UAV aided intelligent routing for ad-hoc wireless network in single-area theater

Gu, Daniel Lihui; Pei, Guangyu; Ly, H.; Gerla, Mário; Zhang, B.; Hong, Xiaobin

doi:10.1109/wcnc.2000.904805

Cited by 64 publications

(31 citation statements)

References 8 publications

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“…There are many routing protocols used in wireless and adhoc networks [7,8], such as flooding, dynamic source routing, and pre-computed routing. But due to the characteristics of UAVs like speed and rapid changes in links between nodes, these protocols need to be modified and the others will be established to adopt this network issues.…”

Section: Routing Protocols Used In Fanetsmentioning

confidence: 99%

Flying Ad-Hoc Networks: Routing Protocols, Mobility Models, Issues

Yassein¹,

Damer²

2016

ijacsa

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Section: Routing Protocols Used In Fanetsmentioning

confidence: 99%

Flying Ad-Hoc Networks: Routing Protocols, Mobility Models, Issues

Yassein¹,

Damer²

2016

ijacsa

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“…In fact, as clearly seen from (4) and (7), whenever the number of tasks in a coalition increases, the total delay increases, hence reducing the utility from forming a coalition. Further, in a coalition where the number of tasks is large, the condition of stability for the polling system, as given by (5), can be easily violated due to heavy traffic incoming from a large number of tasks, thus, yielding a zero utility as per (7). Hence, forming coalitions between the tasks and the UAVs entails a cost that can limit the size of a coalition.…”

Section: A Initial Coalitional Game Formulationmentioning

confidence: 99%

“…The only information required is the location of the tasks, which can be broadcasted by the central command center at the beginning of all time. Further, note that, for determining whether a UAV acts as a collector or relay within any coalition, the players can easily compute the configuration that maximizes the utility in (7). As the number of UAVs is generally small, this computation is straight forward, and has low complexity.…”

Section: Hedonic Coalition Formation Algorithmmentioning

confidence: 99%

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A selfish approach to coalition formation among unmanned air vehicles in wireless networks

Saad

Han

Başar

et al. 2009

2009 International Conference on Game Theory for Networks

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Abstract-Autonomous agents such as unmanned aerial vehicles (UAVs) have a great potential for deployment in next generation wireless networks. While current literature has been mainly focused on the use of UAVs for connectivity enhancement and routing in military ad hoc networks, this paper proposes a novel usage model for UAVs in wireless communication networks. In the proposed model, a number of UAVs are required to collect data from a number of randomly located tasks and transmit this data wirelessly to a common receiver (such as the central command). Each task represents a queue of packets that require collection and transmission to the central receiver. The problem is modeled as a hedonic coalition formation game between the UAVs and the tasks that interact in order to form disjoint coalitions. Each formed coalition is modeled as a polling system consisting of a number of UAVs, designated as collectors, which act as a single server that moves between the different tasks present in the coalition, collects and transmits the packets to a common receiver. Within each coalition, some UAVs can also take the role as a relay for improving the packet success rate of the transmission. The proposed coalition formation algorithm allows the tasks and the UAVs to take local selfish decisions to join or leave a coalition, based on the achieved benefit, in terms of effective throughput, and the cost in terms of delay. Simulation results show how the proposed algorithm allows the UAVs and tasks to self-organize into independent coalitions, while improving the performance, in terms of average player (UAV or task) payoff, of at least 61.96% relatively to a scheme that allocates nearby tasks equally among UAVs.

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“…As indicated before, the common routing method of increasing scalability is the use of hierarchical/clustered protocols such as the Hierarchical State Routing (HSR) protocol [4] or the Intelligent Hierarchical State Routing protocol (IHSR) [5]. These protocols divide the nodes in the spatial network into backbone nodes and regular nodes arranged in clusters.…”

mentioning

confidence: 99%

Scalability Issues in Ad-Hoc Networks: Metrical Routing Versus Table-Driven Routing

Ben-Asher

Feldman

et al. 2008

Wireless Pers Commun

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When studying scalability in ad-hoc networks, most works present experimental results for a limited number of nodes (100-200). Various "explicit" clustering techniques have been proposed to improve scalability, obtaining successful sessions for 400-800 nodes. However, explicit clustering may damage the performance, e.g., cause session breaks due to fast movements of cluster heads. An alternative to explicit clustering is the use of algorithms that are "naturally clustered", i.e., arrange the nodes in dynamic hierarchical structures. In this work, we study the effect of explicit clustering by comparing an advanced version of the Ad Hoc Distance Vector Algorithm (AODV) with the Metrical Routing Algorithm (MRA) that possesses the natural clustering property. We cover fundamental aspects of scalability and experimentally prove the superiority of implicit clustering over explicit clustering. In particular, we consider heterogeneous theaters with several types of transmitters including personal, car-mounted, helicopters and a Geostationary (GEO) satellite. Natural clustering is more effective in heterogeneous theaters as the more powerful transmitters can serve as cluster heads. A formal bound based on general probabilistic assumptions shows that all existing ad-hoc algorithms cannot scale infinitely, thus rendering scalability as an experimental issue.

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UAV aided intelligent routing for ad-hoc wireless network in single-area theater

Abstract: Abstract

Cited by 64 publications

References 8 publications

Flying Ad-Hoc Networks: Routing Protocols, Mobility Models, Issues

Flying Ad-Hoc Networks: Routing Protocols, Mobility Models, Issues

A selfish approach to coalition formation among unmanned air vehicles in wireless networks

Scalability Issues in Ad-Hoc Networks: Metrical Routing Versus Table-Driven Routing

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