# Quantitative Study on the Impact of Energy Consumption Based Dynamic Selfishness in MANETs +
## 2 Related Work
### Incentive Mechanisms for Selfish Nodes  
To reduce the harmful effects on the network caused by the presence of selfish nodes, encouraging nodes to cooperate is critical to ensure the network functions properly. In general, incentive mechanisms can be classified into the following three main kinds: reputation-based, credit-based, and barter-based systems. The main idea of a reputation-based incentive mechanism is that more cooperative nodes get higher reputation scores [16]. The most challenging issue of the reputation-based incentive mechanism is to accurately measure the reputation scores to each node in the network. [PERSON] et al. (2017) proposed a social norm based incentive mechanism for network coding (NC) in MANETs. A reputation system with punishment and reward is considered in the social norm. [PERSON] et al. (2018) introduced a hierarchical account-aided reputation management system that integrates resource and price systems to stimulate the node cooperation in large-scale MANETs. [PERSON] et al. (2019) proposed a secure incentive scheme in highway VANETs scenarios. The scheme utilizes \"virtual checks\" to ensure the security and fairness of the cooperation. The authors also developed a reputation system to stimulate cooperative nodes and penalize malicious nodes. [PERSON] et al. (2018) proposed a hybrid incentive system taking advantage of both reputation mechanisms and monitoring modules in Vehicular Delay-Tolerant Networks (VDTNs). The system encourage selfish nodes to share their resources rather than excluding them from the network. [PERSON] et al. (2019) investigated a blockchain-based incentive content delivery in autonomous vehicular social networks. The reputation assessment models in the paper is based on both social features and user behaviors. In sum, reputation-based incentive mechanisms highly rely on historical information about the node behaviors, which results in the downfall of this type of incentive mechanism. The credit-based incentive mechanism exploits some rewarding mechanisms to nodes for indicating cooperativeness ([PERSON] et al., 2019). [PERSON] et al. (2019) introduced the Nuglet technique. The authors proposed a credit-based incentive protocol that requires the node to forward each packet to its security module in MANETs. The security module, nuglet, is a counter for each node. The nuglet increases (decreases) when the node sends its own (other's) packets. [PERSON] et al. (2019) proposed an enhanced selfish node detection system based on a watchdog mechanism in MANETs. The system revives selfish nodes in the network, instead of isolating them. A virtual payment (credit) is defined in the system, and forwarding nodes will get credit while selfish nodes will get debited. If a node does not have enough credit, it cannot act as a source node to send packets. The barter-based strategy is also known as Tit-for-Tat (TFT) to punish uncooperative nodes. In a TFT strategy, a node takes cooperative or selfish action according to the action from the previous node. Each node in the network represents a player in game theories. Hence, the barter-based strategy is also considered as a game theory approach. [PERSON] et al. (2019) proposed a reward allocation mechanism based on the integration of game theory and reinforcement learning algorithms to maximize the whole network performance. [PERSON] et al. (2019) integrated a reputation system and a price-based system for selfish node detection and incentives in MANETs with a game theory perspective. [PERSON] et al. (2019) introduced an evolutionary game theory based intelligent packet forwarding approach that stimulates the node cooperation in MANETs. [PERSON] et al. (2019) proposed a Stackelberg game based optimal pricing strategy to model data offloading in VANETs scenarios. [PERSON] et al. (2019) proposed two TFT-based strategies, namely Group Reputation and Cooperative Detection strategies, to enforce MAC layer cooperation in VANETs. The proposals address the greediness problem and achieve better misbehavior detection performance.