2,524 research outputs found
Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration
Vehicular fog computing (VFC) has been envisioned as a promising paradigm for
enabling a variety of emerging intelligent transportation systems (ITS).
However, due to inevitable as well as non-negligible issues in wireless
communication, including transmission latency and packet loss, it is still
challenging in implementing safety-critical applications, such as real-time
collision warning in vehicular networks. In this paper, we present a vehicular
fog computing architecture, aiming at supporting effective and real-time
collision warning by offloading computation and communication overheads to
distributed fog nodes. With the system architecture, we further propose a
trajectory calibration based collision warning (TCCW) algorithm along with
tailored communication protocols. Specifically, an application-layer
vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable
distribution with real-world field testing data. Then, a packet loss detection
mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories
based on received vehicle status including GPS coordinates, velocity,
acceleration, heading direction, as well as the estimation of communication
delay and the detection of packet loss. For performance evaluation, we build
the simulation model and implement conventional solutions including cloud-based
warning and fog-based warning without calibration for comparison. Real-vehicle
trajectories are extracted as the input, and the simulation results demonstrate
that the effectiveness of TCCW in terms of the highest precision and recall in
a wide range of scenarios
DFCV: A Novel Approach for Message Dissemination in Connected Vehicles using Dynamic Fog
Vehicular Ad-hoc Network (VANET) has emerged as a promising solution for
enhancing road safety. Routing of messages in VANET is challenging due to
packet delays arising from high mobility of vehicles, frequently changing
topology, and high density of vehicles, leading to frequent route breakages and
packet losses. Previous researchers have used either mobility in vehicular fog
computing or cloud computing to solve the routing issue, but they suffer from
large packet delays and frequent packet losses. We propose Dynamic Fog for
Connected Vehicles (DFCV), a fog computing based scheme which dynamically
creates, increments and destroys fog nodes depending on the communication
needs. The novelty of DFCV lies in providing lower delays and guaranteed
message delivery at high vehicular densities. Simulations were conducted using
hybrid simulation consisting of ns-2, SUMO, and Cloudsim. Results show that
DFCV ensures efficient resource utilization, lower packet delays and losses at
high vehicle densities
Game Theoretic Approaches to Massive Data Processing in Wireless Networks
Wireless communication networks are becoming highly virtualized with
two-layer hierarchies, in which controllers at the upper layer with tasks to
achieve can ask a large number of agents at the lower layer to help realize
computation, storage, and transmission functions. Through offloading data
processing to the agents, the controllers can accomplish otherwise prohibitive
big data processing. Incentive mechanisms are needed for the agents to perform
the controllers' tasks in order to satisfy the corresponding objectives of
controllers and agents. In this article, a hierarchical game framework with
fast convergence and scalability is proposed to meet the demand for real-time
processing for such situations. Possible future research directions in this
emerging area are also discussed
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