Leach (low energy adaptive clustering hierarchy) algorithm is a self-clustering topology algorithm. Its execution process is cyclical.\nEach cycle is divided into two phases: cluster building phase and stable data communication phase. In the stage of cluster building,\nthe adjacent nodes cluster dynamically and randomly generate cluster heads. In the data communication phase, the nodes in the\ncluster send the data to the cluster head, and the cluster head performs data fusion and sends the results to the aggregation node.\nBecause the cluster head needs to complete data fusion, communication with the convergence node and other works, the energy\nconsumption is large. Leach algorithm can ensure that each node acts as cluster head with equal probability, so that the nodes in\nthe network consume energy relatively evenly. The basic idea of Leach algorithm is to randomly select cluster head nodes in a\ncircular way. It evenly distributes the energy load of the whole network to each sensor node in the network. It can reduce network\nenergy consumption and improve network life cycle. Leach repeatedly performs cluster refactoring during its operation. This\npaper studies the parameter detection of wireless sensor network based on Leach algorithm on the on-chip embedded debugging\nsystem. Because the classical low-power adaptive clustering layered protocol (Leach) has the problem of energy imbalance and\nshort node life cycle, this paper uses embedded debugging technology based on Leach algorithm and the residual energy and\nposition of nodes in wireless sensor networks were tested for research. This Leach algorithm uses the concept of wheel. Each round\nconsists of two phases: initialization and stabilization. In the initialization stage, each node generates a random number between 0\nand 1. If the random number generated by a node is less than the set threshold T (n), the node publishes a message that it is a\ncluster head. Through the research on the parameter detection, the simulation results show that the research in this paper has good\nfeasibility and rationality.
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