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Autonomous Relocation Strategies for Cells on Wheels in Public Safety Networks

Published

Author(s)

Kamran Sayrafian, Ladan Rabieekenari

Abstract

Lack of network availability or limited access to communication services are among the challenges that public safety officials and first responders could face during disasters or emergency scenarios. Networking infrastructure can partially (or sometimes fully) breakdown during a catastrophe. At the same time, unusual peaks in traffic load could lead to much higher blocking probability or service interruptions for critical communication. Lack of adequate communication among emergency responders or public safety personnel could put many lives at risks. A possible solution to deal with such scenarios is through the use of mobile/portable infrastructures commonly referred to as Cells on Wheels (COW) or Cells on Light Trucks (COLT). These mobile cells can effectively complement the existing undamaged infrastructure or enable a temporary emergency network by themselves. Given the limited capacity of each cell, variable and spatially non-uniform traffic across the disaster area can make a big impact on the network performance. Not only judicious deployment of the cells can help to meet the coverage and capacity demands across the area, but also intelligent relocation strategies can optimally match the network resources to potentially changing traffic demands. Assuming that each cell can autonomously change its location, in this paper, we propose a decentralized relocation algorithm that adapts network coverage in order to increase the supported users traffic. Our simulations show an average improvement of approximately 35% in the supported traffic compared to static uniform deployment.
Conference Dates
January 8-11, 2017
Conference Location
Las Vegas, NV
Conference Title
The 14th Annual IEEE Consumer Communications & Networking Conference

Citation

Sayrafian, K. and Rabieekenari, L. (2017), Autonomous Relocation Strategies for Cells on Wheels in Public Safety Networks, The 14th Annual IEEE Consumer Communications & Networking Conference, Las Vegas, NV, [online], https://doi.org/10.1109/CCNC.2017.7983079 (Accessed February 29, 2024)
Created July 20, 2017, Updated May 13, 2020