scholarly journals Unmanned Agricultural Tractors in Private Mobile Networks

Network ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 1-20
Author(s):  
Marjo Heikkilä ◽  
Jani Suomalainen ◽  
Ossi Saukko ◽  
Tero Kippola ◽  
Kalle Lähetkangas ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Ad Hoc ◽  
Data Transfer ◽  
Future Research ◽  
Practical Implementation ◽  
Wireless Technologies ◽  
Communications Networks ◽  
Machine Control ◽  
Cost Efficient ◽  
Agricultural Tractors

The need for high-quality communications networks is urgent in data-based farming. A particular challenge is how to achieve reliable, cost-efficient, secure, and broadband last-mile data transfer to enable agricultural machine control. The trialed ad hoc private communications networks built and interconnected with different alternative wireless technologies, including 4G, 5G, satellite and tactical networks, provide interesting practical solutions for connectivity. A remotely controlled tractor is exemplified as a use case of machine control in the demonstrated private communication network. This paper describes the results of a comparative technology analysis and a field trial in a realistic environment. The study includes the practical implementation of video monitoring and the optimization of the control channel for remote-controlled unmanned agricultural tractors. The findings from this study verify and consolidate the requirements for network technologies and for cybersecurity enablers. They highlight insights into the suitability of different wireless technologies for smart farming and tractor scenarios and identify potential paths for future research.

scholarly journals Review and Comparison of Emerging Routing Protocols in Flying Ad Hoc Networks

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 971 ◽  
Author(s):  
Qianqian Sang ◽  
Honghai Wu ◽  
Ling Xing ◽  
Ping Xie
Keyword(s):  
Routing Protocols ◽  
Ad Hoc ◽  
Data Transfer ◽  
Routing Algorithm ◽  
Special Kind ◽  
Research Area ◽  
Future Research ◽  
Quality Of Data ◽  
Key Factor ◽  
Hoc Networks

With the development of Unmanned Air Vehicle (UAV) communication, Flying Ad Hoc Network (FANET) has become a hot research area in recent years, which is widely used in civil and military fields due to its unique advantages. FANET is a special kind of networks which are composed of UAV nodes, and can be used to implement data transfer in certain unique scenarios. To achieve reliable and robust communication among UAVs, a routing algorithm is the key factor and should be designed elaborately. Because of its importance and usefulness, this topic has attracted many researchers, and various routing protocols have also been put forward to improve the quality of data transmission in FANETs. Thus, in this paper, we give a survey on the state-of-the-art of routing protocols proposed in recent years. First, an in-depth research of the routing in FANETs recently has been brought out by absolutely differentiating them based on their routing mechanism. Then, we give a comparative analysis of each protocol based on their characteristics and service quality indicators. Finally, we propose some unsolved problems and future research directions for FANET routing.

scholarly journals Data Traffic Based on Slicing in a 5G Smart Uplink System

Telecom IT ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 44-54
Author(s):  
A. Grebenshchikova ◽  
Elagin V.
Keyword(s):  
Mobile Networks ◽  
Data Transfer ◽  
Relay Node ◽  
Mobile Network ◽  
Video Stream ◽  
Base Station ◽  
Smart Devices ◽  
Future Research ◽  
Data Traffic ◽  
Fifth Generation

The paper considers the data traffic based on slicing in a 5g mobile network uplink system. Slicing is a promising technology for the fifth generation of networks that provides optimal quality of QOS services for each specific user or group of users. Data traffic that is processed by cellular networks increases every year. Therefore, we should consider all set of traffic from VoIP to M2M devices. For example, smart devices in the healthcare system transmit big data that is sensitive to latency, but also a video stream that requires minimal latency in certain cases. The paper focuses on the successful processing of traffic through a relay node, donor microstates, and a base station. All traffic is divided into three levels of QoS segmentation: sensitive, less sensitive, and low-sensitivity, using the AnyLogic simulation program. For fifth-generation 5G networks, achieving minimum latency and maximum data transfer speed within QoS is an important implementation condition. Therefore, in this paper, using simulation modeling, the main and possible results of each segment in the new generation of mobile networks are obtained. The use of a relay node in conjunction with micro-stations can ensure optimal station load and successful data processing. Also, the solutions outlined in this paper will allow you to identify a number of areas for future research to assess possible ways to design new mobile networks, or improve existing ones.

