EDBT 2026 Demo / reviewers in the wild / expert
Vinay Yadam
dblp:397/2213
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
1 paper |
Edge and fog computing · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Services computing and microservices · 100% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Edge and fog computing › service provisioning
UAV-as-a-service |
0.9 | 1 | 2025 | Serv-HU: Service Hand-off for UAV-as-a-Service · IEEE Trans. Serv. Comput. 2025 |
Services computing and microservices › service management
service pricing |
0.3 | 1 | 2025 | Serv-HU: Service Hand-off for UAV-as-a-Service · IEEE Trans. Serv. Comput. 2025 |
Mathematical optimization
lagrangian multiplier method |
0.3 | 1 | 2025 | Serv-HU: Service Hand-off for UAV-as-a-Service · IEEE Trans. Serv. Comput. 2025 |
Methods — techniques the papers use, named apart from their topics
optimal pricing · 2.6lagrangian multiplier method · 2.6KKT conditions · 2.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Serv-HU: Service Hand-off for UAV-as-a-ServiceabstractIn 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$10.3 - 12.7\%$while we apply the optimal SSP selection strategy as compared to the random selection of SSPs. Arijit Roy 0002, Veera Manikantha Rayudu Tummala, Vinay Yadam |
IEEE Trans. Serv. Comput. | 3 |