# A Credit-Based Congestion-Aware Incentive Scheme for DTNs
## 2 Related Work  
In [1], [PERSON] proposes the delay-tolerant networking architecture for interoperability between and among challenged networks. In addition, [PERSON] and other authors in [2] formulate the delay-tolerant networking routing problem and propose a framework for evaluating routing algorithms in such environments. Now, many routing and dissemination protocols have been proposed to effectively deliver messages. For example, [PERSON] et al. [3] propose a probabilistic routing protocol for intermittently connected networks. When a node encounters another node, they will exchange information about the delivery predictabilities, and decide to forward messages based on the delivery predictabilities. [PERSON] et al. [4] develop a new strategy for forwarding, which is referred to as delegation forwarding. [PERSON] et al. [5] design and evaluate BUBBLE, a novel social-based forwarding algorithm, which utilizes the metrics of centrality and community to enhance delivery performance. [PERSON] et al. [6] propose SocialCast, a routing framework for publish-subscribe that exploits predictions based on the metrics of social interaction to identify the best information carriers. [PERSON] et al. [7] propose MaxProp, a protocol for effective routing of DTN messages. MaxProp is based on prioritizing both the schedule of packets transmitted to other peers and the schedule of packets to be dropped. MaxProp performs better than protocols that have access to an oracle that knows the schedule of meetings between peers. [PERSON] et al. [8] propose multiple-copy routing called Spay-and-Wait, which is highly scalable and retains good performance under a large range of scenarios. All the above works assume that nodes are cooperative to forward messages to each other, without considering the selfishness problem. [PERSON] et al. [9] analytically assesses the performance of the unrestricted and two-hop relay schemes when nodes behave selfishly in forwarding messages. The experimental results show that the performance decreases both with the number of selfish nodes and the intensity of their selfishness. [PERSON] et al. [11] investigate how the selfish behavior of nodes affects the performance of DTN multicast. This demonstrates that the selfishness increases the message transmission delay and cost. The existing incentive schemes to address the selfishness problem basically fall into three categories: reputation-based [18; 19; 20], barter-based [10; 21; 22], and credit-based [12; 13; 14; 15; 16]. [PERSON] et al. [18] propose a practical reputation-based incentive scheme, named PRI, to stimulate honest forwarding and discipline selfish behavior. In PRI, each node provides service of forwarding for honest nodes in advance, and excludes selfish nodes whose values are below a deterministic reputation threshold, to encourage nodes to cooperatively forward messages. To promote the selfish nodes to cooperatively forward messages, [PERSON] et al. [19] propose SUCCESS, a secure user-centric and social-aware reputation-based incentive scheme for DTNs, is proposed. Two concepts of self-check and community-check are defined for reputation evaluation and speeding up reputation establishment. To address the selfishness problem, [PERSON] et al. [20] propose a reputation-based incentive scheme to motivate participants to disseminate reliable data in a participatory sensing system, named RIDD, while minimizing the incentive cost for maintaining a sufficient number of reliable participants. Reputation-based schemes are vulnerable to the collusion attack, in which several nodes may collude with each other to get a better reputation by giving false praise. [PERSON] et al. [10] study the impact of selfish behavior and propose the use of pair-wise Tit-for-Tat (TFT) as an incentive mechanism for DTNs. In TFT, each node statistics the number of messages have been forwarded by others in each interval, and then forwards the corresponding number of messages to others in the next interval. For the node selfishness in opportunistic networks, [PERSON] et al.