In this paper, we address the problem of re-establishing the network connectivity in post-disaster scenarios, where the original wireless infrastructure has been partitioned into multiple network fragments (called islands), operating on different frequencies. To this purpose, we propose the utilization of swarms of dedicated repairing units, called Stem-Nodes (SNs). SNs are provided with Cognitive Radio (CR) and self-positioning capabilities, in order to offer maximum reconfigurability in terms of mobility and wireless technologies supported. Moreover, swarms of SNs can self-organize into STEM-Mesh structure, that works as a dynamic backbone to connect heterogeneous islands using different technologies (e.g. Wi-Fi, Wi-MAX, etc). In this paper, we present three contributions pertaining to STEM-Mesh: (i) we describe a distributed motion control scheme (based on virtual springs approach) that enables SNs to self-organize into dynamic STEM-Mesh structures, (ii) we introduce a discovery scheme, through which SNs can explore the scenario in both spatial and frequency domains, and possibly connect the islands to the STEM-Mesh backbone and (iii) we validate the correctness of the proposed scheme, by verifying the optimal placements of the SNs composing the STEM-Mesh on a simplified scenario (e.g. chain topology). Finally, we evaluate through Omnet++ simulations the ability of STEM-Mesh to maximally re-establish connectivity on partitioned network scenarios.

M. Di Felice, A. Trotta, L. Bedogni, L. Bononi, F. Panzieri, G. Ruggeri, et al. (2013). STEM-Mesh: Self-Organizing Mobile Cognitive Radio Network for Disaster Recovery Operations. Piscataway NY : IEEE [10.1109/IWCMC.2013.6583626].

STEM-Mesh: Self-Organizing Mobile Cognitive Radio Network for Disaster Recovery Operations

DI FELICE, MARCO;TROTTA, ANGELO;BEDOGNI, LUCA;BONONI, LUCIANO;PANZIERI, FABIO;
2013

Abstract

In this paper, we address the problem of re-establishing the network connectivity in post-disaster scenarios, where the original wireless infrastructure has been partitioned into multiple network fragments (called islands), operating on different frequencies. To this purpose, we propose the utilization of swarms of dedicated repairing units, called Stem-Nodes (SNs). SNs are provided with Cognitive Radio (CR) and self-positioning capabilities, in order to offer maximum reconfigurability in terms of mobility and wireless technologies supported. Moreover, swarms of SNs can self-organize into STEM-Mesh structure, that works as a dynamic backbone to connect heterogeneous islands using different technologies (e.g. Wi-Fi, Wi-MAX, etc). In this paper, we present three contributions pertaining to STEM-Mesh: (i) we describe a distributed motion control scheme (based on virtual springs approach) that enables SNs to self-organize into dynamic STEM-Mesh structures, (ii) we introduce a discovery scheme, through which SNs can explore the scenario in both spatial and frequency domains, and possibly connect the islands to the STEM-Mesh backbone and (iii) we validate the correctness of the proposed scheme, by verifying the optimal placements of the SNs composing the STEM-Mesh on a simplified scenario (e.g. chain topology). Finally, we evaluate through Omnet++ simulations the ability of STEM-Mesh to maximally re-establish connectivity on partitioned network scenarios.
2013
Proceedings of the 9th International Wireless Communications & Mobile Computing Conference (IWCMC 2013)
602
608
M. Di Felice, A. Trotta, L. Bedogni, L. Bononi, F. Panzieri, G. Ruggeri, et al. (2013). STEM-Mesh: Self-Organizing Mobile Cognitive Radio Network for Disaster Recovery Operations. Piscataway NY : IEEE [10.1109/IWCMC.2013.6583626].
M. Di Felice; A. Trotta; L. Bedogni; L. Bononi; F. Panzieri; G. Ruggeri; V. Loscrí; P. Pace
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/191493
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 20
  • ???jsp.display-item.citation.isi??? 10
social impact