A Secure-Efficient Data Collection Algorithm Based on Self-Adaptive Sensing Model in Mobile Internet of Vehicles

Abstract— Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information. However, other performance requirements such as life cycle of nodes, stability and security are not set as primary design objectives. This makes data collection ability of vehicular nodes in real application environment inferior. By considering the features of nodes in wireless IoV, such as large scales of deployment, collection algorithm is proposed for mobile vehicle network environment. An adaptive sensing model is designed to establish vehicular data collection protocol. The protocol adopts group management in model communication. The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes. It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes. In addition, secure data collection between sensing nodes is undertaken as well. The simulation and experiments show that the vehicular node can realize secure and real-time data collection. Moreover, the proposed algorithm is superior in vehicular network life cycle, power consumption and NETWORK TECHNOLOGY AND APPLICATION reliability of data collection by comparing to other algorithms. < final year projects >