# Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks
## 1 Introduction  
The collection of network's physical items (nodes) embedded with software, actuators, sensors, and other various connectivity modules that allow them to send and receive data is considered the Internet of Things (IoT). A number of transmission medium technologies can be used by IoT, such as Wireless Fidelity (Wi-Fi), Bluetooth, and ZigBee, in whichnodes can share data in both infrastructures in an ad hoc way. Because of the huge number of nodes, the Internet of Things (IoT) accommodates huge amounts of data; moreover, these nodes are usually battery-powered, so they have a tendency toward energy depletion. However, traffic jamming is one of the most common and serious issues faced by small to big cities globally and has challenged the public's lives in a challenging environment. The smart cities in the world would like to plan a strategy to decrease their transportation problem because of the increasing population, which affects overfilled roads [1; 2]. Smart cities implement emerging computing technologies to make smart infrastructure objects, facilities, and other city services, which may include education, public safety, transportation, administration, healthcare, real estate, and more intelligent interconnected utilities [3]. The vehicular ad hoc networks (VANETs) can help to overcome this problem by increasing road safety and improving vehicles' mobility. The Internet of Things (IoT) is a fast-growing field in this modern digital era, with millions of functioning physical devices (nodes) interconnected to each other deprived of human interactivity [4]. The Internet of Things can flawlessly, constantly, and pervasively connect and control the real world's different objects through nodes (physical objects) with different types of intelligent wireless sensors. This multiple set of nodes present among the neighbors is defined as sending set [4]. Therefore, choosing an appropriate criterion to select the rebroadcasting node in opportunistic routing can improve the performance of inter-vehicle network characteristics. In addition, the car following model is limited to roads and highways. Hence, drivers must know the vehicle position and direction to make better decisions and avoid link disconnection. To obtain this information, the beacon messages will be used periodically between neighbors. These updates are very costly in many ways. Each update leads to increased bandwidth usage, packet advancement delay, and increased collision risk in the media access layer [5]. Packet collision will cause packet loss, affecting routing efficiency, and, consequently, a crowded condition occurs when the channel is used by vehicles. As a result, collisions will occur by increasing car densities, leading to increased congestion within the network. This crowded condition in the network causes an increase in pocket loss and delay, consequently decreasing the system functionality [6; 7]. In this work, beacon messages were not used in the opportunistic routing protocol to solve this problem. They were introduced as a fault-tolerant protocol for vehicular networks that use the wireless channel broadcast feature and improve the network performance during data forwarding. Additionally, the number of duplicated packets, packet advancement toward the destination, and density are used as the prioritization criteria for rebroadcasting nodes. In this way, the packets are transferred with the least consumed resources and provide appropriate performance considering opportunistic routing schemes. In our proposed method, it is unnecessary to send beacon packets to keep informed of the status of neighbors and the density of the network. Therefore, it is necessary to calculate these parameters; this leads to reduce the congestions and packet loss. Given the above-mentioned items, a fuzzy protocol is presented in this paper for decision-making on rebroadcasting the packets and their routings to the destination. This fuzzy protocol uses three input parameters with the objective of proper decision-making for rebroadcasting.