which is leveraged by the source node to determine how many and which encoded packets to send out in a retransmission. The ACK packet header only carries over the number of packets received in the last transmission for the source node to reestimate the PER. Both ACK and NACK packets have an empty data section. IV. INITIAL TEST RESULTS To evaluate the performance of UW-HARQ, initial lab tests are conducted utilizing Aqua-NET and our lab testbed Aqua- TUNE [15]. A typical experiment setup is shown in Fig. 4. In this setup, we are using 6 Teledyne Benthos modems in total: DATA NACK ACK

4 Throughput (bps) Fig. 4. Experiment setup Fig Packet Length 80 End-to-end throughput with varying packet lengths 4 ATM-920 modems, 1 UDB-9000 Deck Box modem and 1 SM-75 Smart modem [12]. These three models of Teledyne Benthos modems provide the same interface for upper layer software and have the same performance parameters in terms of acoustic communication. Each modem is connected to a Gumstix, on which UW-HARQ is running on top of embedded Linux and Aqua-NET. In order to evaluate the performance of UW-HARQ, we implemented a TCP-like approach Aqua-SARQ as the baseline. Aqua-SARQ utilizes sliding window and selective acknowledgement to achieve end-to-end reliability. The source node transmits the data packets inside the sliding window to the destination node. An ACK is sent back after the destination receives one or more data packets and therefore the source can slide the window and send out new data packets. In our lab test, unless otherwise specified, the network parameters are as follows: The hop count is 4; The block size is 5, meaning every 5 data packets are grouped into one block and encoded; The packet length is 200; The modem acoustic bit rate is 800bps; The sliding window size for Aqua-SARQ is 1. We evaluate the performance of UW-HARQ and Aqua- SARQ based on two metrics. End-to-end throughput is defined as the number of bits delivered to the destination node per second (bps). Overhead is defined as the ratio between the number of extra packets and the number of data packets transmitted over multiple hops in the network. In the succeeding sections, we are going to discuss the two metrics of UW-HARQ and Aqua-SARQ under different conditions. A. Impact of Packet Length In this section, we study the impact of packet length on the end-to-end throughput of UW-HAQR and Aqua-SARQ. We vary the packet length between 50 and 800 and the result is shown in Fig. 5. As we can see, the throughput of UW-HARQ is larger than that of Aqua-SARQ and the advantage of UW-HARQ becomes larger as the packet length increases. The reason is that UW-HARQ utilizes RBLC and coding ratio estimation to counter the packet loss between the source and the destination and therefore achieves a higher throughput. Aqua-SARQ, on the other hand, does not have any data redundancy and therefore each packet loss will lead to a Throughput (bps) Hop Couunt Fig. 6. End-to-end throughput with varying hop counts retransmission over multiple hops. This significantly degrades end-to-end throughput. The PER becomes larger as the packet length increases and this explains why the advantage of UW- HARQ over Aqua-SARQ increases with larger packet lengths. B. Impact of Hop Count The impact of hop count on the end-to-end throughput of UW-HARQ and Aqua-SARQ is shown in Fig. 6. Generally speaking, UW-HARQ outperforms Aqua-SARQ in terms of throughput, especially with larger hop counts. With a larger hop count, there is a larger possibility that there exists a link between the source and the destination with high PER, which can largely increase the chance of end-to-end packet delivery failure. This fact leads to more retransmissions for Aqua- SARQ as the hop count increases. UW-HARQ, on the other hand, suffers much less from the packet loss due to the RBLC and the adaptive coding ratio estimation. C. Overhead In this section, we investigate the overhead of UW-HARQ and Aqua-SARQ, which is measured by the ratio between the number of extra packets and the number of data packets. The result is shown in Fig. 7. We vary the block size between 5 and 25. We can see that the overhead of UW-HARQ is larger than that of Aqua-SARQ but still comparable. The more extra packets transmitted in UW-HARQ come from the data redundancy, which are used to reduce the number of retransmissions between the source and the destination.

5 5 Number of extra packets/nubmber of data packets Block Size Fig. 7. Overhead with varying block sizes V. RELATED WORKS Reliable data transfer in Terrestrial Wireless Networks has been well studied. [16] proposes a window-less block ACK scheme to improve the efficiency of channel utilization. A contention control scheme is also employed to reduce the overall end-to-end delay. In [17], the authors propose a crosslayer scheme to enhance the reliability and efficiency of endto-end data transfer. These schemes cannot be directly applied to UANs due to the unique characteristics of the underwater networks. Efficient reliable data transfer in UANs has also attracted a lot of research interests. SDRT has been studied in detail in Section I. Fountain Coding has been widely used for reliable data transfer and storage in UANs. In [18], the authors employ fountain code to enhance the reliability and efficiency of broadcasting in UANs. Also a fountain code based reliable data transport and storage protocol for UANs is proposed in [19]. The authors utilize a concatenated fountain coding mechanism to improve the reliability of data transport and storage in a UAN with zone-based architecture. All these approaches are based on theoretical analysis and simulations. To the best of our knowledge, so far there has been no Hybrid ARQ based reliable data transfer scheme implemented on real UAN nodes and tested in lab testbed. VI. CONCLUSIONS AND FUTURE WORK In this paper, we propose an underwater Hybrid ARQ scheme UW-HARQ for multiple hop reliable data transfer in UANs, which is a combination of FEC coding and ARQ. Random Binary Linear Coding is employed as the FEC coding to minimize the computation complexity. A coding ratio estimation scheme is proposed to significantly reduce the number of retransmissions by taking into account the PER between the source and the destination. For the ARQ, UW- HARQ employs NACK to send feedback to the source and therefore the source node can update the PER information and determine which encoded packets to send in a retransmission. In addition to the design of the protocol, we implemented UW-HARQ on real UAN nodes utilizing Aqua-NET and Teledyne Benthos modem. We also conducted initial lab tests by leveraging our lab testbed Aqua-TUNE. Test results show that UW-HARQ outperforms a TCP-like reliable data transfer approach Aqua-SARQ in terms of end-to-end throughput and achieves a comparable overhead. In terms of future work, we are going to conduct more lab tests and field tests to compare the performance of UW- HARQ with other reliable data transfer schemes in UANs including SDRT. Also we plan to design a hop-by-hop Hybrid ARQ scheme to further improve the end-to-end throughput of reliable data transfer in UANs. REFERENCES [1] Ian F. Akyildiz, Dario Pompili, and Tommaso Melodia. 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