Node Discovery and Interpretation in Unstructured Resource-Constrained Environments

A main characteristic of the Internet of Thingsnetworks is the large number of resource-constrained nodes,which, however, are required to perform reliable and fast dataexchange; often of critical nature; over highly unpredictableand dynamic connections and network topologies. Reducingthe number of message exchanges and retransmission of data,while guaranteeing the lifetime of the data session duration asper service requirements are vital for enabling scenarios suchas smart home, intelligent transportation systems, eHealth, etc.This paper proposes a novel theoretical model for thediscovery, linking and interpretation of nodes in unstructuredand resource-constrained network environments and theirinterrelated and collective use for the delivery of smartservices. The model is based on a basic mathematicalapproach, which describes and predicts the success of humaninteractions in the context of long-term relationships andidentifies several key variables in the context ofcommunications in resource-constrained environments. Thegeneral theoretical model is described and several algorithmsare proposed as part of the node discovery, identification, andlinking processes in relation to the key variables. Thealgorithms are each evaluated by simulations to determinewhich parameters are key for optimal node grouping