Abstract
The Internet of Things is used in many sectors for different applications in an efficient way. However, sharing huge data to distant destinations is a difficult task such as sending large data from remote area for healthcare application. So that the Delay Tolerant Network is used but, in some cases, the presence of selfish nodes in Delay Tolerant Network may drop all the packets. To overcome this problem the current research affords a novel African Buffalo Delay Tolerant Network with Risk Packet Jump (ABDTN –RPJ) mechanism to improve the communication channel by predicting the selfish and misbehavior node in an earlier stage. Besides, RPJ is introduced to split the huge data to the other neighboring nodes to reduce packet load on the node if the load is greater than the capacity of the node. Finally, the ABDTN –RPJ is implemented and evaluated using the NS2 simulator. The comparison results proved the efficiency of the proposed model by reducing the delay and drop rate.
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