14,346 research outputs found
Optimized Distributed Processing in a Vehicular Cloud Architecture
The introduction of cloud data centres has opened new possibilities for the storage and processing of data, augmenting the limited capabilities of peripheral devices. Large data centres tend to be located away from the end users, which increases latency and power consumption in the interconnecting networks. These limitations led to the introduction of edge processing where small-distributed data centres or fog units are located at the edge of the network close to the end user. Vehicles can have substantial processing capabilities, often un-used, in their on-board-units (OBUs). These can be used to augment the network edge processing capabilities. In this paper, we extend our previous work and develop a mixed integer linear programming (MILP) formulation that optimizes the allocation of networking and processing resources to minimize power consumption. Our edge processing architecture includes vehicular processing nodes, edge processing and cloud infrastructure. Furthermore, in this paper our optimization formulation includes delay. Compared to power minimization, our new formulation reduces delay significantly, while resulting in a very limited increase in power consumption
Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles
Vehicular Ad-hoc Networks (VANET) enable efficient communication between
vehicles with the aim of improving road safety. However, the growing number of
vehicles in dense regions and obstacle shadowing regions like Manhattan and
other downtown areas leads to frequent disconnection problems resulting in
disrupted radio wave propagation between vehicles. To address this issue and to
transmit critical messages between vehicles and drones deployed from service
vehicles to overcome road incidents and obstacles, we proposed a hybrid
technique based on fog computing called Hybrid-Vehfog to disseminate messages
in obstacle shadowing regions, and multi-hop technique to disseminate messages
in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to
changes in an environment and benefits in efficiency with robust drone
deployment capability as needed. Performance of Hybrid-Vehfog is carried out in
Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators.
The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message
Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP),
PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data
Networking (NDN) with mobility, and flooding schemes at all vehicle densities
and simulation times
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