Energy Efficient and Throughput Oriented Route Optimization Models in the Internet of Vehicles: A Survey

Abstract

The Internet of Vehicles (IoV) has emerged as a promising paradigm that integrates vehicles, communication technologies, and the Internet to foster intelligent transportation systems. To fully exploit the potential of IoV, efficient route optimization models are crucial to optimize energy consumption while ensuring high throughput. This survey paper aims to provide a comprehensive analysis of existing research on energy-efficient and throughput-oriented route optimization models in IoV. The primary objective of this survey is to categorize and evaluate various route optimization techniques that focus on enhancing energy efficiency and throughput in the IoV context. We present a systematic review of literature, encompassing academic papers, conference proceedings, and technical reports up to the time of this research. By examining the state-of-the-art approaches, we identify the underlying principles, strengths, and limitations of each method. The survey first delves into the foundational concepts of IoV and their significance in modern transportation systems. We elucidate the challenges faced in IoV route optimization concerning energy consumption, data transformation, bandwidth contention, and network congestion. In the main body of the survey, we classify existing route optimization models based on their energy efficiency and throughput-oriented objectives. The energy-efficient category encompasses methodologies that aim to minimize a node’s energy consumption and extend its battery life, considering factors such as the routing process involved (massage broadcasting and rebroadcasting), link state, and traffic flow patterns. On the other hand, the throughput-oriented category focuses on maximizing information transformation and ensuring low latency during operational time. Furthermore, we identify open challenges and research gaps in the field of energy-efficient and throughput-oriented route optimization for IoV. These gaps pave the way for future research directions, which can lead to the development of more robust, scalable, and adaptive routing solutions. By evaluating the strengths and weaknesses of various approaches, we aim to inspire researchers, engineers, and entrepreneurs to develop innovative solutions that enhance energy efficiency, maximize throughput, and foster the realization of a smarter and more sustainable transportation ecosystem.