In this paper, we design a test-bed for a bumblebee inspired channel selection algorithm employed on a wireless ad-hoc network. Vehicles in connected ad-hoc networks are routinely challenged with the complex decision-making problem of either staying with the same channel or moving to a different channel under highly time-varying channel quality conditions. In order to enable vehicles to adapt to these time-varying channel conditions, we designed a bumblebee-inspired decision-making algorithm. The proposed algorithm uses temporal channel quality information for optimal channel selection. Channel energy values are used for making switching decisions by taking switching costs into consideration. We implemented a test-bed inside a controlled laboratory environment using ADALM-Pluto Software-defined radios (SDRs) to evaluate the proposed approach. The test-bed can be configured to emulate a vehicular network environment. Furthermore, in this work we show the novelty of our bumblebee algorithm for optimal channel selection in a steady environment. We compared the performance of our Bumblebee algorithm with a random channel selection algorithm, and noticed an increase of 158.33% in the throughput of the network with our algorithm.
Experimental Test-Bed for Bumblebee-Inspired Channel Selection in an Ad-Hoc Network
2018-08-01
7021726 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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