RDTP: reliable data transport protocol in wireless sensor networks

Barati, Ali; Movaghar, Ali; Sabaei, Masoud

doi:10.1007/s11235-015-0098-2

Cited by 15 publications

(4 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Related to this topic, the reliable data transmission in the context of wireless sensor networks (WSNs) has been address by several authors. In Reference 17, RDTP, a reliable data transport protocol for WSNs is introduced. In Reference 18, the authors propose a secure hybrid structure data aggregation method in WSNs.…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid error correction in fragmented IoT media streams

Herrero

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Wireless personal area networks (WPANs), as most IoT networking technologies, rely on constrained low power devices that support a trade‐off between signal coverage and transmission rates. WPANs are characterized for medium to low transmission rates over low distances. The transmission rates, however, are high enough to support maximum transmission unit (MTU) sizes that are large enough to enable the transmission of IPv6 datagrams. One such WPAN technologies is associated with the IEEE 802.15.4 physical layer. Because IEEE 802.15.4 does not natively support IP encapsulation, an adaptation mechanism known as IPv6 over low‐power wireless personal area networks (6LoWPAN) is used to this end. For large datagrams like those generated when transmitting speech frames, 6LoWPAN fragments them in order to comply with the 127‐byte IEEE 802.15.4 MTU size. Fragmentation, however, aggravates the effects of network packet loss. This article explores this problem and attempts to find a mechanism that overcomes these limitations. Specifically, it introduces a hybrid error correction algorithm that dynamically adjusts the number of fragments that are transmitted in order to balance application layer loss and transmission rate.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Hybrid error correction in fragmented IoT media streams

Herrero

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…The major challenge in WSNs environment is the smaller battery power capacity of the nodes [ 17 ]. Some important research contributions in ad-hoc and sensor networks include improving fault tolerance [ 18 ], detection of faulty nodes in WSNs [ 19 , 20 ], reliable data transfer protocol for WSNs [ 21 ] and routing approach in IoT [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Impact of Active Attack on the Performance of the AMCTD Protocol in Underwater Wireless Sensor Networks

Saeed

Khalil

Al-Shamayleh

et al. 2023

Sensors

View full text Add to dashboard Cite

The exponentially growing concern of cyber-attacks on extremely dense underwater sensor networks (UWSNs) and the evolution of UWSNs digital threat landscape has brought novel research challenges and issues. Primarily, varied protocol evaluation under advanced persistent threats is now becoming indispensable yet very challenging. This research implements an active attack in the Adaptive Mobility of Courier Nodes in Threshold-optimized Depth-based Routing (AMCTD) protocol. A variety of attacker nodes were employed in diverse scenarios to thoroughly assess the performance of AMCTD protocol. The protocol was exhaustively evaluated both with and without active attacks with benchmark evaluation metrics such as end-to-end delay, throughput, transmission loss, number of active nodes and energy tax. The preliminary research findings show that active attack drastically lowers the AMCTD protocol’s performance (i.e., active attack reduces the number of active nodes by up to 10%, reduces throughput by up to 6%, increases transmission loss by 7%, raises energy tax by 25%, and increases end-to-end delay by 20%).

show abstract

“…The underwater wireless sensor network (UWSN) is a system comprised of dozens of autonomous sensor nodes deployed in an underwater environment for various purposes. These nodes are composed of sensors, a processing unit, a communication unit, and a power unit that receive data from the environment and transmit it to the sink node via nearest neighbors and cluster heads nodes 7 . A sensor node is a limited‐resource device with limited memory, energy, computing power, and transmission range.…”

Section: Introductionmentioning

confidence: 99%

“…These nodes are composed of sensors, a processing unit, a communication unit, and a power unit that receive data from the environment and transmit it to the sink node via nearest neighbors and cluster heads nodes. 7 A sensor node is a limited-resource device with limited memory, energy, computing power, and transmission range. UWSNs are widely utilized in military defiance systems, coastal monitoring and security, resource exploration, maritime infrastructure inspection, and aided navigation, among other applications.…”

Section: Introductionmentioning

confidence: 99%

An improved underwater wireless sensor network communication using Internet of Things and signal to noise ratio analysis

Kapileswar

Polasi

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Underwater acoustic (UWA) channels are widely regarded as one of the most challenging communication mediums. Low frequencies are best for acoustic propagation, and the bandwidth available for communication is extremely small. The worst channel situation often limits the efficiency of UWA communication systems due to the difficulty and time‐varying nature of the UWA channel. To solve the existing limitations related with underwater signal transmission and communication, an improved underwater communication system incorporated with Internet of Things (IoT) is proposed in this work. The proposed system utilizes the orthogonal signal division multiplexing modulation technique. Here the signal transmission process is achieved with the help of an IoT network system. An improved AdaBoost channel estimation algorithm is used to obtain the channel information. This work utilizes an improved stochastic gradient descent optimization method for selecting the suitable mode of signal transmission based on the estimated channel. Further, an adaptive recursive least square channel equalization algorithm is used for channel compensation. The simulation results are obtained with the help of the MATLAB platform. The performance is analyzed in terms of parameters such as signal to noise ratio, bit error rate, and mean square error. A comparison of the proposed method is also made with the existing methods. The evaluation results show that the proposed method performs better than the existing methods.

show abstract

RDTP: reliable data transport protocol in wireless sensor networks

Cited by 15 publications

References 36 publications

Hybrid error correction in fragmented IoT media streams

Hybrid error correction in fragmented IoT media streams

Analyzing the Impact of Active Attack on the Performance of the AMCTD Protocol in Underwater Wireless Sensor Networks

An improved underwater wireless sensor network communication using Internet of Things and signal to noise ratio analysis

Contact Info

Product

Resources

About