Experimental Test-Bed for Bumblebee-Inspired Channel Selection in an Ad-Hoc Network

Gill, Kuldeep S.; McClintick, Kyle W.; Kanthasamy, Nivetha; Tolbert, Jefferey; Nguyen, Duong; Nguyen, Son Thanh; Wernsing, Galahad M.; Moore, Valerie; Gelman, Ian Solomon; O'Neil, Alexander; Schubert, Nicholas; Coogan, Corey; Murdy, Krysta; Mahan, Brian; Halama, Sylvester; Heath, Kevin N.; Ryder, Elizabeth F.; Gegear, Robert J.; Wyglinski, Alexander M.

doi:10.1109/vtcfall.2018.8690978

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…Given how the proposed bumblebee-based VDSA algorithm relies on the analysis of sensing results that can be performed by multiple nodes (vehicles), as well as how it assumes use of memory for storing past values, this algorithm introduces an additional cost to the system in terms of increased computational, memory, and communication overhead. The amount of required additional computations related to CBR estimation should be minimal, as these are performed only by the entity responsible for selecting the frequency band (e.g., the platoon leader) and requires only a limited number of additions and divisions in the calculation of ( 22) and ( 23), or multiplications and additions when using EWMA for (24). A slightly more complex scenario is the heuristic allocation of the sensing samples according to (20) and (21) as it requires the calculation of the exponential function.…”

Section: B Computational and Memory Complexitymentioning

confidence: 99%

“…Finally, the memory cost of the proposed approach is related only to the CBR estimation using (22) and averaging using either (23) or (24). In the worst case, (22) requires storage of 2JL integers, which corresponds to the number of sensed busy samples k (j) l and the total number of sensed samples N (j) l per channel.…”

Section: B Computational and Memory Complexitymentioning

confidence: 99%

“…The sensing results were gathered in a 10 s observation window, corresponding to J = 100 iterations of the VDSA algorithm, which were used in the calculation of the CBR estimates for the bumblebee-based VDSA. Furthermore, the calculated CBR values were smoothed according to the EWMA rule, defined as in (24), with α = 0.7. Two sensing channel selection methods were considered, with the band allocation for sensing following (20) presented in Section III-B for γ = 0 (uniform sampling) and γ = −2 (non-uniform sampling), respectively.…”

Section: A Simulation Setupmentioning

confidence: 99%

“…The quantitative performance bound was simulated using multi-channel queuing theory for the bumblebee foraging algorithm [23]. In [24], an experimental study was conducted for the bumblebee-inspired channel selection in an ad-hoc network using a collection of Pluto [25] Software-Defined Radio (SDR) units from Analog Devices.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Memory Enabled Bumblebee-Based Dynamic Spectrum Access for Platooning Environments

Gill

Kryszkiewicz

Sroka

et al. 2023

IEEE Trans. Veh. Technol.

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In this paper, we propose a novel memory-enabled non-uniform sampling-based bumblebee foraging algorithm (MEB) designed for optimal channel selection in a distributed Vehicular Dynamic Spectrum Access (VDSA) framework employed in a platoon operating environment. Given how bumblebee behavioral models are designed to support adaptation in complex and highly time-varying environments, these models can be employed by connected vehicles to enable their operation within a dynamically changing network topology and support their selection of optimal channels possessing low levels of congestion to achieve high throughput. As a result, the proposed VDSAbased optimal channel selection employs fundamental concepts from the bumblebee foraging model. In the proposed approach, the Channel Busy Ratio (CBR) of all channels is computed and stored in memory to be accessed by the MEB algorithm to make the necessary channel switching decisions. Two averaging techniques, Sliding Window Average (SWA) and Exponentially Weighted Moving Average (EWMA), are employed to leverage past samples and are evaluated against the no-memory case. Due to the high variability of the environment (e.g., high velocities, changing density of vehicles on the road), we propose to calculate the CBR by employing non-uniform channel sampling allocations as well as evaluate it using both simplified numerical and realistic Vehicle-to-Vehicle (V2V) computer simulations. The numerical simulation results show that gains in the probability of the best channel selection can be achieved relative to a uniform sampling allocation approach. By utilizing memory, we observe an additional increase in the channel selection performance. Similarly, we see an increase in the probability of successful reception when utilizing the bumblebee algorithm via a systemlevel simulator.

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Section: B Computational and Memory Complexitymentioning

confidence: 99%

Section: B Computational and Memory Complexitymentioning

confidence: 99%

Section: A Simulation Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Memory Enabled Bumblebee-Based Dynamic Spectrum Access for Platooning Environments

Gill

Kryszkiewicz

Sroka

et al. 2023

IEEE Trans. Veh. Technol.

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Bumblebee-Inspired C-V2X Dynamic Spectrum Access Testbed Using OpenAirInterface

Gill

Heath

Chuke

et al. 2020

2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)

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Distributed Vehicular Dynamic Spectrum Access for Platooning Environments

Sroka

Kryszkiewicz²,

Sybis³

et al. 2020

2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)

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In this paper, we propose a distributed Vehicular Dynamic Spectrum Access (VDSA) framework for vehicles operating in platoon formations. Given the potential for significant congestion in licensed frequency bands for vehicular applications such as 5.9 GHz. Our approach proposes to offload part of the intra-platoon data traffic to spectral white-spaces in order to enhance vehicular connectivity in support of on-road operations. To enable VDSA, a Bumblebee-based decision making process is employed which is based on the behavioral models of animals, is employed to provide a means of distributed transmission band selection. Simulation results show the distributed VDSA framework improves the leader packets reception ratio by 5%, thus indicating its potential to increase in reliability of intraplatoon communications.

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Experimental Test-Bed for Bumblebee-Inspired Channel Selection in an Ad-Hoc Network

Cited by 3 publications

References 13 publications

Memory Enabled Bumblebee-Based Dynamic Spectrum Access for Platooning Environments

Memory Enabled Bumblebee-Based Dynamic Spectrum Access for Platooning Environments

Bumblebee-Inspired C-V2X Dynamic Spectrum Access Testbed Using OpenAirInterface

Distributed Vehicular Dynamic Spectrum Access for Platooning Environments

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