COMVIVOR: An Evolutionary Communication Framework Based on Survivors’ Devices Reuse

Briante, Orazio; Loscrì, Valeria; Pace, Pasquale; Ruggeri, Giuseppe; Zema, Nicola Roberto

doi:10.1007/s11277-015-2888-y

Cited by 13 publications

(11 citation statements)

References 25 publications

(35 reference statements)

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“…This framework aims at positioning the special nodes in a better way to improve the propagation. The model shows that the smart positioning enhances the dynamics of propagation [1] [7].…”

Section: Related Workmentioning

confidence: 97%

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A New Mobility Model for Ad Hoc Networks in Disaster Recovery Areas

Manaseer

Alawneh

2017

Int. J. Onl. Eng.

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Abstract-Over the last decade, many researchers have focused on Mobile Ad Hoc Networks as the main communication method in disaster recovery situations. In these researches, there has been marginal focus on the mobility patterns of nodes in disaster recovery scenarios. In this paper, a deeper analysis has been performed on some of the main mobility models used in testing new protocols and a new mobility model is proposed to incorporate some neglected factors concerned with disaster recovery situations.Keywords-MANETs, Disaster recovery, Mobility Model, Random Waypoint, Routing, Hexacell. IntroductionManaging disasters and emergency situations requires accurate and precise messages delivery, on which sensitive decisions making in such scenarios depends [1]. Since most of the infrastructure of any communication is eradicated by the strike of the disaster, this can affect rescuing missions and recovery which are timely critical. The alternative should be planned and set for managing the post disaster situations and emergency issues.Disaster perspective, is how people look at the disaster and what they believe that is most critical to be managed after the disaster, which affects the parameters that are chosen and taken into consideration in such situations, this can affect efficiency of disaster management which supposed to minimize losses in lives [2].Communications play a key role in disasters recovery and emergency management situations. Ad hoc networks are infrastructure-less networks which make the main focus of researches is how to implement them in disasters recovery areas. In order for the study of disaster recovery situations to be more realistic and of higher credibility, the mobility model that describes node movement in the network area should be representative and reflects such scenarios. This is the motive behind the proposed model iJOE

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“…This framework aims at positioning the special nodes in a better way to improve the propagation. The model shows that the smart positioning enhances the dynamics of propagation [1] [7].…”

Section: Related Workmentioning

confidence: 97%

“…In [7], a system to generate a map for pedestrians in disaster situation was proposed. In which the collection of data and sharing messages without end-end networks, that doesn't rely on cloud computing..…”

Section: Related Workmentioning

confidence: 99%

A New Mobility Model for Ad Hoc Networks in Disaster Recovery Areas

Manaseer

Alawneh

2017

Int. J. Onl. Eng.

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“…The mobility model proposed is based mainly on the Jaccard dissimilarity metric to control the deployment of the Unmanned Aerial Vehicles composing the network. A similar work is presented in [34], where instead an in-network density analysis is used to select the physical areas that need to be visited by a flying robot.…”

Section: Related Workmentioning

confidence: 99%

“…These pollution maps were generated using the R Graph tool [43] and following a Kriging-based interpolation [44]. In particular, a Gaussian distribution is used to adjust the parameters coming from UAV [2] UAV [3] UAV [4] UAV [5] UAV [6] UAV [7] UAV [8] UAV [9] UAV [10] UAV [11] UAV [12] UAV [13] UAV [14] UAV [15] UAV [16] UAV [17] UAV [18] UAV [19] UAV [20] UAV [21] UAV [22] UAV [23] UAV [24] UAV [25] UAV [26] UAV [27] UAV [28] UAV [29] UAV [30] UAV [31] UAV [32] UAV [33] UAV [34] UAV [35] UAV [36] UAV [37] UAV [38] UAV [39] UAV [40] UAV [41] UAV [42] UAV [43] UAV [44] UAV [45] UAV [46] UAV UAV [9]…”

Section: Validation and Simulationmentioning

confidence: 99%

Using UAV-Based Systems to Monitor Air Pollution in Areas with Poor Accessibility

Alvear

Zema

Natalizio

et al. 2017

Journal of Advanced Transportation

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Air pollution monitoring has recently become an issue of utmost importance in our society. Despite the fact that crowdsensing approaches could be an adequate solution for urban areas, they cannot be implemented in rural environments. Instead, deploying a fleet of UAVs could be considered an acceptable alternative. Embracing this approach, this paper proposes the use of UAVs equipped with off-the-shelf sensors to perform air pollution monitoring tasks. These UAVs are guided by our proposed Pollution-driven UAV Control (PdUC) algorithm, which is based on a chemotaxis metaheuristic and a local particle swarm optimization strategy. Together, they allow automatically performing the monitoring of a specified area using UAVs. Experimental results show that, when using PdUC, an implicit priority guides the construction of pollution maps by focusing on areas where the pollutants' concentration is higher. This way, accurate maps can be constructed in a faster manner when compared to other strategies. The PdUC scheme is compared against various standard mobility models through simulation, showing that it achieves better performance. In particular, it is able to find the most polluted areas with more accuracy and provides a higher coverage within the time bounds defined by the UAV flight time.

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“…One mode is to manage its own network and other mode is useful to manage other network connection. There is another emergency communication establishment reported in [20] known as COMVIVOR (Communication for survivor). In this framework a smart node positioning is reported for fastened the information propagation.…”

Section: Related Workmentioning

confidence: 99%

Design, development and deployment of a RSSI based wireless network for post disaster management

Kaundal¹,

Sharma²,

Prateek³

et al. 2018

IJET

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The wide spectrum of applications of wireless sensor networks in real time monitoring of disaster prone areas makes it very promising and reliable. The present work focuses on communication link establishment for the first 72 hours just after disaster, highlighting the capability of wireless sensor network especially in disaster prone area. The complete network consisting of 8 wireless nodes with integrated Xbee as a sensor to establish a communication link in between the pursuit team and trapped people. The network is deployed in Dunga Valley of Dehradun, Uttarakhand, a seismic zone with a population of more than 1 lakh. The nodes are capable of recognizing the traveler's location whenever they are passing by the disaster prone areas. The nodes gather RSSI values along with the estimated distances of the traveler (having anchor node) from the pursuit team (having pursuit node). The system has proven its validity by tracking the trapped people in communication deprived area in Dunga Valley by doing mock drill several times. The paper reports the design of wireless network as well as deployment aspects of the nodes in such disaster prone areas.

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COMVIVOR: An Evolutionary Communication Framework Based on Survivors’ Devices Reuse

Cited by 13 publications

References 25 publications

A New Mobility Model for Ad Hoc Networks in Disaster Recovery Areas

A New Mobility Model for Ad Hoc Networks in Disaster Recovery Areas

Using UAV-Based Systems to Monitor Air Pollution in Areas with Poor Accessibility

Design, development and deployment of a RSSI based wireless network for post disaster management

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