Implementation of 3D Obstacle Compliant Mobility Models for UAV Networks in ns-3

Regis, Paulo Alexandre; Bhunia, Suman; Sengupta, Shamik

doi:10.1145/2915371.2915384

Cited by 18 publications

(7 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Gauss-Markov (GM) mobility model proposed by Regis et al 39 for 2D and 3D ad hoc networks. The GM can efficiently deal with the inherent randomness of the nodes.…”

Section: Mobility Models For Fanetsmentioning

confidence: 99%

A novel unmanned aerial vehicle‐sink enabled mobility model for military operations in sparse flying ad‐hoc network

Agrawal

Kapoor

Tomar

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

The flying ad‐hoc network (FANET) is a self‐configured, rapidly deployable network for a variety of time‐critical applications such as military and disaster relief operations. Most mobility models view FANETs as dense networks leading to unrealistic network scenarios and may not provide real‐world results. Unmanned aerial vehicles (UAVs) may not always be connected due to low battery, malfunction, budget constraints, or the nature of the application. Existing mobility models do not work in realistic FANET scenarios, that is, sparse FANETs, and simulate the model in a two‐dimensional domain. To address the issues, a novel mobility model has been proposed for military operations in sparse FANETs. This is the first paper that addresses the issue of sparse networks as well as implementing the proposed work in the simulator in three‐dimensional space. The proposed UAV‐sink enabled mobility model (US‐MM) increases the network performance without impeding the mobility of UAVs as UAVs perform critical functions in military operations. The simulation has been done using NS‐3.25. The obtained results show the efficiency of our proposed model which achieves increased network connectivity and stability of UAV's connection to the base station in the sparse FANETs.

show abstract

“…The Gauss-Markov (GM) mobility model proposed by Regis et al 39 for 2D and 3D ad hoc networks. The GM can efficiently deal with the inherent randomness of the nodes.…”

Section: Mobility Models For Fanetsmentioning

confidence: 99%

A novel unmanned aerial vehicle‐sink enabled mobility model for military operations in sparse flying ad‐hoc network

Agrawal

Kapoor

Tomar

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…be intelligent enough to avoid collisions. Following previous research into UAVs [20]- [22], we modelled the movement of the UAVs using a Gauss-Markov 3D mobility model. We assumed that the UAVs move with random speeds in a range [ The take-off and landing conditions were not considered, because we believe that they have a minor impact on the network.…”

Section: Performance Evaluationmentioning

confidence: 99%

Adaptive Hello Interval in FANET Routing Protocols for Green UAVs

Mahmud

Cho

2019

IEEE Access

View full text Add to dashboard Cite

With the recent advances in unmanned aerial vehicles (UAVs), the development of energy-efficient networking technology for mission-oriented multiple cooperative UAVs has become crucial. Routing in flying ad-hoc networks (FANETs) with UAVs is a challenging issue because of the high speed and sudden changes in direction of UAVs. Traditional routing protocols in FANETs periodically send hello messages for the establishment and maintenance of the routes. However, sending hello messages periodically after a fixed interval increases bandwidth wastage when the hello interval is excessively short or causes long delays in neighbour discovery when the hello interval is overly long. Moreover, several disconnected UAV groups have been observed in which the group members are connected among themselves but detached from the main network. By exchanging excessive hello messages inside the group, the UAVs maintain an unnecessary neighbourhood, causing wastage of energy. However, FANETs have certain advantages, such as knowledge about mission-related information. To solve the problem of unnecessary energy drain, we propose a novel adaptive hello interval scheme-energy efficient hello (EE-Hello)-based on available mission-related information, such as the volume of the allowed airspace, number of UAVs, UAV transmission range, and UAV speed. We present a method to decide the distance that a UAV needs to travel before sending a hello message. We also specify a technique to determine the number of UAVs necessary to achieve specific network requirements, such as packet delivery ratio or throughput, with the expenditure of minimum energy. We show that the proposed EE-Hello can save about 25% of the energy currently used, by suppressing unnecessary hello messages without degrading the overall network throughput. INDEX TERMS FANETs, UAV networks, green UAV networks, energy efficient routing, adaptive hello interval. I. INTRODUCTION Recently, Unmanned Aerial Vehicles (UAVs) have become very popular because of their wide range of applications for which they can be used [1], [2]. In particular, their capability to work as a group with minimum human intervention has led to a productive area of research. However, energy efficiency is a major concern in today's UAVs [3]. Generally, small UAVs can fly for a maximum of 30 minutes depending upon available energy. Therefore, research has focused on producing energy-efficient green UAVs that can fly for longer. In addition, in a multi-UAV system, UAVs need to maintain communication links between themselves in order to accomplish their mission cooperatively. However, owing to the rapid The associate editor coordinating the review of this manuscript and approving it for publication was Onur Alparslan.

show abstract

“…In these models UAVs depends upon the previous or earlier speed and direction (Guillen-Perez & Cano, 2018). The types of time-dependent mobility models are BSA (Boundless simulation area) mobility model GMM (Gauss-Markov mobility model) (Regis, Bhunia & Sengupta, 2016) and ST (Smooth turn) mobility model.…”

Section: Tdmm (Time-dependent Mobility Models)mentioning

confidence: 99%

A study of mobility models for UAV Communication Networks

Nawaz¹,

Ali²,

Massan³

2019

3C Tecnología

View full text Add to dashboard Cite

The Unmanned aerial vehicle communication network (UAVCN) is a group or swarm of unmanned aerial vehicles which can be used for specific military and civilian applications without human intercession. This network faces the design problem which is based on network mobility. The frequent topology changes affect communication and collaboration among the UAVs (Unmanned aerial vehicles). To govern the movement pattern of UAVCN different mobility models needed to be studied in order to solve this communication issue. In this paper, mobility models are explored which provides the particular mobility pattern to resolve the problem of collaboration, communication and cooperation of UAVs. These models have been categorized into five groups and classified each group in detail. These mobility models provide the platform to understand and implement the unmanned aerial communication network for specific environment scenarios. The mobisim simulator tool is used to generate the mobility model s trajectories for different mobility models.

show abstract

Implementation of 3D Obstacle Compliant Mobility Models for UAV Networks in ns-3

Cited by 18 publications

References 9 publications

A novel unmanned aerial vehicle‐sink enabled mobility model for military operations in sparse flying ad‐hoc network

A novel unmanned aerial vehicle‐sink enabled mobility model for military operations in sparse flying ad‐hoc network

Adaptive Hello Interval in FANET Routing Protocols for Green UAVs

A study of mobility models for UAV Communication Networks

Contact Info

Product

Resources

About