Method for optimizing communication sessions in a kinematic sensor system

Astakhova T.N., Kolbanev M.O., Sovetov B.Ya. Method for optimizing communication sessions in a kinematic sensor system. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2026, vol. 26, no. 1, pp. 145–153 (in Russian). doi: 10.17586/2226-1494-2026-26-1-145-153

In the context of rapid development of the Internet of Things, energy-efficient mobile sensor networks with moving nodes are becoming increasingly relevant. This work considers a kinematic sensor system with a Control and Information Processing Center (CIPC) where mobile nodes transmit data in cyclically organized time slots. It is assumed that communication sessions during data transmission from mobile nodes to the CIPC are arranged cyclically. The transmission cycle is divided into equal time segments (time slots) such that each slot is dedicated to data transfer from a specific mobile node to the CIPC. A method is proposed for constructing an optimal schedule for node-CIPC interactions based on the criterion of the system total energy consumption. The method enables the CIPC, at each new cycle, to select an order of slot distribution among nodes that ensures minimal energy expenditure. The proposed method optimizes the schedule of communication sessions to minimize the overall energy consumption of the system. It integrates a kinematic model of node movement based on Dubins differential equations, a radio physics model of signal propagation (Friis formula), and an assignment problem for scheduling. Developed are: an energy consumption model considering predicted distances to the CIPC based on Dubins trajectories; an algorithm for constructing the optimal data transmission schedule; and a software implementation of the method. Numerical experiments with a network of 10 nodes demonstrated a reduction in total energy consumption by 29.8 % compared to uniform slot allocation. The proposed approach complements existing research in mobile sensor networks where, as a rule, realistic kinematic constraints are either not considered or global schedule optimization is absent. The method is especially effective in scenarios with controlled mobility (drones, ground robots, autonomous platforms).

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