Prolong network lifetime and improve efficiency in WSN‐UAV systems using new clustering parameters and CSMA modification

Tarighi, Reza; Farajzadeh, Kamran; Hematkhah, Hooman

doi:10.1002/dac.4324

Cited by 9 publications

(4 citation statements)

References 29 publications

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“…20 While the deployment of WSN offers a promising solution, it is not without its challenges, including sensor node lifespan limitations, packet loss issues, and routing complexities. [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] Therefore, an imperative requirement in disaster management scenarios is the implementation of an energy-efficient routing protocol tailored to the specific demands of WSNs. Bio-inspired routing protocols emerge as a viable option due to their adaptability in addressing multiple and intricate objective functions.…”

Section: Motivationmentioning

confidence: 99%

“…In such critical situations, the urgency of communication is paramount to ensure the swift delivery of crucial relief to disaster victims 20 . While the deployment of WSN offers a promising solution, it is not without its challenges, including sensor node lifespan limitations, packet loss issues, and routing complexities 21–36 . Therefore, an imperative requirement in disaster management scenarios is the implementation of an energy‐efficient routing protocol tailored to the specific demands of WSNs.…”

Section: Introductionmentioning

confidence: 99%

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An enhanced bio‐inspired energy‐efficient localization routing for mobile wireless sensor network

Tumula,

Rama Devi,

Ramadevi

et al. 2024

Int J Communication

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SummaryEnvironmental disasters such as earthquakes, tsunamis, floods, and landslides disrupt natural resources, human casualties, and so on. Early warning and alert of such events will help for preparedness to avoid human and economic causalities. Managing a disaster or emergency scenario is a difficult endeavor. These episodes of mass devastation, whether caused by natural disasters or man‐made disasters, result in massive losses of money, property, and lives as a result of inadequate response by the government and management authorities. As a result, actions must be taken to avoid these circumstances from occurring by discovering the causes of these catastrophes in advance and providing swift rescue procedures once the crisis happens. In a disaster situation, communication plays a vital role, and a lot of people turn towards it as a source of information conveyance/delivery for controlling the situation. Even these communication networks are damaged and incur tremendous losses during disasters. All the communication networks, including mobile wireless sensor networks (WSNs) deployed for communication, also suffer huge damage and face many challenges during disasters. Nature appears to deal with these issues well. WSN is inspired by several biological systems and processes that have intrinsically attractive properties such as adaptation, self‐organization, and self‐healing. In this paper, we proposed an enhanced bio‐inspired energy‐efficient localization (EBEEL) routing for Mobile WSN. The main focus of the proposed EBEEL algorithm is to overcome the challenges faced by peer‐existing routing protocols such as data aggregation, limited bandwidth, scalability, data redundancy, energy consumption, packet drops, load balancing, and Quality of Service (QoS).

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Section: Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An enhanced bio‐inspired energy‐efficient localization routing for mobile wireless sensor network

Tumula,

Rama Devi,

Ramadevi

et al. 2024

Int J Communication

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“…However, power management in WSNs poses a significant challenge when the WSN must operate continuously for sustained periods without a consistent power source. In such contexts, the nodes have specific limitations regarding their memory, processing capacity, radio communication range, and energy supply [5]. One type of node uses batteries that cannot be replaced or recharged under harsh environmental conditions [6].…”

Section: Introductionmentioning

confidence: 99%

Q-Learning and Efficient Low-Quantity Charge Method for Nodes to Extend the Lifetime of Wireless Sensor Networks

Xu,

Li,

Cui

et al. 2023

Electronics

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With the rapid development of the Internet of Things (IoT), improving the lifetime of nodes and networks has become increasingly important. Most existing medium access control protocols are based on scheduling the standby and active periods of nodes and do not consider the alarm state. This paper proposes a Q-learning and efficient low-quantity charge (QL-ELQC) method for the smoke alarm unit of a power system to reduce the average current and to improve the lifetime of the wireless sensor network (WSN) nodes. Quantity charge models were set up, and the QL-ELQC method is based on the duty cycle of the standby and active times for the nodes and considers the relationship between the sensor data condition and the RF module that can be activated and deactivated only at a certain time. The QL-ELQC method effectively overcomes the continuous state–action space limitation of Q-learning using the state classification method. The simulation results reveal that the proposed scheme significantly improves the latency and energy efficiency compared with the existing QL-Load scheme. Moreover, the experimental results are consistent with the theoretical results. The proposed QL-ELQC approach can be applied in various scenarios where batteries cannot be replaced or recharged under harsh environmental conditions.

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“…UAVs help in performing time-sensitive tasks [ 8 , 9 , 10 , 11 ], monitoring emergencies [ 12 ], saving energy of WSN [ 13 , 14 , 15 , 16 , 17 ], extending the lifetime of WSN network [ 14 , 18 ], connecting separate nodes and networks [ 12 , 19 ], and enabling data aggregation [ 17 , 20 ]. Measures such as optimizing the flight routes [ 9 , 12 , 14 , 15 , 16 , 19 ] and locations [ 15 , 19 , 21 ] of UAVs, designing clustering mechanisms [ 17 , 18 , 22 ], media access control mechanisms [ 10 , 18 , 23 , 24 ], and sleeping schedules of WSN [ 14 ] and the like have been adopted to achieve these targets. Assisting in locating the WSN nodes [ 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

WSN-Assisted UAV Trajectory Adjustment for Pesticide Drift Control

Tuan

Yang

et al. 2020

Sensors

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Unmanned Aerial Vehicles (UAVs) have been widely applied for pesticide spraying as they have high efficiency and operational flexibility. However, the pesticide droplet drift caused by wind may decrease the pesticide spraying efficiency and pollute the environment. A precision spraying system based on an airborne meteorological monitoring platform on manned agricultural aircrafts is not adaptable for. So far, there is no better solution for controlling droplet drift outside the target area caused by wind, especially by wind gusts. In this regard, a UAV trajectory adjustment system based on Wireless Sensor Network (WSN) for pesticide drift control was proposed in this research. By collecting data from ground WSN, the UAV utilizes the wind speed and wind direction as inputs to autonomously adjust its trajectory for keeping droplet deposition in the target spraying area. Two optimized algorithms, namely deep reinforcement learning and particle swarm optimization, were applied to generate the newly modified flight route. At the same time, a simplified pesticide droplet drift model that includes wind speed and wind direction as parameters was developed and adopted to simulate and compute the drift distance of pesticide droplets. Moreover, an LSTM-based wind speed prediction model and a RNN-based wind direction prediction model were established, so as to address the problem of missing the latest wind data caused by communication latency or a lack of connection with the ground nodes. Finally, experiments were carried out to test the communication latency between UAV and ground WSN, and to evaluate the proposed scheme with embedded Raspberry Pi boards in UAV for feasibility verification. Results show that the WSN-assisted UAV trajectory adjustment system is capable of providing a better performance of on-target droplet deposition for real time pesticide spraying with UAV.

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Prolong network lifetime and improve efficiency in WSN‐UAV systems using new clustering parameters and CSMA modification

Cited by 9 publications

References 29 publications

An enhanced bio‐inspired energy‐efficient localization routing for mobile wireless sensor network

An enhanced bio‐inspired energy‐efficient localization routing for mobile wireless sensor network

Q-Learning and Efficient Low-Quantity Charge Method for Nodes to Extend the Lifetime of Wireless Sensor Networks

WSN-Assisted UAV Trajectory Adjustment for Pesticide Drift Control

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