Survey on Risk-Based Decision-Making Models for Trust Management in VANETs

2019 ◽  
pp. 52-73
Author(s):  
Junaid Mohammad Qurashi
Keyword(s):  
Decision Making ◽  
Ad Hoc Networks ◽  
Mobile Networks ◽  
Intelligent Transportation Systems ◽  
Trust Management ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Transportation Systems ◽  
Future Research ◽  
Hoc Networks

Ubiquitous use of wireless technology and ad-hoc networks have paved the way for intelligent transportation systems also known as vehicular ad-hoc networks (VANETs). Several trust-based frameworks have been proposed to counter the challenges posed by such fast mobile networks. However, the dynamic nature of VANETs make it difficult to maintain security and reliability solely based on trust within peers. Decision-making upon collaborative communications is critical to functioning of VANETs in safe, secured, and reliable manner. Decision taken over malicious or wrong information could lead to serious consequences. Hence, risk management within paradigm of trust becomes an important factor to be considered. In this chapter, a survey of the existing works having incorporated risk factor in their trust models has been explored to give an overview of approaches utilized. The parameters chosen in these models are analyzed and categorized based on the approaches modeled. Finally, future research directions will be presented.

Performance Analysis of AODV Protocol in Mobile Ad Hoc Networks

2011 ◽  
Vol 403-408 ◽  
pp. 2415-2419 ◽  
Author(s):  
Yuan Ming Ding ◽  
Chang Hong Sun ◽  
Lin Song ◽  
Wan Qi Kong
Keyword(s):  
Routing Protocol ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Data Transfer ◽  
Simulation Software ◽  
Aodv Protocol ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
Aodv Routing Protocol ◽  
Better Than

Simulation environment of the mobile Ad Hoc network is built by applying NS2 simulation software. The simulation data indicates that AODV routing protocol is better than DSDV in throughput, fairness and stability. In the underwater network environment where the nodes are in Low-Speed movement, the data transfer rate of AODV routing protocol is higher than AOMDV. To a certain extent, AODV is more suitable for application in underwater environments.

scholarly journals Revisiting the CompCars Dataset for Hierarchical Car Classification: New Annotations, Experiments, and Results

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 596
Author(s):  
Marco Buzzelli ◽  
Luca Segantin
Keyword(s):  
Real World ◽  
High Performance ◽  
Ad Hoc ◽  
Future Research ◽  
Levels Of Detail ◽  
Excellent Starting Point ◽  
Starting Point ◽  
Hierarchical Nature ◽  
Multiple Levels ◽  
Entire Dataset

We address the task of classifying car images at multiple levels of detail, ranging from the top-level car type, down to the specific car make, model, and year. We analyze existing datasets for car classification, and identify the CompCars as an excellent starting point for our task. We show that convolutional neural networks achieve an accuracy above 90% on the finest-level classification task. This high performance, however, is scarcely representative of real-world situations, as it is evaluated on a biased training/test split. In this work, we revisit the CompCars dataset by first defining a new training/test split, which better represents real-world scenarios by setting a more realistic baseline at 61% accuracy on the new test set. We also propagate the existing (but limited) type-level annotation to the entire dataset, and we finally provide a car-tight bounding box for each image, automatically defined through an ad hoc car detector. To evaluate this revisited dataset, we design and implement three different approaches to car classification, two of which exploit the hierarchical nature of car annotations. Our experiments show that higher-level classification in terms of car type positively impacts classification at a finer grain, now reaching 70% accuracy. The achieved performance constitutes a baseline benchmark for future research, and our enriched set of annotations is made available for public download.

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