CTR: Cluster based Topological Routing for Disaster Response Networks
Abstract
Large scale disasters require prompt rescue and relief operations to restrict further casualties. To carry out such operations, it is essential to have a communication infrastructure between survivors and responders, which is often impaired due to the disaster. Off-the-shelf wireless devices such as smartphones, PDAs and Laptops offer an effective solution towards the establishment of makeshift communication infrastructure. However, in the absence of bonafide power sources, it becomes imperative to judiciously utilize energy (battery power) of such devices such that the network is functional until primary infrastructure is restored. This paper proposes a novel approach, called Cluster based Topological Routing (CTR) that prolongs the longevity of the network by exploiting the natural gathering of survivors in shelter points. In particular, the clustering algorithm identifies such survivor groups combined with a data forwarding approach, to minimize the number of data transmissions yet guaranteeing the required packet delivery and network latency. Our extensive simulation study shows that CTR yields twice the network lifetime than existing routing approaches in disaster response networks, while ensuring comparable packet delivery and network latency.
Recommended Citation
V. K. Shah et al., "CTR: Cluster based Topological Routing for Disaster Response Networks," Proceedings of the 2017 IEEE International Conference on Communications (2017, Paris, France), Institute of Electrical and Electronics Engineers (IEEE), May 2017.
The definitive version is available at https://doi.org/10.1109/ICC.2017.7996327
Meeting Name
2017 IEEE International Conference on Communications, ICC 2017 (2017: May 21-25, Paris, France)
Department(s)
Computer Science
Research Center/Lab(s)
Center for High Performance Computing Research
International Standard Book Number (ISBN)
978-1-4673-8999-0
International Standard Serial Number (ISSN)
1938-1883
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 May 2017
Comments
This work is partially supported by Defense Threat Reduction Agency (DTRA) grant HDTRA1-10-1-0085, North Atlantic Treaty Organization (NATO) under SPS grant G4936 "Hybrid Sensor Network for Emergency Critical Scenarios", NSF grants under award numbers CNS-1545037, CNS-1545050, DGE-1433659, and a grant from Intelligent Systems Center at Missouri S&T.