## 1 Introduction and State-of-the-Art  
### Relevance of the Research  
The continued expansion of Internet of Things (IoT) traffic [1, 2, 3] is facilitated by the ongoing enhancement of the hardware links within sensor networks. Concurrently, the adoption of Edge computing ideology [4, 5, 6] serves to manage the intricacies of the \"first-mile\" segment (from the sensor array to the peripheral server). It is noteworthy to highlight that the increasing proportion of mass traffic originating from specific target sensors, which, in certain cases, surpasses the cumulative traffic of the entire sensor array (for instance, a single 4k camera in a city's video surveillance system generates more traffic than the entirety of the city's smart traffic lights). This observation underscores the necessity of introducing an additional link to the peripheral server to aggregate substantial traffic from these target sensors. The authors of this article have previously investigated, in [7; 8], the issue of the integration of a sensor network end IoT device (SNEIoT), developed on the reliable and cost-effective Raspberry Pi computing platform, as a viable solution to address this need. The incorporation of such a SNEIoTD aims to diminish the likelihood of information loss within the critical infrastructure of a smart city and enhance the adaptability of controlling massive traffic at the initial stage. Consequently, a pressing challenge in this context is the effective control of information transfer from the SNEIoTD environment to a hub, a task that the authors formalize based on the TCP. The endpoint in the studied system is a SNEIoTD, which aggregates information from sensors that generate massive traffic, and, as it accumulates, transmits it to the hub. The hub can be either a peripheral server or a cloud data storage itself. At the same time, an SNEIoTD is a significantly simpler computing device than a hub (which is why we mention Raspberry Pi in this context). It should be noted that the idea of using an SNEIoTD as an intermediate link was inspired by practice. While organizing the process of transferring information from 4k cameras of a city's video surveillance system, we were faced with multiple cases of information loss due to the unreliability of the 5G information transmission channel. After we introduced an additional link (the \"sensor network end IoT device\") into the \"4k camera array\"--\"hub\" system, we were able to solve the above problem (Figure 1). Let us explain in more detail why in this research we focus on the transport layer of the Open Systems Interconnection (OSI) model and the TCP. As we mentioned above, sensor networks are designed to collect critical information (for example, information from cameras of a city's video surveillance system). This information can characterize functioning industries, various processes in a smart city, and people's preferences. In each case mentioned, the loss of collected information can have extremely significant negative consequences, even catastrophic. In the context of the above, the issue of reliability in transferring information from the elements of the sensor array to the final point of its placement comes to the forefront. An OSI model's transport layer is developed to guarantee reliable data transmission from a sender to a recipient [9; 10; 11]. However, the degree of its reliability may exhibit significant fluctuations. There exist numerous transport-layer protocols [12; 13; 14], from protocols that solely offer fundamental transport capabilities (such as data transfer functions without acknowledgement) to protocols that guarantee the delivery of multiple data packets to a destination in the proper sequence. Multiplexing numerous data streams establishes a data flow control mechanism and ensures the reliability of the received data.