6533b823fe1ef96bd127eced

RESEARCH PRODUCT

Multi-Layer Offloading at the Edge for Vehicular Networks

Christian GrassoGiovanni SchembraGiuseppe FaraciCarla CirinoSergio PalazzoFabio Busacca

subject

Vehicular ad hoc networkComputer scienceDistributed computingServerComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSReinforcement learningEnergy consumptionEnhanced Data Rates for GSM EvolutionLayer (object-oriented design)Edge computingDomain (software engineering)

description

This paper proposes a multi-layer platform for job offloading in vehicular networks. Offloading is performed from vehicles in the Vehicular Domain towards Multi-Access Edge Computing (MEC) Servers deployed at the edge of the network, and between MEC Servers. Offloading decisions at both domains are challenging for the overall system performance. Optimization at the MEC Layer domain is obtained by model-based Reinforcement Learning, while a strategy to decide the best offloading rate from the Vehicular Domain is defined to achieve the desired trade-off between costs and performance. Numerical analysis shows the achieved performance.

http://hdl.handle.net/20.500.11769/482946