Serv-HU: Service Hand-off for UAV-as-a-Service

In this work, we propose a UAV Service Hand-off scheme (Serv-HU) for the UAV-as-a-Service (UaaS) platform to provide seamless UAV services to the end-users. Traditionally, a service provider of a UaaS platform serves a limited application area due to the unavailability of adequate resources such as UAVs. Failing to deliver the service by the service providers for the requested entire application area by the end-user affects the reputation of the service providers. Consequently, the service delivery for a partial application area impacts the overall business, which is unacceptable for a Service-Oriented Architecture. To address this issue, we design a service hand-off scheme that enables the service providers to serve the entire requested application area by the end users with the help of other available service providers. We consider the presence of two types of service providers – Primary (PSP) and Secondary (SSP) in a UaaS platform. We apply a two-stage approach for the UAV service delivery to the end-users. In the first stage, a PSP optimally selects the SSPs for serving the uncovered application area by the PSP. The end-users request the service from the PSP, and on failing to provide the service for the entire application area, the PSP makes the service available from the optimally selected SSPs. In the second stage, we design an optimal pricing strategy that helps in determining the price charged to the end-users considering the involvement of PSPs and SSPs. We apply the Lagrangian multiplier method and Karush-Kuhn-Tucker (KKT) conditions to achieve the outcomes of these two stages. The simulation results depict that the charged price is reduced by <inline-formula><tex-math notation="LaTeX">$10.3 - 12.7\%$</tex-math></inline-formula> while we apply the optimal SSP selection strategy as compared to the random selection of SSPs.

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Publication Details

Journal
IEEE Transactions on Services Computing
Published
2024-12-24
DOI
https://doi.org/10.1109/tsc.2024.3521684
Citations
8
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
2.79
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article

Serv-HU: Service Hand-off for UAV-as-a-Service

Arijit Roy, Veera Manikantha Rayudu Tummala, Vinay Yadam
8 citations
IEEE Transactions on Services Computing
Advanced Manufacturing and Logistics Optimization
2.79
article

Serv-HU: Service Hand-off for UAV-as-a-Service

Arijit Roy, Veera Manikantha Rayudu Tummala, Vinay Yadam
article en
8 citations

Abstract

In this work, we propose a UAV Service Hand-off scheme (Serv-HU) for the UAV-as-a-Service (UaaS) platform to provide seamless UAV services to the end-users. Traditionally, a service provider of a UaaS platform serves a limited application area due to the unavailability of adequate resources such as UAVs. Failing to deliver the service by the service providers for the requested entire application area by the end-user affects the reputation of the service providers. Consequently, the service delivery for a partial application area impacts the overall business, which is unacceptable for a Service-Oriented Architecture. To address this issue, we design a service hand-off scheme that enables the service providers to serve the entire requested application area by the end users with the help of other available service providers. We consider the presence of two types of service providers – Primary (PSP) and Secondary (SSP) in a UaaS platform. We apply a two-stage approach for the UAV service delivery to the end-users. In the first stage, a PSP optimally selects the SSPs for serving the uncovered application area by the PSP. The end-users request the service from the PSP, and on failing to provide the service for the entire application area, the PSP makes the service available from the optimally selected SSPs. In the second stage, we design an optimal pricing strategy that helps in determining the price charged to the end-users considering the involvement of PSPs and SSPs. We apply the Lagrangian multiplier method and Karush-Kuhn-Tucker (KKT) conditions to achieve the outcomes of these two stages. The simulation results depict that the charged price is reduced by <inline-formula><tex-math notation="LaTeX">$10.3 - 12.7\%$</tex-math></inline-formula> while we apply the optimal SSP selection strategy as compared to the random selection of SSPs.

IEEE Transactions on Services ComputingVol. 18(1)
Indian Institute of Technology Patna (IN), Indian Institute of Information Technology Allahabad (IN), Sri Sri University (IN)
Openalex Percentile: Top 9%
Advanced Manufacturing and Logistics Optimization
2.79
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