scholarly journals A MAC Protocol of Concurrent Scheduling Based on Spatial-Temporal Uncertainty for Underwater Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xin Liu ◽  
Xiujuan Du ◽  
Meiju Li ◽  
Lijuan Wang ◽  
Chong Li
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Mac Protocol ◽  
Average Energy ◽  
Propagation Delay ◽  
Spatial Uncertainty ◽  
Underwater Sensor Networks ◽  
Temporal Uncertainty ◽  
Concurrent Scheduling ◽  
Time Division

Underwater sensor networks (UWSNs) are characterized by large energy consumption, limited power supply, low bit rate, and long propagation delay, as well as spatial-temporal uncertainty, which present both challenges and opportunities for media access control (MAC) protocol design. The time-division transmissions can effectively avoid collisions since different nodes transmit packets at different period of time. Nevertheless, in UWSNs with long propagation delay, in order to avoid collisions, the period of time is subject to be long enough, which results in poor channel utilization and low throughput. In view of the long and different propagation delay between a receiving node and multiple sending nodes in UWSNs, as long as there is no collision at the receiving node, multiple sending nodes can transmit packets simultaneously. Therefore, in this paper, we propose a MAC protocol of concurrent scheduling based on spatial-temporal uncertainty called CSSTU-MAC (concurrent scheduling based on spatial-temporal uncertainty MAC) for UWSNs. The CSSTU-MAC protocol utilizes the characteristics of temporal-spatial uncertainty as well as long propagation delay in UWSNs to achieve concurrent transmission and collision avoidance. Simulation results show that the CSSTU-MAC protocol outperforms the existing MAC protocol with time-division transmissions in terms of average energy consumption and network throughput.

DOTS: A propagation Delay-aware Opportunistic MAC protocol for underwater sensor networks

2010 ◽  
Author(s):  
Youngtae Noh ◽  
Paul Wang ◽  
Uichin Lee ◽  
Dustin Torres ◽  
Mario Gerla
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Underwater Sensor Networks

scholarly journals RLT Code Based Handshake-Free Reliable MAC Protocol for Underwater Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Xiujuan Du ◽  
Keqin Li ◽  
Xiuxiu Liu ◽  
Yishan Su
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Small Degree ◽  
Underwater Sensor Networks ◽  
Medium Access ◽  
Reliable Transmission ◽  
Underwater Acoustic Channels ◽  
End To End ◽  
Low Efficiency

The characteristics of underwater acoustic channels such as long propagation delay and low bit rate cause the medium access control (MAC) protocols designed for radio channels to either be inapplicable or have low efficiency for underwater sensor networks (UWSNs). Meanwhile, due to high bit error, conventional end-to-end reliable transfer solutions bring about too many retransmissions and are inefficient in UWSN. In this paper, we present a recursive LT (RLT) code. With small degree distribution and recursive encoding, RLT achieves reliable transmission hop-by-hop while reducing the complexity of encoding and decoding in UWSN. We further propose an RLT code based handshake-free (RCHF) reliable MAC protocol. In RCHF protocol, each node maintains a neighbor table including the field of state, and packages are forwarded according to the state of a receiver, which can avoid collisions of sending-receiving and overhearing. The transmission-avoidance time in RCHF decreases data-ACK collision dramatically. Without RTS/CTS handshaking, the RCHF protocol improves channel utilization while achieving reliable transmission. Simulation results show that, compared with the existing reliable data transport approaches for underwater networks, RCHF can improve network throughput while decreasing end-to-end overhead.

A Cooperative MAC Scheduling Scheme for Underwater Sensor Networks

2013 ◽  
Vol 295-298 ◽  
pp. 903-908 ◽  
Author(s):  
Khoa Thi Minh Tran ◽  
Seung Hyun Oh
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Sensor Nodes ◽  
Media Access Control ◽  
Underwater Sensor Networks ◽  
Media Access ◽  
Acoustic Sensor Networks ◽  
Data Message ◽  
Cooperative Mac

The long propagation delay in underwater acoustic sensor networks renders existing media access control (MAC) protocols for terrestrial wireless networks undesirable. In this paper, we propose a new cooperative MAC protocol for underwater sensor networks that is used to detect objects and monitoring the environment. Our proposed MAC protocol tries to prevent data collisions through short term scheduling among neighbor nodes with exchange of short data message. By adapting the all sensor nodes to the transmitting schedules in which time is optimized we can minimize the collision rate between nodes. Through simulations, we show our proposed protocol can minimize data collisions and not only offers a higher throughput, but also indicates a better end-to-end delay.

