A Method for Balancing Latency and Data Loss in High-Density Heterogeneous Internet of Things Networks

Problem statement. The growing number of devices in heterogeneous Internet of Things networks creates an additional load on limited radio resources, which complicates ensuring stability and quality of data transmission. Heterogeneous communication subchannels have different characteristics that require effective load balancing mechanisms. The development of methods to minimize data transmission delay and reduce the likelihood of packet loss is especially relevant for high-density Internet of Things networks, where resource management becomes critical. The aim of the work is to improve the efficiency of data transmission in a high-density heterogeneous Internet of Things network. Methods used. The work uses optimization methods, the gray wolf pack algorithm, queuing theory and probabilistic analysis. Novelty. The method proposed in the article takes into account the individual characteristics of subchannels and provides dynamic load distribution. This allows adapting the solution to different types of heterogeneous networks, reducing delay and data loss. Result. A mathematical model describing data transmission through several communication subchannels and an objective function combining the average data transmission delay and the probability of packet loss have been developed. Analytical expressions for key network characteristics, such as the probability of loss and average delay, have been derived. Practical significance. The developed model and method can be used in the design of devices and networks of high-density heterogeneous Internet of Things networks in order to improve their efficiency.