Wireless sensor network-based energy-efficient collaborative scheduling method

Abstract

The invention discloses a wireless sensor network-based energy-efficient collaborative scheduling method, which is characterized by comprising the following steps of: (1) initializing a target; (2) estimating a state; (3) selecting a sampling interval; (4) dynamically forming a next cluster; and (5) dynamically updating a cluster head, i.e., judging whether a moving target moves out of a monitoring region of a wireless sensor network, stopping tracking if the moving target moves out of the monitoring region of the wireless sensor network, otherwise transferring state estimation information of the cluster head at the current moment to a cluster head of a next moment by the cluster head, changing the cluster head of the next moment into a working cluster head and turning to the step (2). According to the wireless sensor network-based energy-efficient collaborative scheduling method, various performance indexes are considered, the performance indexes are optimized on line to select the cluster head, the cluster is dynamically generated and the sampling interval is adaptively determined, and accurate tracking of a target is realized through collaborative sensing and information fusion of a sensor node in the cluster. The wireless sensor network-based energy-efficient collaborative scheduling method has the advantages that communication energy is saved, energy distribution and calculation resources in a network are balanced, the life cycle of the network is prolonged, the reliability of the network is improved and the like.

Description

technical field [0001] The invention relates to a wireless sensor network resource scheduling algorithm, in particular to a wireless sensor network energy efficient cooperative scheduling method. Background technique [0002] Wireless sensor networks have the characteristics of large number of sensor nodes, small size, self-organization, rapid deployment, limited battery energy, and limited computing and communication resources. Through distributed information processing within the network and collaboration of local sensor nodes, wireless sensor networks are more flexible and effective than traditional centralized sensor node arrays. A challenging issue in wireless sensor network design is how to optimize system resource allocation under various resource constraints. In a dense network environment, a large amount of measurement information is redundant, how to select sensor nodes participating in sensing, balance information gain and energy resource consumption, in order to...

AI Technical Summary

Problems solved by technology

Among them, the scheduling method based on the minimum distance is simple and easy to use, and it is also easy to implement in the sensor node network, but it does not consider the requirements of energy consumption and tracking accuracy, and it is easy to generate error accumulation in the sensor nodes, thereby deteriorating the performance of the entire network; minimum The trace scheduling method is a scheduling method based on the prediction error covariance matrix trace, which essentially only considers the performance index of tracking accuracy and does not consider the constraint of energy consumption; the adaptive scheduling method uses the weighting of the two indicators of accuracy and energy as the cost function , using it as the basis for selecting the next task node, but in this method, only a single sensor node performs perception and data transmission at each moment, without considering the coordination between multiple sensor nodes that perceive the target

Due to the limitations of the sensing range and tracking accuracy of a single sensor node, the tracking performance for low signal-to-noise ratio and maneuvering targets is very poor, and when selecting task nodes, the energy balance consumption of each sensor node in the wireless sensor network is not considered.

The dynamic group scheduling method we applied for before considers the real-time requirements of target tracking, tracking accuracy, and the minimum energy of a single sensor node. Energy balance distribution across the network

[0004] Obviously, the above-mentioned scheduling algorithms have deficiencies; through the analysis of the characteristics of wireless sensor networks, it can be seen that to design a good scheduling algorithm, not only the prediction accuracy and energy consumption must be considered, but also the computing and communication resource constraints of the sensor nodes themselves, and Whether it can meet the needs of real-time tracking of the network and the energy balance requirements of the entire sensor network

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