Recently, the concept of combining ‘things’ on the Internet to provide various services has gained tremendous momentum. Such a concept has also impacted the automotive industry, giving rise to the Internet of Vehicles (IoV). IoV enables Internet connectivity and communication between smart vehicles and other devices on the network. Shifting the computing towards the edge of the network reduces communication delays and provides various services instantly. However, both distributed (i.e., edge computing) and central computing (i.e., cloud computing) architectures suffer from several inherent issues, such as high latency, high infrastructure cost, and performance degra-dation. We propose a novel concept of computation, which we call moisture computing (MC) to be deployed slightly away from the edge of the network but below the cloud infrastructure. The MC-based IoV architecture can be used to assist smart vehicles in collaborating to solve traffic monitor-ing, road safety, and management issues. Moreover, the MC can be used to dispatch emergency and roadside assistance in case of incidents and accidents. In contrast to the cloud which covers a broader area, the MC provides smart vehicles with critical information with fewer delays. We argue that the MC can help reduce infrastructure costs efficiently since it requires a medium-scale data center with moderate resources to cover a wider area compared to small-scale data centers in edge computing and large-scale data centers in cloud computing. We performed mathematical analyses to demonstrate that the MC reduces network delays and enhances the response time in contrast to the edge and cloud infrastructure. Moreover, we present a simulation-based implementation to evaluate the computational performance of the MC. Our simulation results show that the total processing time (computation delay and communication delay) is optimized, and delays are minimized in the MC as apposed to the traditional approaches.
Funding: This work was supported in part by Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No.2021-0-00590,Decentralized High Performance Consensus for Large-Scale Blockchains), in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology under Grant 2018R1D1A1B07048697, and in part by the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government Ministry of Trade, Industry and Energy (MOTIE) (The Competency Development Program for Industry Specialist) under Grant P0008703. This research was also partly supported by the Deanship of Research, Islamic University of Madinah, Madinah, Saudi Arabia.This work was supported in part by Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No. 2021-0-00590, Decentralized High Performance Consensus for Large-Scale Blockchains), in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology under Grant 2018R1D1A1B07048697, and in part by the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government Ministry of Trade, Industry and Energy (MOTIE) (The Competency Development Program for Industry Specialist) under Grant P0008703. This research was also partly supported by the Dean-ship of Research, Islamic University of Madinah, Madinah, Saudi Arabia.
