C-ICAMA, a centralized intelligent channel assigned multiple access for multi-layer ad-hoc wireless networks with UAVs

Gu, Daniel Lihui; Ly, H.; Hong, Xiaobin; Gerla, Mário; Pei, Guangyu; Lee, Yeng-Zhong

doi:10.1109/wcnc.2000.903973

Cited by 27 publications

(16 citation statements)

References 6 publications

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“…Using this preference relation, every task can evaluate its preferences over the possible coalitions that the task can form. Consequently, the proposed task allocation model verifies both hedonic conditions, and hence, the problem is easily mapped into a (N , ≻) hedonic coalition formation game, with the preference relations given by (9) and (11) which are also dependent on the underlying TU coalitional game described in Section III-A. Having formulated the problem as a hedonic game, the final task is to provide a distributed algorithm, based on the defined preferences, for forming the coalitions.…”

Section: B Task Allocation As a Hedonic Coalition Formation Gamementioning

confidence: 99%

“…In this context, every player (task or UAV) has a knowledge of the current structure (depending on the nature of the tasks, they may know the structure through the UAVs, without any need to communicate with other tasks). Given the current structure, each player investigates its top preference, and decides to perform a switch operation, if possible through (9) and (11) for the UAVs and tasks respectively. We consider that, the order in which the players make their switch operations is random, but sequential.…”

Section: Hedonic Coalition Formation Algorithmmentioning

confidence: 99%

“…With the emergence of small "mini-UAVs" (MUAVs) that offer advantages in flexibility and cost [5], the usage scenarios for UAVs have significantly increased. In wireless networks, there has been several contributions that tackle the use of UAVs in connectivity improvement [6], routing [7], [8], and medium access control [9].…”

Section: Introductionmentioning

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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Section: B Task Allocation As a Hedonic Coalition Formation Gamementioning

confidence: 99%

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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“…If every node in the network can reach any other node by either direct connection or routing via other nodes, then we say that the network is connected in the sense of (5). In this paper, we assume that the network is connected to begin with and concentrate on how to improve connectivity as the network evolves.…”

Section: Uav-assisted Network Modelmentioning

confidence: 99%

Optimization of MANET connectivity via smart deployment/movement of unmanned air vehicles

Han

Swindlehurst

Liu

2009

IEEE Trans. Veh. Technol.

257

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Abstract-Unmanned air vehicles (UAVs) can provide important communication advantages to ground-based wireless ad hoc networks. In this paper, the location and movement of UAVs are optimized to improve the connectivity of a wireless network. Four types of network connectivity are quantified: global message connectivity, worst-case connectivity, network bisection connectivity, and k-connectivity. The problems of UAV deployment and movement are formulated to improve the different types of connectivity. Both problems are N P -hard. For the deployment case, some heuristic adaptive schemes are proposed to yield simple but effective solutions. In addition, a closed-form solution for the two-node one-UAV case is provided. For k-connectivity, we propose an algorithm that improves connectivity using Delaunay triangulation. To optimize the UAV movement, an algorithm that tracks changes in the network topology is constructed. The simulation results show that by only deploying a single UAV, the global message network connectivity and the worst-case network connectivity can be improved by up to 109% and 60%, respectively. The network bisection connectivity and the k-connectivity can also be significantly improved.Index Terms-Ad hoc network, network connectivity, unmanned air vehicle (UAV).

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“…Gu et al [7] proposed a routing scheme for multi-layer ad hoc networks that use UAVs in their backbones. Gu et al [8] also presented a multiple access protocol for such type of network.…”

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confidence: 99%

Radio Propagation Models in Wireless Networks of Unmanned Aerial Vehicles

Peng¹

2015

IJCNC

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C-ICAMA, a centralized intelligent channel assigned multiple access for multi-layer ad-hoc wireless networks with UAVs

Cited by 27 publications

References 6 publications

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

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

Optimization of MANET connectivity via smart deployment/movement of unmanned air vehicles

Radio Propagation Models in Wireless Networks of Unmanned Aerial Vehicles

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