Nowadays the technical solutions related to energy resource management are being rapidly developed and integrated into the daily lives of people. The energy resource management systems use sensor networks for receiving and processing information during the realia time. Despite the large number of research related to increasing the life expectancy of a network, node positioning, network clustering as well as the optimization of the data-processing model, issues related to the data flow management and classification of the information become more and more topical; they allow to reduce the amount of transmitted information within the network. The network load of the unstructured information flow is the most important aspect that impacts the service quality of the network as well as the life expectancy of a node; as a result, the methods of network performance optimization and increase in life expectancy in the networks with a high information transmission rate become ineffective. Nowadays the amount of transmitted information in the Internet of Things networks is increased and becomes chaotic which results in the reduction of the overall network efficiency and life expectancy. The article discusses the management method of the network data flow that can respond to a data flow programming task whilst taking into account the balancing of the node energy in the network
