Employing Unmanned Aerial Vehicles for Improving Handoff Using Cooperative Game Theory

Goudarzi, Shidrokh; Anisi, Mohammad Hossein; Ciuonzo, Domenico; Soleymani, Seyed Ahmad; Pescapè, Antonio

doi:10.1109/taes.2020.3021106

Cited by 18 publications

(11 citation statements)

References 49 publications

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“…The simulation results also demonstrate that the algorithm can reduce the ping-pong effect in certain cases. Dong et al [15] proposed a scheme that dynamically adjusts the HO trigger parameters (handover) to reduce the number of unnecessary transfers. The scheme specifically considers the UAV sailing at a certain altitude and taking off.…”

Section: Related Workmentioning

confidence: 99%

Unmanned aerial vehicle with handover management fuzzy system for 5G networks: challenges and perspectives

Ayass¹,

Coqueiro²,

Carvalho³

et al. 2022

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The next generation of wireless networks, 5G, and beyond will bring more complexities and configuration issues to set the new wireless networks, besides requirements for important and new services. These new generations of wireless networks, to be implemented, are in extreme dependence on the adoption of artificial intelligence techniques. The integration of unmanned aerial vehicles (UAV) in wireless communication networks has opened several possibilities with increased flexibility and performance. Besides, they are considered as one of the most promising technologies to be used in the new wireless networks. Thus, UAVs are expected to be one of the most important applications to provide a new way of connectivity to the 5G network, and it is expected to grow from being a 19.3 billion USD industry in 2019 to 45.8 billion USD by 2025. In this paper, we provide a proposal of handover management on aerial 5G network utilizing the fuzzy system. The simulations performed prove the benefits of our proposal by QoS/QoE (quality of service/quality of experience) metrics.

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Section: Related Workmentioning

confidence: 99%

Unmanned aerial vehicle with handover management fuzzy system for 5G networks: challenges and perspectives

Ayass¹,

Coqueiro²,

Carvalho³

et al. 2022

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“…The performance of any application can be valued by validating the chief metrics like throughput, execution time, and handover delay. To identify the effectiveness of the presented research work, the presented model was compared with other existing models like DDPOS [21], BSD2C-IoD [22], BACS-IoD [28], and SDN-MIH [29]. The comparison result is shown in Table V.…”

Section: Comparative Analysismentioning

confidence: 99%

A Secure Unmanned Aerial Vehicle Service for Medical System to Improve Smart City Facilities

Doraswamy¹,

Krishna²,

Giriprasad³

2022

IJACSA

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The use of drone technology and drones are currently widespread due to their increasing applications. However, there are some specific security-based challenges in the authentication process. In most drone-based applications, there are many authentication approaches, which are subject to handover delay issues with security complexities for an attack. To end these issues, the presented research has focused on developing a novel Optimized deep learning model known as Fruit Fly based UNet Drone Assisted Security (FFUDAS) to remove the malicious attacks. Moreover, the user requests are stored in the cloud, and the stored data are trained to the drones. Hereafter, the drones can deliver medicine to the requestor's location; in that, the malicious attacks were changes the location of drones. Once the attack is identified, then the attack removal process is done. Finally, the new path location to the requested user was identified with the help of fruit fly fitness; then the medicines are delivered to the requested user's location. Furthermore, the designed procedure is executed in an NS2 platform with required nodes. The robustness of the presented model was verified by evaluating the metrics like confidential data rate, execution time, handover delay, pack perception and data delivery rate, and energy consumption. Furthermore, to identify the effectiveness of the presented work, the presented model is compared with other existing schemes. The comparison results show that the presented model has higher throughput, less execution time and handover delay.

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“…These approaches assist in improving handoff efficiency, without compromising on QoS performance due to their low complexity. These approaches are further extended in [6] wherein cooperative game theory is proposed. This strategy can be applied to application specific networks, and is not scalable.…”

Section: Duementioning

confidence: 99%

NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs

2022

IJIES

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Seamless connectivity is need-of-the-hour for high-speed wireless networks. With the advent of 5th Generation (5G) wireless devices, users from different networks require inter-network connectivity with minimum packet drops, and maximum bit-rate. In order to perform this task, high efficiency handover models are proposed, which evaluate various network-level parameters including trust-levels, capacity, Quality of Service (QoS), etc. These algorithms also evaluate various node level metrics which include end-to-end delay, Received Signal Strength Indicator (RSSI), movement patterns, etc. in order to map the nodes to relevant networks. The drawback of proposed approaches is their inability to cater high-speed environments without causing QoS degradation. Moreover, most of these models do not consider node-level augmentations, which restricts their performance when applied to real-world scenarios. In order to remove these drawbacks and make the algorithms perform well with high speed environments without QoS degradation, we propose the design of a novel Connectivity as a Service (CaaS) model that uses Node-Level Augmentation & Dynamic Sleep Scheduling (NLADSS) for high efficiency heterogeneous wireless network handoffs. It was observed that the proposed algorithm is able to achieve a handoff efficiency of 98% for 5G heterogeneous networks, which outperforms most of the recently proposed models. The proposed model also aims at providing immutability, traceability, and high-performance distributed computing, while not compromising on QoS performance of the network.

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Employing Unmanned Aerial Vehicles for Improving Handoff Using Cooperative Game Theory

Cited by 18 publications

References 49 publications

Unmanned aerial vehicle with handover management fuzzy system for 5G networks: challenges and perspectives

Unmanned aerial vehicle with handover management fuzzy system for 5G networks: challenges and perspectives

A Secure Unmanned Aerial Vehicle Service for Medical System to Improve Smart City Facilities

NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs

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