A geographic mobility prediction routing protocol for Ad Hoc UAV Network

Lin, Lin; Sun, Qibo; Wang, Shangguang; Yang, Fangchun

doi:10.1109/glocomw.2012.6477824

Cited by 70 publications

(44 citation statements)

References 8 publications

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“…Several evaluation metrics are calculated, such as the ratio of energy remaining capacity ( R erc ), the packet delivery ratio ( PDR ), the end‐to‐end delay ( EED ), the overhead ( OH ), and the Pathstability under different speeds and densities. UVAR‐S, MPGR, LEPR, CBLADSR, and the proposed ECaD are all evaluated and compared. Ten pairs of UAVs are randomly selected to communicate with each other.…”

Section: Performance Evaluationmentioning

confidence: 99%

ECaD: Energy‐efficient routing in flying ad hoc networks

Oubbati

Mozaffari

Chaib

et al. 2019

Int J Communication

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Summary Much progress can be expected in the domain of unmanned aerial vehicle (UAV) communication by the next decade. The cooperation between multiple UAVs in the air exchanging data among themselves can naturally form a flying ad hoc network (FANET). Such networks can be the key support to accomplish several kinds of missions while providing the required assistance to terrestrial networks. However, they are confronted with many challenges and difficulties, which are due to the high mobility of UAVs, the frequent packet losses, and the weak links between UAVs, all affecting the reliability of the data delivery. Furthermore, the unbalanced energy consumption may result in earlier UAV failure and consequently accelerate the decrease of the network lifetime, thus disrupting the overall network. This paper supports the use of the movement information and the residual energy level of each UAV to guarantee a high level of communication stability while predicting a sudden link breakage prior to its occurrence. A robust route discovery process is used to explore routing paths where the balanced energy consumption, the link breakage prediction, and the connectivity degree of the discovered paths are all considered. The performance of the scheme is evaluated through a series of simulations. The outcomes demonstrate the benefits of the proposed scheme in terms of increasing the lifetime of the network, minimizing the number of path failures, and decreasing the packet losses.

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Section: Performance Evaluationmentioning

confidence: 99%

ECaD: Energy‐efficient routing in flying ad hoc networks

Oubbati

Mozaffari

Chaib

et al. 2019

Int J Communication

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“…MPRP (Mobility Prediction Routing Protocol) [12] predicts link status in the data transmitting phase, and encapsulates location information in data packets. In data transmitting phase, the intermediate can learn the location information from the node, which forwards data packet to it.…”

Section: Mobility Prediction Based Protocolmentioning

confidence: 99%

“…Literature [11][12] proposed many methods to talk about how to use mobility prediction mechanism in the reactive protocol. But most of the mechanisms are to find the most stable path as the best path within the known path.…”

Section: Mobility Prediction Based Protocolmentioning

confidence: 99%

On-demand and Greedy Forwarding Based Routing Protocol for Mobile Ad Hoc Networks

Huang¹,

Fan²,

Xiang³

et al. 2017

Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 201

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Abstract. The dynamic topology of a mobile ad hoc network poses a real challenge in the design of routing protocol, especially in high-dynamic environments. In this paper, we proposed a new routing protocol which based on on-demand and greedy forwarding. This protocol proposed three opinions to RGR, i.e., through scoped flooding to decrease control overhead in route discovery phase, through mobility prediction to monitor the condition of reactive path and help nodes to choose the proper next-hop in GGF phase, and through delayed route requests to reduce unnecessary waste of network resources. Compared to RGR, AODV, Modified-RGR and Optimized-RGR, simulation results show that the improved RGR not only have high packet receive ratio, but have low average normalized routing overhead and average end-to-end delay.

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“…We can cite as an example "Face Routing" used by GFG [23], a mechanism which consists in creating a planar graph of the network connections, then using the right hand rule [24] to reach the destination. Several geographical routing protocols have been proposed: GPSR [25], GPMOR [26], USMP [27] or MPGR [28].…”

Section: Routing Protocols For Uaanetsmentioning

confidence: 99%

Emulation-Based Performance Evaluation of Routing Protocols for Uaanets

Maxa¹,

Roudière²,

Larrieu³

2015

Lecture Notes in Computer Science

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Abstract. UAV Ad hoc NETwork (UAANET) is a subset of the wellknown Mobile Ad-hoc NETworks (MANETs). It consists of forming an ad hoc network with multiple small Unmanned Aerial Vehicles (UAVs) and the Ground Control Station (GCS). Similar to MANETs, the UAANET communication architecture is infrastructure-less and self-configuring network of several nodes forwarding data packets. However, it also has some specific features that brings challenges on network connectivity. Consequently, an adapted routing protocol is needed to exchange data packets within UAANETs. In this paper, we introduce a new hybrid experimental system that can evaluate different types of adhoc routing protocols under a realistic UAANET scenario. It is based on virtual machines and the Virtualmesh [1] framework to emulate physical aspects. We evaluated AODV, DSR and OLSR efficiency in a realistic scenario with three UAVs scanning an area. Our results show that AODV outperformed OLSR and DSR.

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A geographic mobility prediction routing protocol for Ad Hoc UAV Network

Cited by 70 publications

References 8 publications

ECaD: Energy‐efficient routing in flying ad hoc networks

ECaD: Energy‐efficient routing in flying ad hoc networks

On-demand and Greedy Forwarding Based Routing Protocol for Mobile Ad Hoc Networks

Emulation-Based Performance Evaluation of Routing Protocols for Uaanets

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