A bidirectional congestion control transport protocol for the internet of drones

Sharma, Bhisham; Srivastava, Gautam; Lin, Jerry Chun‐Wei

doi:10.1016/j.comcom.2020.01.072

Cited by 33 publications

(18 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e network lifetime was not reduced by congestion control algorithm. A reliable and congestion based protocol was introduced in [12] for enhancing the reliability results. e designed protocol used Order Preference by Similarity to Ideal Solution (TOPSIS) technique to choose an optimal path for data transmission.…”

Section: Related Workmentioning

confidence: 99%

A Machine Learning-Based Intelligence Approach for Multiple-Input/Multiple-Output Routing in Wireless Sensor Networks

Sridhar¹,

Rao²,

Kumar

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Computational intelligence methods play an important role for supporting smart networks operations, optimization, and management. In wireless sensor networks (WSNs), increasing the number of nodes has a need for transferring large volume of data to remote nodes without any loss. These large amounts of data transmission might lead to exceeding the capacity of WSNs, which results in congestion, latency, and packet loss. Congestion in WSNs not only results in information loss but also burns a significant amount of energy. To tackle this issue, a practical computational intelligence approach for optimizing data transmission while decreasing latency is necessary. In this article, a Softmax-Regressed-Tanimoto-Reweight-Boost-Classification- (SRTRBC-) based machine learning technique is proposed for effective routing in WSNs. It can route packets around busy locations by selecting nodes with higher energy and lower load. The proposed SRTRBC technique is composed of two steps: route path construction and congestion-aware MIMO routing. Prior to constructing the route path, the residual energy of the node is determined. After that, the residual energy level is analyzed using softmax regression to determine whether or not the node is energy efficient. The energy-efficient nodes are located, and numerous paths between the source and sink nodes are established using route request and route reply. Following that, the SRTRBC technique is used for congestion-aware routing based on buffer space and bandwidth capability. The path that requires the least buffer space and has the highest bandwidth capacity is picked as the optimal route path among multiple paths. Finally, congestion-aware data transmission is used to minimize latency and data loss along the route path. The simulation considers a variety of performance metrics, including energy consumption, data delivery rate, data loss rate, throughput, and delay, in relation to the amount of data packets and sensor nodes.

show abstract

Section: Related Workmentioning

confidence: 99%

A Machine Learning-Based Intelligence Approach for Multiple-Input/Multiple-Output Routing in Wireless Sensor Networks

Sridhar¹,

Rao²,

Kumar

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…Sharma et al [ 68 ] suggested a protocol that depends on congestion, which offers both symmetric reliability and congestion control based on rate adjustment. The protocol aims to minimize packet drops, maintain fairness, and boost energy quality.…”

Section: Recent Advancementsmentioning

confidence: 99%

The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends

Abdelmaboud

2021

Sensors

View full text Add to dashboard Cite

The use of unmanned aerial vehicles or drones are a valuable technique in coping with issues related to life in the general public’s daily routines. Given the growing number of drones in low-altitude airspace, linking drones to form the Internet of drones (IoD) is a highly desirable trend to improve the safety as well as the quality of flight. However, there remain security, privacy, and communication issues related to IoD. In this paper, we discuss the key requirements of security, privacy, and communication and we present a taxonomy of IoD based on the most relevant considerations. Furthermore, we present the most commonly used commercial case studies and address the latest advancements and solutions proposed for the IoD environments. Lastly, we discuss the challenges and future research directions of IoD.

show abstract

“…However, this method considers neither the energy as a factor nor detection the congestion during data collection. Sharma et al discuss a bidirectional congestion control transport protocol for the internet of drones 23 . This method uses optimal path technique for order preference by similarity to ideal solution (TOPSIS) method for efficient data transmission.…”

Section: Literature Reviewmentioning

confidence: 99%

A proficient data gathering technique for unmanned aerial vehicle‐enabled heterogeneous wireless sensor networks

Singh

Malik

Kumar

et al. 2021

Int J Communication

View full text Add to dashboard Cite

SummaryUnmanned aerial vehicle (UAV)‐enabled wireless sensor networks (WSNs) have evolved as the significant paradigms to communicate the information among the devices in today's scenario instantly. These technologies support for developing smart crop spraying, smart infrastructure, aerial photography and videography, emergency services, etc. in providing smart solutions. Therefore, there is a dire need to develop an energy‐efficient solution for data gathering through UAVs. In this paper, an optimum weighted probability function is proposed by considering residual node energy, node spacing, and average energy of networks. This function helps in optimizing the clustering process for three‐tier heterogeneity by minimizing the energy of the proposed network. The proposed methods achieve 29.45% and 52.48% increment in the network lifespan as compared to the existing algorithm. The reason for such a gigantic enhancement in the network lifespan is the selection of the highest capable node as a cluster head using the proposed function.

show abstract

A bidirectional congestion control transport protocol for the internet of drones

Cited by 33 publications

References 35 publications

A Machine Learning-Based Intelligence Approach for Multiple-Input/Multiple-Output Routing in Wireless Sensor Networks

A Machine Learning-Based Intelligence Approach for Multiple-Input/Multiple-Output Routing in Wireless Sensor Networks

The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends

A proficient data gathering technique for unmanned aerial vehicle‐enabled heterogeneous wireless sensor networks

Contact Info

Product

Resources

About