Gennady P. Vinogradov

Research Institute of Centerprogramssystems

Relevance. Wireless sensor networks (BSN) due to such characteristics as low energy consumption by nodes, low cost, self-organization, distribution and small size, the ability to determine the location of events have been applied in various fields. The increase in the amount of information transmitted to the BSS has created a number of problems that have become the focus of research in the field of wireless sensor networks. They are aimed at finding ways to expand the functionality of network nodes, especially when used in environments characterized by uncertainty. The main ones are: the network node must be capable of pre-processing information, including clustering, aggregation and merging of heterogeneous data, studying the situation and making decisions, both independently and as part of a group, taking into account the data received from other network nodes. In addition, the node management system must perform distributed processing of complex requests within the network and routing with optimized energy consumption. The implementation of these requirements is possible by improving the intellectual component of the management system of both the network as a whole and an individual node in particular. The purpose of the work. Development of methods that extend the functionality of a wireless sensor network node control system based on fuzzy logic inference and pattern theory. Main results: Due to the complexity of structuring and mathematically describing the behavior of the environment in the node's control area, it is proposed to use effective patterns of response to changes in its state. For this purpose, linguistic variables and fuzzy production rules are introduced in information models of the environment. This approach made it possible to ensure a relevant correlation of the coordinate vector of the situation with a particular response pattern and reduce the amount of calculations. The rules contain references to primary data processing tasks and response procedures by means of an autonomous network node. It is proposed to use meta-guidelines to update the rule base. Meta-guidelines define the parameters of membership functions and the rules of inference when calculating attribute values. This made it possible to supplement data transfer with the transfer of knowledge required for the necessary configuration of the parameters of the algorithms of local nodes. With this approach, the network node has knowledge about itself and the environment, and becomes capable of independent decision-making as part of a group. To increase the robustness of data processing algorithms in nodes, it is proposed to use the concept of a "typical situation". As an example, the paper shows the use of the proposed approach in the tasks of integrating data from several sensors of a node and detecting an intrusion object.

model, fuzzy logic, pattern, wireless network, sensor