UCMAC: A Cooperative MAC Protocol for Underwater Wireless Sensor Networks

Kim, Hee-won; Im, Tae Ho; Cho, Ho-Shin

doi:10.3390/s18061969

Cited by 17 publications

(21 citation statements)

References 35 publications

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“…The proposed protocol also supports multiple handshakes and concurrent transmissions as DSCT, except that the handshaking is implemented in a dedicated control channel by TDMA and the transmission rate of the data channel is reduced. The throughput, packet delivery rate, average end-to-end delay, average energy consumption and normalized offered load are defined as [29]:…”

Section: Simulations and Resultsmentioning

confidence: 99%

A Collision-Free Hybrid MAC Protocol Based on Pipeline Parallel Transmission for Distributed Multi-Channel Underwater Acoustic Networks

Xiong

Ning

2020

Electronics

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The transmission rate between two nodes is usually very low in underwater acoustic networks due to the low available bandwidth of underwater acoustic channels. Therefore, increasing the transmission parallelism among network nodes is one of the most effective ways to improve the performance of underwater acoustic networks. In this paper, we propose a new collision-free hybrid medium access control (MAC) protocol for distributed multi-channel underwater acoustic networks. In the proposed protocol, handshaking and data transmission are implemented as a pipeline on multiple acoustic channels. Handshaking is implemented using the time division multiple access (TDMA) technique in a dedicated control channel, which can support multiple successful handshakes in a transmission cycle and avoid collision in the cost of additional delay. Data packets are transmitted in one or multiple data channels, where an algorithm for optimizing the transmission schedule according to the inter-nodal propagation delays is proposed to achieve collision-free parallel data transmission. Replication computation technique, which is usually used in parallel computation to reduce the requirement of communication or execution time, is used in the data packet scheduling to reduce communication overhead in distributed environments. Simulation results show that the proposed protocol outperforms the slotted floor acquisition multiple access (SFAMA), reverse opportunistic packet appending (ROPA), and distributed scheduling based concurrent transmission (DSCT) protocols in throughput, packet delivery rate, and average energy consumption in the price of larger end-to-end delay introduced by TDMA based handshaking.

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Section: Simulations and Resultsmentioning

confidence: 99%

A Collision-Free Hybrid MAC Protocol Based on Pipeline Parallel Transmission for Distributed Multi-Channel Underwater Acoustic Networks

Xiong

Ning

2020

Electronics

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“…In the simulations, the normalized throughput, packet delivery rate, average end-to-end delay, and average energy consumption of the proposed method are compared with underwater ALOHA (UWALOHA), underwater carrier sense multiple access/collision avoidance (UW-CSMA/CA), slotted floor acquisition multiple access (SFAMA) and ROPA protocols with different network loads and node numbers. The normalized throughput, packet delivery rate, average end-to-end delay, average energy consumption and normalized offered load are defined as [23]: Normalized throughput: The ratio of the average number of data bits successfully received by the intended destinations per second to the transmission bit rate (dimensionless).Packet delivery rate: The ratio of the number of data packets successfully delivered at the intended destinations to the total number of data packets generated (dimensionless).Average end-to-end delay: The average time interval between generation and successful delivery of data packets at the intended destinations (in ms).Average energy consumption: The ratio of the total energy consumption to the number of data packets successfully received by the intended destinations (in Joule/packet or J/pkt).Normalized offered load: The ratio of the average number of data bits sent per second to the transmission bit rate (dimensionless).…”

Section: Simulations and Resultsmentioning

confidence: 99%

Concurrent Transmission Based on Distributed Scheduling for Underwater Acoustic Networks

Zhang

Lai

Xiong

2019

Sensors

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Handshaking is a common technique used to avoid collisions in terrestrial and underwater content-based networks. However, due to the long propagation delay of the underwater acoustic channel, the conventional handshaking mechanism, which only allows one successful handshake and one pair of nodes to communicate per transmission cycle, becomes less effective in underwater acoustic networks. This paper proposes a new distributed scheduling method for underwater acoustic networks that supports multiple handshakes and concurrent transmissions in one transmission cycle for one-hop clusters. A deterministic scheduling algorithm was developed to optimize the sending sequence and time of the source nodes jointly so that the total data transmission time is shortened while avoiding collisions among multiple concurrent transmissions. The deterministic scheduling algorithm can also reduce the scheduling overhead and enables the synchronization of the data concurrent transmissions in a distributed manner via the standard two-way handshaking. Simulation results show that the proposed method outperforms several conventional underwater medium access control protocols in normalized throughput, packet delivery rate, average end-to-end delay, and average energy consumption.

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“…In the case of IoUT, by the environmental specificity, onsurface wireless communication systems cannot be applied [13]- [17]. Therefore, many different IoUT models that fit the underwater characteristics have been suggested [24]- [29]. The method tuned to fit the underwater environment was suggested based on the IEEE 802.11 protocol used on the surfaces [6], [28].…”

Section: A Backgroundmentioning

confidence: 99%

Intelligent Handover Prediction Based on Locational Priority With Zero Scanning for the Internet of Underwater Things

Park

2020

IEEE Access

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It is becoming clear that the maritime industry is expected to see considerable growth over the coming years, and the Internet of Underwater Things (IoUT) could have an essential role to play in its technological development. In this regard, because batteries are the main power source in underwater environments, there is a clear need to minimize the consumption of energy. In addition, underwater links that make use of acoustic soundwaves can cause relatively long propagation delays. In our proposed scheme, we focus on the initial connection procedure between sensor nodes and underwater base stations to tackle these environmental problems, in which the former estimates the signal strength of the latter. From local information measured during the initial network entry phase, underwater sensor nodes determine locational priority of candidate targets, but do not scan or measure the signal strength of other neighbouring underwater base stations as a means of keeping the power consumption to an absolute minimum. This can be considered an appropriate scenario for use in severely battery-limited environments such as IoUT. Based on analysis using machine learning, we obtain meaningful clues regarding the procedure for handover prediction without channel measurement. By removing the overhead from the channel measurement, the power consumption of the underwater things can be minimized. Two different methods of deciding on handover priority are suggested and analysed mathematically. The performance of each method is evaluated through intensive system-level simulations and compared to that of a more conventional scheme.

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UCMAC: A Cooperative MAC Protocol for Underwater Wireless Sensor Networks

Cited by 17 publications

References 35 publications

A Collision-Free Hybrid MAC Protocol Based on Pipeline Parallel Transmission for Distributed Multi-Channel Underwater Acoustic Networks

A Collision-Free Hybrid MAC Protocol Based on Pipeline Parallel Transmission for Distributed Multi-Channel Underwater Acoustic Networks

Concurrent Transmission Based on Distributed Scheduling for Underwater Acoustic Networks

Intelligent Handover Prediction Based on Locational Priority With Zero Scanning for the Internet of Underwater Things

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