scholarly journals Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4368
Author(s):  
Jitander Kumar Pabani ◽  
Miguel-Ángel Luque-Nieto ◽  
Waheeduddin Hyder ◽  
Pablo Otero
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Real Life ◽  
Base Station ◽  
Fuzzy Decision Making ◽  
Underwater Sensor Networks ◽  
Packet Forwarding ◽  
Node Number ◽  
The Impact

Underwater Wireless Sensor Networks (UWSNs) are subjected to a multitude of real-life challenges. Maintaining adequate power consumption is one of the critical ones, for obvious reasons. This includes proper energy consumption due to nodes close to and far from the sink node (gateway), which affect the overall energy efficiency of the system. These wireless sensors gather and route the data to the onshore base station through the gateway at the sea surface. However, finding an optimum and efficient path from the source node to the gateway is a challenging task. The common reasons for the loss of energy in existing routing protocols for underwater are (1) a node shut down due to battery drainage, (2) packet loss or packet collision which causes re-transmission and hence affects the performance of the system, and (3) inappropriate selection of sensor node for forwarding data. To address these issues, an energy efficient packet forwarding scheme using fuzzy logic is proposed in this work. The proposed protocol uses three metrics: number of hops to reach the gateway node, number of neighbors (in the transmission range of a node) and the distance (or its equivalent received signal strength indicator, RSSI) in a 3D UWSN architecture. In addition, the performance of the system is also tested with adaptive and non-adaptive transmission ranges and scalable number of nodes to see the impact on energy consumption and number of hops. Simulation results show that the proposed protocol performs better than other existing techniques or in terms of parameters used in this scheme.

scholarly journals Packet Flow Based Reinforcement Learning MAC Protocol for Underwater Acoustic Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2284
Author(s):  
Ibrahim B. Alhassan ◽  
Paul D. Mitchell
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Basic Function ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Medium Access ◽  
Underwater Acoustic ◽  
Q Learning ◽  
Acoustic Sensor Networks

Medium access control (MAC) is one of the key requirements in underwater acoustic sensor networks (UASNs). For a MAC protocol to provide its basic function of efficient sharing of channel access, the highly dynamic underwater environment demands MAC protocols to be adaptive as well. Q-learning is one of the promising techniques employed in intelligent MAC protocol solutions, however, due to the long propagation delay, the performance of this approach is severely limited by reliance on an explicit reward signal to function. In this paper, we propose a restructured and a modified two stage Q-learning process to extract an implicit reward signal for a novel MAC protocol: Packet flow ALOHA with Q-learning (ALOHA-QUPAF). Based on a simulated pipeline monitoring chain network, results show that the protocol outperforms both ALOHA-Q and framed ALOHA by at least 13% and 148% in all simulated scenarios, respectively.

scholarly journals Receiver-Initiated Handshaking MAC Based on Traffic Estimation for Underwater Sensor Networks ‡

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3895 ◽  
Author(s):  
Yuan Dong ◽  
Lina Pu ◽  
Yu Luo ◽  
Zheng Peng ◽  
Haining Mo ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Sensor Networks ◽  
Propagation Delay ◽  
Mac Protocols ◽  
Underwater Sensor Networks ◽  
Medium Access ◽  
The Status ◽  
Efficient Data ◽  
Traffic Estimation ◽  
Delay Tolerant

In underwater sensor networks (UWSNs), the unique characteristics of acoustic channels have posed great challenges for the design of medium access control (MAC) protocols. The long propagation delay problem has been widely explored in recent literature. However, the long preamble problem with acoustic modems revealed in real experiments brings new challenges to underwater MAC design. The overhead of control messages in handshaking-based protocols becomes significant due to the long preamble in underwater acoustic modems. To address this problem, we advocate the receiver-initiated handshaking method with parallel reservation to improve the handshaking efficiency. Despite some existing works along this direction, the data polling problem is still an open issue. Without knowing the status of senders, the receiver faces two challenges for efficient data polling: when to poll data from the sender and how much data to request. In this paper, we propose a traffic estimation-based receiver-initiated MAC (TERI-MAC) to solve this problem with an adaptive approach. Data polling in TERI-MAC depends on an online approximation of traffic distribution. It estimates the energy efficiency and network latency and starts the data request only when the preferred performance can be achieved. TERI-MAC can achieve a stable energy efficiency with arbitrary network traffic patterns. For traffic estimation, we employ a resampling technique to keep a small computation and memory overhead. The performance of TERI-MAC in terms of energy efficiency, channel utilization, and communication latency is verified in simulations. Our results show that, compared with existing receiver-initiated-based underwater MAC protocols, TERI-MAC can achieve higher energy efficiency at the price of a delay penalty. This confirms the strength of TERI-MAC for delay-tolerant applications.

