A Mission-Oriented Coordination Framework for Teams of Mobile Aerial and Terrestrial Smart Objects

Pace, Pasquale; Aloi, Gianluca; Caliciuri, Giuseppe; Fortino, Giancarlo

doi:10.1007/s11036-016-0726-4

Cited by 26 publications

(11 citation statements)

References 21 publications

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“…The WSN nodes are mapped to a given sector by means of the barycentric coordinate system as outlined by Equations (1) to (8). The information includes cell structure, information about the nodes, and charge statistics.…”

Section: Sdn Controllermentioning

confidence: 99%

“…• Topology former runs Algorithm 1 and builds a conceptual topology by partitioning the cell into sectors based on the UAV movements. The WSN nodes are mapped to a given sector by means of the barycentric coordinate system as outlined by Equations (1) to (8). Further, the mapped WSN nodes are subdivided into logical clusters on the merit of the mean available charge.…”

Section: Sdn Controllermentioning

confidence: 99%

“…8,18 Fully distributed models are still under experimentation and testing phase. Centralized controllers being easiest to deploy are the heart of experimental SDN and have a single point of failure but come with an advantage of the ease of configuration.…”

Section: Introductionmentioning

confidence: 99%

“…Logically centralized controllers are easy to scale as compared with centralized controllers but are susceptible to failures and produce synchronization problems. 8,18 Fully distributed models are still under experimentation and testing phase. The two major architectures of SDN include forwarding and control element separation (ForCES) 19 and OpenFlow.…”

Section: Introductionmentioning

confidence: 99%

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Efficient data management and control over WSNs using SDN‐enabled aerial networks

Sayeed

Kumar

Sharma

2019

Int J Communication

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The recent developments in collaborative search, acquisition, and tracking have hoisted the geographical barrier. The network between unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) is one such collaboration, which comprises battery-powered static sensor nodes that act as sources and sinks and UAVs that act as relays. This collaborative network presents with opportunities and advantages, but at the same time, configuration of such networks is an arduous task. The WSN nodes are characterized by constant depleting power. Their network itself requires constant management and reconfiguration. These requisites can be slaked through the formation of an efficient data dissemination algorithm, which acclimates according to the network state. Considering this, a data dissemination approach is presented in this paper, which constructs a virtual topology predicated on the charge of WSN nodes utilizing software-defined networks (SDNs) through UAVs. The topology is constantly monitored and reconfigured when required. The aerial nodes are equipped with multiple-input multiple-output (MIMO) antennas in order to facilitate simultaneous communication with the ground nodes, the base station, and the SDN controller. An efficient sleep timer and backoff counter strategies are also utilized by the proposed approach. The SDN controller facilitates the topology formation and maintenance of a sleep timer and a backoff counter. The proposed model is compared with clustered hierarchical layouts and hexagonal cell layouts through the network simulations. The results suggest significant improvements in the proposed model for various metrics, such as lifetime, delay, latency, delivery ratio, and throughput in comparison with the existing solutions.High radio frequency (RF) coverage, high altitude, high throughput, heavy payload, less operating time, ease of use, and low cost are the basic requirements of UAV-CONOPS. Chemical, Biological, Radiological, and Nuclear Reconnaissance (CBRN)-CONOPS whose major purpose is the containment of hazards are also turning towards UAV networks. Cellular network-based air-to-ground links and unmanned aircraft system (UAS)-backbone systems, communication aware sensor distribution, etc are some of the promising aspects of the UAV systems. 2,3 The crucial step towards UAV networks is the development of sustainable multi-UAV environments. National regulations, routing, path planning, quality of service (QoS), integration with Global Information Grid (GIG), mobility control, coordination, and standardization are the steps required for efficient migration towards flying networks (multi-UAV). 4,5 The complexity of the multi-UAV ad hoc networks makes data dissemination also a challenging prospect. Latency, delay, antenna type, timing, etc come into play when we are talking about a network that is so fast moving and dynamic. 6 Multi-UAVs collaborate to achieve common objectives. It is evident that the collaborative UAV and the ground networks together can perform complex tasks. Some of these tasks...

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Section: Sdn Controllermentioning

confidence: 99%

Section: Sdn Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient data management and control over WSNs using SDN‐enabled aerial networks

Sayeed

Kumar

Sharma

2019

Int J Communication

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“…Swarm robotics is the study of how a large number of simple physically embodied agents can be designed such that a desired collective behavior emerges from the local interaction among agents and between agents and the environment. The mono-modal locomotion has been the principal interest of swarm robotics [10] for so long period but also using heterogeneous robots with different locomotion has been investigated [11]. However, multi-modal locomotion seems to be very interesting in order to allow agents performing a variety of tasks adaptively in different environments.…”

Section: Introductionmentioning

confidence: 99%

Exploring unknown environments with multi-modal locomotion swarm

Zedadra

Jouandeau

Séridi

et al. 2016

Intelligent Distributed Computing X

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Swarm robotics is focused on creating intelligent systems from large number of simple robots. The majority of nowadays robots are bound to operations within mono-modal locomotion (i.e. land, air or water). However, some animals have the capacity to alter their locomotion modalities to suit various terrains, operating at high levels of competence in a range of substrates. One of the most significant challenges in bio-inspired robotics is to determine how to use multimodal locomotion to help robots perform a variety of tasks. In this paper, we investigate the use of multi-modal locomotion on a swarm of robots through a multi-target search algorithm inspired from the behavior of flying ants. Features of swarm intelligence such as distributivity, robustness and scalability are ensured by the proposed algorithm. Although the simplicity of movement policies of each agent, complex and efficient exploration is achieved at the team level.

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A collaborative task-oriented scheduling driven routing approach for industrial IoT based on mobile devices

Duan

Luo

et al. 2018

Ad Hoc Networks

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A Mission-Oriented Coordination Framework for Teams of Mobile Aerial and Terrestrial Smart Objects

Cited by 26 publications

References 21 publications

Efficient data management and control over WSNs using SDN‐enabled aerial networks

Efficient data management and control over WSNs using SDN‐enabled aerial networks

Exploring unknown environments with multi-modal locomotion swarm

A collaborative task-oriented scheduling driven routing approach for industrial IoT based on mobile devices

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