Maximizing the underwater wireless sensor networks’ lifespan using BTC and MNP5 compression techniques

Jawad, Ghufran Ali M.; Al-Qurabat, Ali Kadhum M.; Idrees, Ali Kadhum

doi:10.1007/s12243-021-00903-6

Cited by 8 publications

(3 citation statements)

References 37 publications

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“…An international standard known as IEEE 802.11 describes the characteristics of a wireless local area network (WLAN). Originally, WiFi stands for Wireless Fidelity, and the WiFi Alliance has awarded a certification with that same name (formerly WECA, or Wireless Ethernet Compatibility Alliance), the group in charge of ensuring that devices that are 802.11 compliant can communicate with one another [37], [49].…”

Section: A Wi-fi Based Localization Systemmentioning

confidence: 99%

Exploring Radio Frequency-Based UAV Localization Techniques: A Comprehensive Review

Abdulhussein Abdulzahra,

Kadhum M. Al-Qurabat

2024

IJCDS

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UAVs (unmanned aerial vehicles) and WSNs (wireless sensor networks) are now two well-established technologies for monitoring, target tracking, event detection, and remote sensing. Typically, WSN is made up of thousands or even millions of tiny, battery-operated devices that measure, gather, and send information from their surroundings to a base station or sink. Within the realm of wireless positioning and communication, UAVs have garnered a lot of interest because of their remarkable mobility and simplistic deployment to tackle the problems of imprecise sensor placement, inadequate infrastructure coverage, and the massive quantity of sensing data that WSN collects. A crucial prerequisite for many position-based WSN applications is node location, or localization. The use of UAVs for localization is more preferable than permanent terrestrial anchor nodes due to their high accuracy and minimal implementation complexity. The possible interference or signal block in such an operating environment, however, might cause the Global Positioning System (GPS) to become ineffective or unobtainable. In these conditions, the need for innovative UAV-based sensor node location technologies has become essential. Radio frequency (RF)-based localization techniques are reviewed in the current paper. We examine the available RF features for localization and look into the current approaches that work well for unmanned vehicles. The most recent research on RF-based UAV localization is reviewed, along with potential avenues for future investigation.

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Section: A Wi-fi Based Localization Systemmentioning

confidence: 99%

Exploring Radio Frequency-Based UAV Localization Techniques: A Comprehensive Review

Abdulhussein Abdulzahra,

Kadhum M. Al-Qurabat

2024

IJCDS

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“…In our simulation, we adopt a basic MAC receiving protocol where the receiving units transmit packets simultaneously regardless of channel status, and frames lost due to collisions are not retransmitted. Acoustic detection of underwater MAC might be a logical distinction, given the unusually high propagation lag that synchronous protocols make impossible [14]; Therefore, recognition is often used in the sushisen literature as [11].…”

Section: Fig1: New Sushien Architecture Packet Delivery Implementationmentioning

confidence: 99%

Enchantment of performance spoofing attacks in sushisen algorithm wireless networks

Senthil¹,

SUGANYA²,

Inakshi³

2023

Preprint

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Underwater wireless sensor networks (WSN) can be used for a variety of applications. High propagation delay, limited bandwidth, 3D deployment, and lack of power are some of the challenges faced UWSN. An adversary with low communication depth prevents nearby relay nodes from perforating the path. In this paper, proposed dropped packet ratio (DPR) can effectively prevent depth spoofing attacks by ensuring that an ineligible node is likely to be triggered and removed. After the new node is again sent delivery speeds is increase sensitive to power decrease under conventional conditions. Compared with the related protocol, the proposed new sushisen protocol achieves higher energy, capacity, and scalability.

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“…The previous papers [ 10 , 11 , 14 , 15 , 16 , 17 , 18 , 19 ] on this topic have primarily focused on compression algorithms such as LZW and its variations (e.g., s-LZW) and have often employed hardware with substantial computing power, such as the Raspberry Pi 4B with 8 GB RAM. In contrast, this paper introduces, as the main contribution and novelty of our work, the following new elements: the evaluation of canonical Huffman, Lempel–Ziv 77, Lempel–Ziv 78, and Lempel–Ziv–Welch algorithms in terms of energy and time efficiency for compressing and transmitting text data and the evaluation of the Joint Photographic Experts Group algorithm in terms of energy and time efficiency for compressing and transmitting image data.…”

Section: Related Workmentioning

confidence: 99%

Study of the Impact of Data Compression on the Energy Consumption Required for Data Transmission in a Microcontroller-Based System

Piątkowski,

Puślecki,

Walkowiak

2023

Sensors

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As the number of Internet of Things (IoT) devices continues to rise dramatically each day, the data generated and transmitted by them follow similar trends. Given that a significant portion of these embedded devices operate on battery power, energy conservation becomes a crucial factor in their design. This paper aims to investigate the impact of data compression on the energy consumption required for data transmission. To achieve this goal, we conduct a comprehensive study using various transmission modules in a severely resource-limited microcontroller-based system designed for battery power. Our study evaluates the performance of several compression algorithms, conducting a detailed analysis of computational and memory complexity, along with performance metrics. The primary finding of our study is that by carefully selecting an algorithm for compressing different types of data before transmission, a significant amount of energy can be saved. Moreover, our investigation demonstrates that for a battery-powered embedded device transmitting sensor data based on the STM32F411CE microcontroller, the recommended transmission module is the nRF24L01+ board, as it requires the least amount of energy to transmit one byte of data. This module is most effective when combined with the LZ78 algorithm for optimal energy and time efficiency. In the case of image data, our findings indicate that the use of the JPEG algorithm for compression yields the best results. Overall, our research underscores the importance of selecting appropriate compression algorithms tailored to specific data types, contributing to enhanced energy efficiency in IoT devices.

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Maximizing the underwater wireless sensor networks’ lifespan using BTC and MNP5 compression techniques

Cited by 8 publications

References 37 publications

Exploring Radio Frequency-Based UAV Localization Techniques: A Comprehensive Review

Exploring Radio Frequency-Based UAV Localization Techniques: A Comprehensive Review

Enchantment of performance spoofing attacks in sushisen algorithm wireless networks

Study of the Impact of Data Compression on the Energy Consumption Required for Data Transmission in a Microcontroller-Based System

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