Adaptive Data Transmission Control for Spatio-temporal Data Retention over Crowds of Vehicles

Abstract

Some specific services for Internet of Things, such as real-time map and providing local weather information, depend strongly on geographical time and location. We refer to the data for such service as spatio-temporal data (STD). When STD is used in a query response system similar to conventional Internet services, users not only need to acquire data actively as required, they must also have functions for retrieving data available STD. Therefore, we propose an STD retention system that uses vehicles as information hubs (InfoHubs) for disseminating and retaining the data in a specific area. In our system, InfoHubs diffuse, maintain, and advertise STD over places and times where the STD are strongly dependent, thereby allowing users to receive such data passively within the specific area. Additionally, because STD are associated with a particular space, the system can reduce search costs. We also propose an adaptive transmission control method that each vehicle effectively operates its wireless resources autonomously and STD are retained and distributed efficiently. Finally, we evaluated our proposed method using simulations and clarified that our proposed system is capable of achieving a coverage rate of nearly 100% for STD while reducing the number of data transmissions compared to existing systems.