Conditional Probabilistic Coefficient based Selfish Node Identification in Cyber Physical Systems

In Cyber Physical System (CPS), reputation based trust management has gained an important role in data distribution for the maximum cooperation in the sensor nodes. But, the presence of selfish nodes in such environment decreases the coordination between the nodes and decrease the lifetime of the cyber physical system network, the throughput and packet delivery ratio get decreased mainly because of retransmissions. In order to increase the throughput and delivery ratio of packets, an efficient and flexible mechanism for isolating the selfish node becomes essential. This paper proposes a Conditional Probabilistic Coefficient Model (CPCM) helps in isolating selfish nodes and makes the CPS network robust. This CPCM assists in estimating the negative impact produced by the selfish nodes towards network resilience. This study has been simulated in NS-2, where CPCM showed improved results by comparing control overheads, throughput, delivery rate of packet and total overheads, than the existing minimization mechanisms like TRMF-CPS [13], MTF-WSN [16], and FPDM [11] proposed for selfish nodes.