English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

The Intelligent Transportation System (ITS) becomes an important component of the smart city toward safer roads, better traffic control, and on-demand service by utilizing and processing the information collected from sensors of vehicles and road side infrastructure. In ITS, Vehicular Cloud Computing (VCC) is a novel technology balancing the requirement of complex services and the limited capability of on-board computers. However, the behaviors of the vehicles in VCC are dynamic, random, and complex. Thus, one of the key safety issues is the frequent disconnections between the vehicle and the Vehicular Cloud (VC) when this vehicle is computing for a service. More important, the connection fault will disturb seriously the normal services of VCC and impact the safety works of the transportation. In this paper, a safety resource allocation mechanism is proposed against connection fault in VCC by using a modified workflow with prediction capability. We firstly propose the probability model for the vehicle movement which satisfies the high dynamics and real-time requirements of VCC. And then we propose a Prediction-based Reliability Maximization Algorithm (PRMA) to realize the safety resource allocation for VCC. The evaluation shows that our mechanism can improve the reliability and guarantee the real-time performance of the VCC.

A Safety Resource Allocation Mechanism against Connection Fault for Vehicular Cloud Computing