A Heuristic Algorithm Based Task Assignment Method for Wireless Sensor Networks

Abstract

The present invention relates to a wireless sensor network task allocation method based on a heuristic algorithm, comprising the following steps: loading a task model and a wireless sensor network, obtaining the task quantity in the task model and the sensor nodes in the wireless sensor network, for subsequent chromosome Coding; population initialization: each chromosome in the population corresponds to a task allocation scheme, the length of the chromosome is the number of tasks in the task model, and the element stored in the node is the sensor node in the network model, that is, the i-th node of the chromosome stores the sensor node A, On behalf of scheduling sensor node A to perform task i; perform 3-1 crossover operation on individuals in the population; perform mutation operation; calculate the fitness value of individuals in the population and perform selection operation; update pheromone concentration; output the optimal solution.

Description

technical field [0001] The invention belongs to the field of Internet of things, and relates to a wireless sensor network task allocation method based on a heuristic algorithm. Background technique [0002] A sensor network consists of a large number of small, energy-constrained sensor nodes with computing and wireless communication capabilities. These sensor nodes can sense information from the environment, process the sensed data and transmit it to other devices in the network. Sensor networks are currently widely used in fields including environmental monitoring, object tracking, forest fire prevention, and battlefield situation monitoring. Therefore, sensor networks have received more and more research and attention from both scientific and industrial circles. Deployment of wireless sensor networks is usually to complete a complex task, in order to complete the task, wireless sensor networks need to consume a lot of energy to collect information, process data and dissem...

AI Technical Summary

Problems solved by technology

The heuristic algorithm can ensure that the optimal solution of the problem is found according to the given constraints in small-scale scenarios, but the heuristic algorithm in large-scale scenarios converges slowly and is also prone to premature convergence, and cannot guarantee that the obtained solution is the global optimal solution , if you want to improve the quality of the solution, you need to expand the search space of the algorithm, which makes the convergence speed slower and greatly reduces the efficiency of the algorithm

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