On the impact of quality of experience (QoE) in a vehicular cloud with various providers
M Aloqaily, B Kantarci… - 2014 11th Annual High …, 2014 - ieeexplore.ieee.org
2014 11th Annual High Capacity Optical Networks and Emerging …, 2014•ieeexplore.ieee.org
With the acceleration of mobile applications, mobile cloud computing is envisioned to be the
best fit solution to make a compromise between users' and service providers' benefits. An
extension of mobile cloud computing, vehicular cloud computing, provides another viable
solution, by consolidating the benefits of mobile cloud computing and vehicular
communications. Among several challenges in this environment, privacy, service price and
provision delay are the most important. In this paper, we propose a framework to address …
best fit solution to make a compromise between users' and service providers' benefits. An
extension of mobile cloud computing, vehicular cloud computing, provides another viable
solution, by consolidating the benefits of mobile cloud computing and vehicular
communications. Among several challenges in this environment, privacy, service price and
provision delay are the most important. In this paper, we propose a framework to address …
With the acceleration of mobile applications, mobile cloud computing is envisioned to be the best fit solution to make a compromise between users' and service providers' benefits. An extension of mobile cloud computing, vehicular cloud computing, provides another viable solution, by consolidating the benefits of mobile cloud computing and vehicular communications. Among several challenges in this environment, privacy, service price and provision delay are the most important. In this paper, we propose a framework to address these challenges in a vehicular cloud based on a quality-of-experience (QoE) approach, discuss the drawbacks of existing architectures, and propose and validate a new architecture. This architecture is an extension of a system [1] we proposed in previous work. QoE is obtained via other mobile nodes in the vehicular cloud, and re-formulated according to a weighted combination of the three key factors: privacy, price and delay. Privacy is defined as a function of the information revealed to the service provider. We evaluate our proposal via simulations, and based on the numerical results, we show that QoE-based service provisioning in a vehicular cloud improves upon a naïve service provision approach, as well as other approaches that address only one of the factors.
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