Delta Encoding Correction for Mobile Edge Caching in Internet of Vehicles

Abstract

As one of the key components of intelligent transportation systems, the Internet of Vehicles enables vehicles to acquire and exchange essential information with each other and other facilities. As an infrastructure that directly connects the vehicles to the Internet, the roadside unit (RSU) is responsible for collecting information generated by the vehicle and transmitting it to the control center for analysis. However, ever-increasing number of vehicles and sensors will lead to a large amount of data. Furthermore, there exists redundancy in the data collected within a data collection period by vehicles. Both of these can severely reduce the efficiency of data storage and upload. In this article, we consider that each RSU installs a mobile edge computing server and present delta encoding correction for saving data cache space and transmission time. First, we propose a new cost model and an evaluation method for delta encoding of COPY/ADD class. Then, the type of delta encoding and the corresponding merging rules are defined. Based on these rules, we proposed a minimum delta encoding cost (MDC) algorithm, which adopts the idea of divide and conquer to obtain a superior correcting sequence of delta encoding. Theoretical analysis proves that the proposed MDC algorithm can generate the encoding sequence with the smallest total cost without affecting information reconstruction. In addition, we conduct experiments based on the randomly produced synthetic dataset. Experiment results show that, compared with the Greedy, One-Pass, and 1.5-Pass algorithms, the delta encoding output by the MDC algorithm has better performance in saving cache costs.