## 1 Introduction
Nevertheless, due to the mobility of vehicles, which enhances the uncertainty of their classification and identification, this is indeed a complex job. One useful strategy is to provide nodes with intelligent frameworks that can identify and prevent nodes that behave suspiciously [13; 14; 15]. An Efficient Monitoring System (EMS) is introduced in this article to facilitate network nodes in recognizing selfish nodes. EMS provides a reputation value to every network node to accomplish this goal. As a result, whenever nodes actively participate in a communication activity, the EMS adjusts their reputation value depending on four subsystems (nodes categorization, neighborhood assessment, punishment, and recommendation). The categorization component's objective is to classify nodes into various types based on their reputation value. The categorization mechanism computes each node's cooperation value by relying on their classification. The cooperation value is sent to the determination component, which uses it to penalize or incentivize the nodes based on how cooperative and collaborative they are. The neighbor's assessment system handles how neighbors measure a node's network reputation. This is done by seeking information regarding their views on this. The punishment component punishes the selfish nodes for showing selfish behavior regularly and blacklist such nodes into the network. The recommendation component adjusts the nodes' reputation value and relies on the information exchanged by any of the other components after a communication opportunity. The EMS can categorize, track, and take action against such types of nodes. Whenever a selfish or non-cooperative node is identified, the EMS broadcasts an alert to all the neighbors of the node, enabling the message to circulate across the network. This alert can notify cooperative nodes that a newly selfish node has entered the network. The following are the essential points of this article:  
* A summary of the most common credit-based, reputation-based, tit-for-tat-based, and hybrid-based cooperative communication approaches in vehicular networks. * A case study demonstrating the negative effect of selfish and misbehavior nodes on VDTN efficiency using the package delivery probability, packet average delay, energy consumption, and amount of dropped packages as the evaluation criteria. * The framework of an EMS is made up of three distinct components to detect and elude selfish nodes to minimize their effect on cooperative node outcomes. * Analysis of the presented EMS solution's effect on VDTN efficiency in terms of package delivery probability, package average delay, energy consumption, and the amount of dropped packets. The remaining article is organized into the following different sections. The overview of existing incentive techniques is presented in Section 2. Section 3 provides a discussion to illustrate the effect of selfish nodes inside a VDTN network. The efficient monitoring system and its implementation in VDTNs are described in Section 4. In Section 5, the experimental results are presented. Lastly, the article is concluded, and future works are discussed in Section 6.