scholarly journals Improving Duty Cycle-based MAC Protocol in Wireless Networks using AI and Machine Learning

2019 ◽  
Vol 9 (2) ◽  
pp. 3011-3017
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Duty Cycle ◽  
Mac Protocol ◽  
Selection Function ◽  
Medium Access ◽  
Sleep Phase ◽  
Agricultural Applications ◽  
Time Division ◽  
Wireless Node

Duty cycle of a Medium Access Control (MAC) protocol is made up of sleep phase, wake-up phase and listen phase. MAC protocols usually proposes to optimize the duration of the wake-up and listen phases, in order to increase the duration of the sleep phase, thereby reducing the unwanted energy consumption of the wireless node. In this paper, we propose an Artificial Intelligence (AI) and machine learning (ML) based approach, which uses a hybrid combination of Time Division Multiple Access (TDMA), Bitmap Assisted MAC (BMA) and Sensor MAC (SMAC). The machine learning layer utilizes the duty cycle in the MAC layer, and generates multiple solutions for a given wireless communication. The AI layer then selects the best solution from the generated solutions by incorporating a duty cycle factor in the selection function, thereby optimizing the duty cycle of the protocol. The proposed system shows a 15% improvement in communication speed, and a 10% reduction in energy consumption across multiple communications. We plan to further extend this work for rural India, and apply it to real time agricultural applications.

scholarly journals Energy-Efficient MAC Protocol for Wireless Sensor Networks - A Review

2012 ◽  
pp. 107-111
Author(s):  
Smriti Joshi ◽  
Anant Kr. Jayswal
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Load Balance ◽  
Mac Protocol ◽  
Average Energy ◽  
Wireless Sensor ◽  
Wsn Lifetime

Energy efficiency is the kernel issue in the designing of wireless sensor network(WSN) MAC protocols. Energy efficiency is a major consideration while designing wireless sensor network nodes. Most sensor network applications require energy autonomy for the complete lifetime of the node, which may span up to several years. These energy constraints require that the system be built such that Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. Each component consumes minimum possible power, ensure the average successful transmission rate, decrease the data packet average waiting time, and reduce the average energy consumption. Influencing by the design principles of traditional layered protocol stack, current MAC protocol designing for wireless sensor networks (WSN) seldom takes load balance into consideration, which greatly restricts WSN lifetime. As a novel Forwarding Election-based MAC protocol, is presented to prolong WSN lifetime by means of improving energy efficiency and enhancing load balance.

scholarly journals Energy-Efficient and Fast MAC Protocol in UAV-Aided Wireless Sensor Networks for Time-Critical Applications

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2635 ◽  
Author(s):  
Sabitri Poudel ◽  
Sangman Moh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Multiple Access ◽  
Mac Protocol ◽  
Mac Protocols ◽  
Wireless Sensor ◽  
Sensing Applications ◽  
Time Critical

Unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs) can be effectively used for time-critical sensing applications. UAVs can be used to collect the sensed data from sensors and transfer them to a base station. The real-time transfer of data is highly desired in the time-critical applications. However, the medium access control (MAC) protocols designed for UWSNs so far are primarily focused on the efficient use of UAVs to collect data in the sensing areas. In this paper, we propose an energy-efficient and fast MAC (EF-MAC) protocol in UWSNs for time-critical sensing applications. EF-MAC adopts carrier sense multiple access (CSMA) for the registration of sensor nodes with a UAV and time division multiple access (TDMA) with variable slot time for the transmission of collected data. The UAV is equipped with two transceivers to minimize both energy consumption and delay in air-to-ground communication. The energy consumption and delay are formally analyzed and the performance of EF-MAC is evaluated via extensive simulation. The simulation results show that the proposed EF-MAC outperforms the conventional MAC protocols in terms of energy efficiency and communication delay.

An Energy Aware Routing Based on Swarm Intelligence for Wireless Sensor Networks

2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.

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