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UID:927@lincs.fr
DTSTART;TZID=Europe/Paris:20251104T140000
DTEND;TZID=Europe/Paris:20251104T180000
DTSTAMP:20251126T123214Z
URL:https://www.lincs.fr/events/technical-economic-and-environmental-evalu
 ation-of-vehicular-and-edge-computing/
SUMMARY:Technical\, Economic and Environmental Evaluation of Vehicular and
 Edge Computing
DESCRIPTION:Keywords: Vehicular Cloud Computing\, Task Offloading\,
 Game-Theoretic Optimization\, Sustainable Computing\n\nAbstract:\nThis
 thesis investigates the technical\, economical and environmental
 feasibility of computing architectures for supporting delaysensitive
 applications such as Augmented Reality (AR) and Autonomous Driving (AD).
 While Cloud Computing (CC) is the prevalent computing paradigm today\, it
 cannot offer sufficiently low latency. This limitation is overcome by Edge
 Computing (EC)\, which consists in deploying computational capability at
 the edge of the access network. However\, EC entails high infrastructure
 costs and raises environmental concerns\, due to the short lifecycle of
 electronic devices (around four years) and increased energy
 consumption.\n\nMeanwhile\, the number of connected vehicles is steadily
 increasing. These vehicles already carry onboard computing and
 communication resources that can be opportunistically exploited\, not only
 for driving-related tasks\, but also for task offloading computation from
 external devices\, e.g.\, smartphones\, laptops\, or wearable health
 devices of end-users. These resources available in the vehicles can be
 managed under the paradigm of Vehicular Cloud Computing (VCC).\n\nIn this
 thesis\, we first analyze the economic feasibility of Edge Computing
 deployment through a game-theoretic model\, showing how multitenant
 cooperation can mitigate the high cost of deployment. Then\, we evaluate
 under which conditions VCC can replace EC\, i.e.\, whether offloading tasks
 to vehicles can provide similar performance to EC. Results are obtained via
 high fidelity network and mobility simulations\, in an urban mobile network
 scenario. We find that VCC can achieve ultra-low latency\, with delays of
 about 10 ms\, even when vehicles are sparsely distributed. A comparative
 cost analysis shows that replacing EC with VCC can reduce infrastructure
 expenditure by approximately 10% over five years. Finally\, we propose a
 VCC management scheme to optimize energy consumption\, carbon emissions\,
 and to compute a fair allocation of the revenues generated by service
 end-user tasks.\n\nThe scheme is based on mathematical programming and
 coalitional game theory. Via Monte-Carlo simulation\, we show that energy
 consumption due to VCC is below 0.1% of the overall vehicle consumption in
 realistic scenarios\, and that vehicle owners receive substantial
 incentives for participating in task execution.\n\nIn summary\, this thesis
 demonstrates the feasibility of future generation mobile network
 architectures\, such as Edge Computing and Vehicular Cloud Computing\, to
 support extremely low-latency applications.
CATEGORIES:PhD Defense
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TZID:Europe/Paris
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DTSTART:20251026T020000
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