Adaptability of Various Mobility Models for Flying AdHoc Networks—A Review

Singh, Kuldeep; Verma, Anil Kumar

doi:10.1007/978-981-10-4585-1_5

Cited by 5 publications

(8 citation statements)

References 24 publications

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“…This relation could be determined based on a probabilistic equation. Typically, the mobility models in which the nodes move in groups, could be placed in this class [20]. A number of important models, which are placed in this category are pursue [81], Reference Point Group [82], Nomadic Community [81], and column [81].…”

Section: Mobility Modelsmentioning

confidence: 99%

“…Furthermore, a group of studies try to specifically focus on the topic of mobility itself and either survey a number of models or even try to propose novel models to be adopted by their intended applications. Accordingly, there has been a research on studying mobility models in Flying Ad-hoc Networks (FANET) [20]. In a relative study, the authors in [24] have claimed that due to lack of a comprehensive taxonomy for mobility models in the literature, they have came up with a survey study on a number of mobility models to pave the way for researchers to propose their new models with more ease and transparency.…”

Section: A Related Studiesmentioning

confidence: 99%

“…The authors in [228] have employed this model to propose their approach in multimedia delivery systems in emergency response operations. The authors in [20] have indicated that this mobility model is one of the best candidates for being adopted by the FANETs. It is believed that the employed policies in the routing protocols could severely impact the operations made in the disaster area [229].…”

Section: ) Disaster Area Mobility Model (Dam) [80]mentioning

confidence: 99%

“…Meanwhile, to be able to justify and compare the observed results, it is essential to deeply understand the structure of the nodes movement in different mobility models. Accordingly, while there have been a number of efforts on giving a survey on a number of mobility models [20]- [25], not only neither of them has evaluated those models in the presence of RPL, but to the best of our knowledge, none of them has conducted any sorts of experimental studies as part of their survey to provide a deeper insight into the impact of different mobility models on the performance of the network in RPL-based IoT applications.…”

Section: Introductionmentioning

confidence: 99%

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Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

et al. 2020

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With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications.

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Section: Mobility Modelsmentioning

confidence: 99%

Section: A Related Studiesmentioning

confidence: 99%

Section: ) Disaster Area Mobility Model (Dam) [80]mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

et al. 2020

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“…4 Manhattan grid allows a node to move in straight x-axis and y-axis directions in a grid road layout in urban areas. Specifically, the node moves in different directions (i.e., either straight, left, or right, rather than backward) to proceed or to turn to the left or right road at an intersection [92].…”

Section: A1mentioning

confidence: 99%

Routing Schemes in FANETs: A Survey

Khan

Yau

Noor

et al. 2019

Sensors

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Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues.

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Reinforcement-Based Clustering in Flying Ad-Hoc Networks for Serving Vertical and Horizontal Routing

Abdulhae,

Mandeep,

Islam

et al. 2023

IEEE Access

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Unmanned aerial vehicles (UAVs) are receiving increasing attention due to their wide range of applications. Flying ad-hoc networks (FANETs) enable inter-communication between UAVs, but their dynamics and fast changes in mobility and topology make it challenging to achieve stable routing. Clustering based FANETs provide a self-organizing approach for routing, but clustering is a decentralized process based on different utilities that can affect performance. In this work, we propose a centralized agent placed in a remote ground station to adjust the role of each utility in the cluster-head arbitration. Our approach uses six utilities, including node centrality, residual energy, link holding time, velocity similarity, buffer occupancy, and diversity. The developed reinforcement learning (RL)-clustering approach enables routing over multiple planes, with each plane representing a network cell with a different coverage radius of nodes, including Femto, Pico, and Micro planes. We propose a novel reward formulation for effective learning of agents that includes indicators of stability based on role change, energy consumption, and confirmation message through the selected node. For evaluation, the developed RL based agent was evaluated on three types of agents, namely, Q-learning, DQN, and DDPG and it was compared with random agent. Results have shown the superiority of our developed RL based clustering in terms of stability, energy consumption and most network metrics.

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Adaptability of Various Mobility Models for Flying AdHoc Networks—A Review

Cited by 5 publications

References 24 publications

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

Routing Schemes in FANETs: A Survey

Reinforcement-Based Clustering in Flying Ad-Hoc Networks for Serving Vertical and Horizontal Routing

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