Domain
Wireless Sensor Networks (WSNs), UAV Networks, Wireless Communications, Network Routing, Surveillance Systems, 5G IoT
In this work uses innovative multi-channel load-sensing techniques to deploy unmanned aerial vehicles (UAVs) for surveillance.The research aims to improve the quality of data transmission methods and improve the efficiency and reliability of surveillance systems by exploiting the mobility and adaptability of UAVs does the proposed protocol intelligently distribute network traffic across multiple channels, considering the load of each channel, While addressing challenges such as load balancing, this study investigates the effectiveness of the protocol by simulations or practical tests on The expected results have improved UAV-based surveillance systems, more flexible and efficient networks for applications such as security, emergency response and the environment alignment of monitoring -Offering infrastructures, which contribute to efficient and reliable monitoring solutions.
The paper presents an Effective Load-Aware Multipath Routing Protocol (ELAMRP) designed to enhance the surveillance capabilities of unmanned aerial vehicles (UAVs). It addresses communication challenges in UAV networks, such as limited bandwidth and dynamic topology, by strategically distributing network traffic across multiple channels based on their load. The study details the implementation of ELAMRP through simulations, demonstrating its superiority over existing protocols in terms of network load balancing, reduced end-to-end delay, packet delivery ratio, and throughput. Key innovations include a unique load estimation metric and efficient path selection algorithms that ensure robust data transmission for various surveillance applications.
This paper employs the following methods:
- Load-Aware Multipath Routing
- Path Loss Calculation
- Signal-to-Noise Ratio Calculation
- Channel Capacity Calculation
The following datasets were used in this research:
- Packet delivery ratio
- End-to-end delay
- Throughput
- Channel capacity
- Improved network load balancing
- Reduced end-to-end delay
- Enhanced packet delivery ratio
- Increased throughput
The authors identified the following limitations:
- Number of GPUs: None specified
- GPU Type: None specified
UAV networks
surveillance
multipath routing
load balancing
energy efficiency
signal-to-noise ratio
channel capacity
path loss