FoggyEdge: An Information Centric Computation Offloading and Management Framework for Edge-based Vehicular Fog Computing

Abstract: The recent advances aiming to enable in-network service provisioning are empowering a plethora of smart infrastructure developments, including smart cities, and intelligent transportation systems. Although edge computing in conjunction with roadside units appears as a promising technology for proximate service computations, the rising demands for ubiquitous computing and ultra-low latency requirements from consumer vehicles are challenging the adoption of intelligent transportation systems. Vehicular fog computing which extends the fog computing paradigm in vehicular networks by utilizing either parked or moving vehicles for computations has the potential to further reduce the computation offloading transmission costs. Therefore, with a precise objective of reducing latency and delivering proximate service computations, we integrated vehicular fog computing with roadside edge computing and proposed a four-layer framework named FoggyEdge. The FoggyEdge framework is built at the top of named data networking and employs microservices to perform in-network computations and offloading. A real-world SUMO-based preliminary performance comparison validates FoggyEdge effectiveness. Finally, a few future research directions on incentive mechanisms, security and privacy, optimal vehicular fog location, and load-balancing are summarized.