scholarly journals Residual Energy Estimation-Based MAC Protocol for Wireless Powered Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7617
Author(s):  
Sol-Bee Lee ◽  
Jung-Hyok Kwon ◽  
Eui-Jik Kim
Keyword(s):  
Sensor Networks ◽  
Energy Harvesting ◽  
Information Transfer ◽  
Mac Protocol ◽  
Residual Energy ◽  
Superior Performance ◽  
Medium Access ◽  
Energy Estimation ◽  
Sensor Devices ◽  
Multiple Sensor

This paper presents a residual energy estimation-based medium access control (REE-MAC) protocol for wireless powered sensor networks (WPSNs) composed of a central coordinator and multiple sensor devices. REE-MAC aims to reduce overhead due to control messages for scheduling the energy harvesting operation of sensor devices and provide fairness for data transmission opportunities to sensor devices. REE-MAC uses two types of superframes that operate simultaneously in different frequency bands: the wireless energy transfer (WET) superframe and wireless information transfer (WIT) superframe. At the beginning of each superframe, the coordinator estimates the change in the residual energy of individual sensor devices caused by their energy consumption and energy harvesting during the previous superframe. It then determines the devices’ charging priorities, based on which it allocates dedicated power slots (DPSs) within the WET superframe. The simulation results demonstrated that REE-MAC exhibits superior performance for the harvested energy, average freezing time, and fairness to existing representative WPSN MAC protocols.

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 Minimizing the Adverse Effects of Asymmetric Links: A Novel Cooperative Asynchronous MAC Protocol for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2402 ◽  
Author(s):  
Md. Mahedee Hasan ◽  
Amit Karmaker ◽  
Mohammad Shah Alam ◽  
Andrew Craig
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cooperative Communication ◽  
Mac Protocol ◽  
Research Work ◽  
Wireless Sensor ◽  
Medium Access ◽  
Link Asymmetry ◽  
Asymmetric Link ◽  
Asymmetric Links

As Wireless Sensor Networks (WSNs) grow in popularity, researchers are now focusing more on some challenging issues that significantly degrade overall performance, such as energy hole mitigation, link asymmetry minimization, etc. Link asymmetry is a problem that arises when the coverage distance between two adjacent nodes varies. It creates an obstacle to overcome when designing an efficient Medium Access Control (MAC) protocol for WSNs with low duty-cycling. This phenomenon poses an especially difficult challenge for receiver-initiated asynchronous MAC protocols, which are popular due to their relatively higher energy efficiency. Exploiting the benefits of cooperative communication has emerged as one of the viable solutions to overcome this limitation. Cooperative communication in WSNs has received a lot of attention in recent years. Many researchers have worked to create a MAC layer supporting cooperative communication. However, the association of cooperative communication with an asymmetric link is not studied in the literature. In this research work, COASYM-MAC, a cooperative asynchronous MAC protocol for WSNs, is proposed based on a receiver-initiated MAC protocol that uses the fact that nodes have alternate paths between them to reduce link asymmetry. A key feature of the proposed protocol is that the optimal helper node is selected automatically in case of link asymmetry. Simulations exhibited that COASYM-MAC performs significantly better than a state-of-the-art MAC protocol for WSNs that handles asymmetric links, ASYM-MAC.

scholarly journals Enhanced 3-D GM-MAC Protocol for Guaranteeing Stability and Energy Efficiency of IoT Mobile Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3230 ◽  
Author(s):  
Yoonkyung Jang ◽  
Ahreum Shin ◽  
Intae Ryoo
Keyword(s):  
Energy Efficiency ◽  
Sensor Networks ◽  
Mac Protocol ◽  
Buffer Management ◽  
Sensor Nodes ◽  
Mobile Sensor ◽  
Medium Access ◽  
Dimensional Group ◽  
Management Scheme ◽  
Group Number

In wireless sensor networks, energy efficiency is important because sensor nodes have limited energy. 3-dimensional group management medium access control (3-D GM-MAC) is an attractive MAC protocol for application to the Internet of Things (IoT) environment with various sensors. 3-D GM-MAC outperforms the existing MAC schemes in terms of energy efficiency, but has some stability issues. In this paper, methods that improve the stability and transmission performance of 3-D GM-MAC are proposed. A buffer management scheme for sensor nodes is newly proposed. Fixed sensor nodes that have a higher priority than the mobile sensor nodes in determining the group numbers that were added, and an advanced group number management scheme was introduced. The proposed methods were simulated and analyzed. The newly derived buffer threshold had a similar energy efficiency to the original 3-D GM-MAC, but improved performance in the aspects of data loss rate and data collection rate. Data delay was not included in the comparison factors as 3-D GM-MAC targets non-real-time applications. When using fixed sensor nodes, the number of group number resets is reduced by about 43.4% and energy efficiency increased by about 10%. Advanced group number management improved energy efficiency by about 23.4%. In addition, the advanced group number management with periodical group number resets of the entire sensor nodes showed about a 48.9% improvement in energy efficiency.

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