Reliable and Efficient Data Transfer for Underwater Acoustic Networks
نویسنده
چکیده
As an emerging research area, Underwater Acoustic Networks (UANs) have attracted tremendous interests in last several years. Reliable and efficient data transfer is of critical importance for UANs since it serves as the essential underlying service for various tasks. Due to the unique features of UANs including the long propagation delay, low bandwidth and high error probability, reliable and efficient data transfer has been facing great challenges. In this dissertation work, we plan to tackle this problem from three different perspectives. First, we design a Coding based multi-hop Coordinated Reliable Data Transfer (CCRDT) protocol for multi-hop string topology UANs. GF(256) Random Linear Coding is employed to enhance reliability and efficiency over one hop. A multi-hop coordination scheme is proposed to eliminate collisions and improve throughput. CCRDT has been implemented on real UAN nodes and extensive lab tests has been conducted to show its advantages over existing approaches. Second, we propose a Selective ARQ and Slotted Handshake based Access (SASHA) for arbitrary topology UANs. SASHA embraces the most commonly employed techniques in coordination based UAN MAC design. We implemented SASHA on real UAN nodes and conducted a sea test to evaluate its performance. We investigated the hop-by-hop and end-to-end behavior of SASHA. From the experimental data, important issues have been discovered and corresponding design guidelines are suggested. Last, to address the reliable and efficient broadcast problem for UANs, we propose a Two-phase Broadcast (TBS) scheme. TBS does not rely on topology or neighbor information and thus is more adaptive to the dynamic changes in UANs. TBS includes two phases: the Fast Spreading phase and the Data Recovery phase. The Fast Spreading phase combines opportunistic overhearing and network coding to improve broadcast efficiency. The Data Recovery phase aims to guarantee reliability and reduce interference probability. In this prospectus, we will present these three works in detail. We will also discuss the future directions to complete this Ph.D. dissertation.
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