Selfish Node Detection by Modularized Deep NMF Autoencoder Based Incentivized Reputation Scheme

Delay tolerant network is a boon in emergency fields like flood and war zones. The data gathered by the sensor nodes is transmitted whenever any aggregator node comes in contact with those stationary sensor nodes. However, few nodes can behave differently and don't transmit the information. These nodes which don't take part in communication to preserve it's battery or are compromised are selfish nodes and have to be identified to avoid communication disruption. This article discusses the selfish node's detection schemes and proposes a novel hybrid scheme. Most of the recent schemes work with on node's reputation or incentives if it takes part in communication. This paper has proposed an incentivized reputation scheme that first clusters the nodes using their social features, calculates the weighted social tie as their social connection strength and updates the weighted social tie by applying reward or penalty. The incentive is offered if residual energy and packet delay has a tradeoff or are penalized. A new modularized deep nonnegative matrix deep autoencoder is developed to calculate the reputation of nodes using social features and named IRU-mDANMF (incentivized reputation update by modularized DANMF). The scheme has been experimented with in several scenarios and is performing significantly better than state-of-the-art schemes.

Automated summary

This article discusses the detection schemes for selfish nodes in delay tolerant networks and proposes a novel hybrid scheme. The scheme clusters nodes based on their social features and updates reputation through reward or penalty. Experimental results show that the proposed scheme performs significantly better than existing schemes.