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A Hybrid Network Emergency Communication Model

A Hybrid Network Emergency Communication Model

Abdussalam Nuri Baryun, Khalid Al Begain, David Villa
Copyright: © 2013 |Volume: 4 |Issue: 2 |Pages: 23
ISSN: 1947-9158|EISSN: 1947-9166|EISBN13: 9781466632653|DOI: 10.4018/jhcr.2013040102
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MLA

Baryun, Abdussalam Nuri, et al. "A Hybrid Network Emergency Communication Model." IJHCR vol.4, no.2 2013: pp.17-39. http://doi.org/10.4018/jhcr.2013040102

APA

Baryun, A. N., Al Begain, K., & Villa, D. (2013). A Hybrid Network Emergency Communication Model. International Journal of Handheld Computing Research (IJHCR), 4(2), 17-39. http://doi.org/10.4018/jhcr.2013040102

Chicago

Baryun, Abdussalam Nuri, Khalid Al Begain, and David Villa. "A Hybrid Network Emergency Communication Model," International Journal of Handheld Computing Research (IJHCR) 4, no.2: 17-39. http://doi.org/10.4018/jhcr.2013040102

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Abstract

To communicate within disaster scenarios, different devices/systems need to cooperate with specific protocols. The key communication protocol needs to provide interoperability among these systems and provide the solution for emergency services. The paper studies the hybrid network disaster recovery (HNDR) systems and classifies its communication scenarios and requirements. The authors propose a new networking protocol for the hybrid network, with ability to forward sessions and messages through different transport protocols, and copes with node mobility and node failure. The paper considers heterogeneous network disaster recovery scenario and proposes a cost effective and easy to deploy hybrid network emergency communication protocol (HNEC). This internetwork protocol is a specific model of the inter-domain messaging (IDM) protocol for emergency communications. The routing protocol procedure is similar to the reactive AODV procedure but is different in maintaining routes from unpredicted link breaks or node failure. A detailed simulation model with the designed network layer model is used to investigate network delivery rate and end-to-end delay performance. The performance results are analyzed using varying node load, mobility speed, and network size.

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