# Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks
## 1 Introduction
Given the importance of the packet's advancement, the variation and local density of the vehicles, and controlling duplicate packets in the network, these three variables are chosen as the inputs to the fuzzy system for proper decision-making. The routing tries to choose the rebroadcasting nodes with the maximum advancement toward the destination. Moreover, the local density of a parameter is dynamic in the network. Routing should make proper decisions considering the density. Finally, the number of duplications of the packets cause congestions and collisions in the network for which the routing should have required to control. Consequently, routing and packet rebroadcasting use fuzzy decision-making with these three parameters. For improving the limitations found in the research literature and for choosing the right routes for retransmission, we proposed the fuzzy logic to merge the following three concepts: (i) packet improvement to minimize delay between links; (ii) local control to manage rapid communicational changes, which may minimize retransmission and maximize throughput; and (iii) choosing nodes with the least number of received duplicate packets. With the implementation of fuzzy logic on the rebroadcasting physical device (node), the nearest best node is selected from the set of relays, leading to generating routes with maximum throughput and lower delay for end-to-end node with the effective rate of data delivery. In multi-hop wireless sensor network unequal clustering, the size of clusters increases as the get farther from the road side unit. Therefore, when the nodes are densely aggregated around the roadside unit, the cluster head energy decreases rapidly. In addition to its packets, the cluster head node must guide other clusters' packets. Using the fuzzy system while considering measures like the grade of each device and its space (distance) to the road side unit leads to decreasing transmission delay, increasing network lifetime and decreasing energy consumption during cluster head selection and cluster formation [7; 8]. Employing fuzzy system is a solution to overcome wireless sensor networks uncertainty problem [9]. Compared to non-fuzzy methods, employing fuzzy systems has many advantages: decreasing computational complexity, requiring less memory, and decreasing network development cost [6]. According to the wireless sensor network limitations and clustering, designing suitable routing methods can also improve performance and prolong lifetime in multi-hop wireless sensor networks [10]. The multi-hop (more than one hope) communications provide a consistent mechanism of communication for transferring the information in VANETs. Given the unique features of VANETs, several routing solutions have been proposed for these networks. Their main characteristics include being dynamic, high-mobility, and responsive to the network density. The network density parameter is one of the main parameters functioning to deliver the data packets to the destination. For minimum density in VANETs the routing protocols frequently desired negotiation between latency and reliability [8] Multi-hop routing has recently taken the devotion of the researchers. In this protocol, a packet is sent to all vehicles in the network in a flooding manner. Different protocols have been proposed in the recent years for the efficiency of broadcast communications and reliable transmissions that are known as smart flooding protocols [11]. The objective of presenting these procedures is to minimize the quantity of the multicast packets and an efficient use of the bandwidth in the network. Flooded transmission of the data is a protocol for sending a data packet from a source to all of its neighboring nodes. The first protocol for the flooded transmission is the simple flooding protocol [12], in which when a packet is generated and sent from a node, the receiving node rebroadcasts the packet. In order to prevent multiplier broadcasting of the same packet, each node contains a list of delivered data packets and their lifetimes.