A Mission-Oriented Service Discovery Mechanism for Highly Dynamic Autonomous Swarms of Unmanned Systems

Autefage, Vincent; Chaumette, Serge; Magoni, Damien

doi:10.1109/icac.2015.28

Cited by 12 publications

(4 citation statements)

References 22 publications

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“…Autefage et al (Autefage et al , 2015) proposed a service discovery system for mobile swarm of unmanned system (UMS). This system is similar to ours in that the system tries to discover necessary devices in a mission-oriented manner.…”

Section: Related Workmentioning

confidence: 99%

Design and evaluation of mission-oriented sensing platform with military analogy

Inomoto

Saiki

Nakamura

et al. 2017

IJPCC

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The purpose of this paper is to perform large-scale environmental sensing with a lot of IoT devices, as typically seen in Smart City, efficiently and for multiple applications. In this paper, we propose a novel sensing method, called mission oriented sensing, which accepts multiple and dynamic sensing purposes on a single infrastructure. Design/methodology/approach The proposed method achieves the purpose by dealing sensing configuration (application's purpose) as mission. It realizes sharing single infrastructure by accepting multiple missions in parallel, and it accepts missions' update anytime. In addition, the sensing platform based on military analogy can command and control a lot of IoT devices in good order, and this realizes mission oriented sensing above. Findings Introducing mission oriented sensing, multiple purpose large-scale sensing can be conducted efficiently. The experimental evaluation with a prototype platform shows the practical feasibility. In addition, the result shows that it is effective to update sensing configuration dynamically. Research limitations/implications The proposed method focuses aggregating environmental sensor value from a lot of devices, and thus it can treat stream data such as video or audio or control a specific device directly. Originality/value In proposed method, a single sensing infrastructure can be used by multiple applications, and it admits heterogeneous devices in a single infrastructure. In addition, the proposed method has less technical restriction and developers can implement actual platform with technologies for context.

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Section: Related Workmentioning

confidence: 99%

Design and evaluation of mission-oriented sensing platform with military analogy

Inomoto

Saiki

Nakamura

et al. 2017

IJPCC

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“…Connectivity issues for random networks are well understood in the static case [1], but are more complex in mobile networks [2]. The effects of mobility are receiving increasing attention in the context of device-to-device (D2D) networks [3], [4], drone swarms [5] and IoT applications [6]. Hence, in this paper we are motivated to investigate a fundamental issue relating to mobile connectivity, namely, how long will two mobile devices be connected over a finite time horizon?…”

Section: Introductionmentioning

confidence: 99%

Connectivity Times for Mobile D2D Networks

Smith

Coon

2018

2018 IEEE International Conference on Communications (ICC)

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Connectivity questions for mobile D2D networks are often approached by considering steady state performance metrics. This is due to the difficulty in handling a finite time horizon with random mobility. Hence, in this paper we create a framework to evaluate connectivity time in closed form over a finite time horizon for mobile devices. The basic metric is the mean proportion of time devices are connected over a finite period. The methodology is shown to deliver closed form results for a variety of deterministic and random mobility models in both fading and non-fading scenarios. This allows a comparison of mobility types and an understanding of the underlying parameters. In addition, an approach is developed which allows different mobility types to be compared on the basis of a single 'equivalent' speed and also the overall framework allows the energy requirements of certain mobility control mechanisms to be evaluated.

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“…In order to validate the accuracy of experimentation with mobile devices performed with NEmu, we replicate performance results obtained by simulation of a multiagents system called AMiRALE [23]. Emulation is performed with NEmu while simulations are carried out with JBotSim [24], a Java library which enables the design of low and high level communication scenarios and behaviors of heterogeneous mobile nodes.…”

Section: Amirale Experiments Replicationmentioning

confidence: 99%

NEmu: A distributed testbed for the virtualization of dynamic, fixed and mobile networks

Autefage

Magoni

2016

Computer Communications

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To cite this version:Vincent Autefage, Damien Magoni. NEmu: A distributed testbed for the virtualization of dynamic, fixed and mobile networks. Computer Communications, Elsevier, 2016, 80, pp.33-44. 10.1016/j.comcom.2016 AbstractExperimentation is typically the last step before launching a network application on a large production scale. However, it is often difficult to gather enough hardware resources for experimenting with a reasonably sized distributed application inside a controlled environment. Virtualization is thus a handy technique for creating such an experimentation testbed. We propose a tool called NEmu designed to create virtual dynamic networks by using emulation for testing and evaluating prototypes of networked or distributed applications with a complete control over the network topology and link parameters. NEmu leverages system emulators such as QEMU for virtualizing the hosts and the routers. It uses vnd for virtualizing components such as links and switches. In addition, NEmu allows users to create such customized topologies with limited hardware resources and without any administrative rights. We validate NEmu by replicating two network experiments and by showing that NEmu gives results very similar to the original ones.

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A Mission-Oriented Service Discovery Mechanism for Highly Dynamic Autonomous Swarms of Unmanned Systems

Cited by 12 publications

References 22 publications

Design and evaluation of mission-oriented sensing platform with military analogy

Design and evaluation of mission-oriented sensing platform with military analogy

Connectivity Times for Mobile D2D Networks

NEmu: A distributed testbed for the virtualization of dynamic, fixed and mobile networks

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