A Shared Parking Model in Vehicular Network Using Fog and Cloud Environment Oanh Tran Thi Kim, Nguyen Dang Tri, VanDung Nguyen, Nguyen H. Tran, Choong Seon Hong Department of Computer Engineering, Kyung Hee University, 446-701, Korea Email: {ttkoanh, trind, ngvandung85, nguyenth, cshong}@khu.ac.kr Abstract—At the present, the traffic is really in a mess when the number of vehicles is increasing rapidly. As a consequence, finding a parking space is remarkably difficult and expensive. Therefore, solving this problem has attracted the attention of both scientists and companies. Our study also focuses on solving parking problem to relieve the traffic congestion, reduce air pollution and enhance driving effectively. However, unlike other studies, we consider parking problem in the view of IoT. From this perspective, Fog Computing and Roadside Cloud are utilized to find a vacant spot. By utilizing this infrastructures, any parking space at many places can be shared. Then, we analyze and apply the matching theory to solve the parking problem. Accordingly, our proposal not only helps drivers finding an ideal available space but also brings the owners of these places profit. Simulation results demonstrate that the proposed approach is a reliable solution for the finding parking slot. Index Terms—Parking; Fog Computing; Vehicular Cloud; Matching theory I. I NTRODUCTION According to the International Parking Institute (IPI), 60 percent of the world will live in cities in 2030, and IHS Automotive, an industry research group, estimates that the number of vehicles on the roads will tally 284 million, up from 253 million today. This rapid increase leads to the high demand for parking space and during busy periods of the day, it is common for drivers to keep circling in order to search for an available spot. This activity creates many problems and frustrations for drivers. It has been shown that around 30% of the traffic in these congested areas is in fact due to cruising vehicles [1]. Moreover, a study [2] has shown that this would account for waste of 8.37 million gallons of gasoline and over 129,000 tons of CO2 emissions. Therefore, an optimal strategy to find a parking spot can remarkably relieve traffic congestion, reduce air pollution and enhance driving comfortably effectively. These above-mentioned ben- efits are one of many goals VANET. As a result, solving parking problem is considered as a challenge in VANET. Besides, VANET is now in the progress of merging cloud to constitute cloud-based vehicular network. The new excited field has been received particular attention both in industrial and academic levels [3]–[5]. Like an inspiration, it really motivates we to take parking problem to cloud environment. In this paper, we consider parking problem in the view of Internet This work was supported by the ICTR&D program of MSIP\IITP. [R0126- 15-1009, Development of Smart Mediator for Mashup Service and Information Sharing among ICBMS Platform]. * Dr. CS Hong is the corresponding author. of things (IoT), as shown in Fig. 1. There are abundant slots in many areas such as restaurants, bank parking lot, apartment, office building parking lots/garages, and so on. Take a glance at the areas, it is easy to see that the places are characterized by land uses with nearly opposite parking demand schedules. For instance, an office building parking lot is used frequently during daytime business hours, while a restaurant has a high demand for parking in the evening. Therefore, it is extremely wasted if the shared parking policy is not used. Thus, it is realized that these resources of Fog Computing and cloud-based vehicular network as Roadside Cloud can be utilized to find an available parking space. In details, we propose a new robust parking space management system. Our system can cover all available parking spaces which is named RFPARK in large area with Roadside Cloud and Fog Computing. Underlying our design, RFPARK owns an enormous parking space. Therefore, RFPARK can give drivers an ideal vacant parking space based on matching theory approach. To the best of our knowledge, no existing studies have utilized Fog Computing and Vehicular Cloud to address park- ing problem. The paper is organized as follows. Section 2 describes relation works. Section 3 illustrates the proposed system. Section 4 defines the problem as the College Admis- sions Matching. Simulations results are analyzed in Section 5 and conclusion are drawn in Section 6. II. RELATED WORKS As we mentioned above, looking for an empty parking spot in rush hour is a big problem in urban areas, and of great interest, from a research perspective. A number of on- going researches effort could be generally classified into two types: sensors based approach and RSUs based approach. In the sensors based approach [1], [6], [7], fixed sensors are embedded in the parking slots to monitor parking spaces. They detect the availability of slots across some area, and the locations of currently vacant parking slots are spread to the mobile devices and the users can find out a parking in the area. One of the biggest shortcomings of this scheme is that the drivers have to shift their focus from the road to the mobile device they are using. It really is not safe for passengers. It would be better if they are well-guided to an ideal open parking slot. Since, VANET have emerged as an optimal technology to improve not only road safety but also better driving experience. Then, approaches based on 321 Copyright 2015 IEICE APNOMS 2015