Multi-object optimized deployment method for industrial wireless sensor network

Abstract

The invention discloses a multi-object optimized deployment method for an industrial wireless sensor network, comprising the following steps: (1) dividing a monitoring region into three-dimensional grids, and arranging sensor nodes, cluster heads and base stations on cross points of the grids; (2) generating obstacle matrixes; (3) representing harmony individuals; (4) setting algorithm control parameters; (5) setting communication radiuses of the sensor and the cluster heads; (6) judging whether the communication between the sensor nodes and the cluster heads satisfies the conditions; (7) judging whether the hop number of communication between the sensor nodes and the base stations satisfies the conditions; (8) initializing harmony matrixes by using a heuristic strategy; (9) calculating an objective function value of each harmony; (10) finding out the optimized harmony; (11) generating a new harmony; (12) comparing the quality of the new harmony with the quality of the corresponding harmony in a harmony memory vault; (13) updating the optimized harmony; and (14) judging whether the stopping conditions are satisfied or not. The method can realize multi-object optimization for system reliability, and real-time performance, sensor node deployment cost and maintenance cost of the industrial wireless sensor network, and can satisfy the industrial actual requirements.

Description

A multi-objective optimal deployment method for industrial wireless sensor networks technical field The invention relates to two major fields of industrial wireless sensor networks and intelligent computing, in particular to a method for multi-target optimal deployment of industrial wireless sensor networks. Background technique As industrial systems continue to become larger and more complex, the scale of industrial control systems continues to expand, and their installation and wiring costs are also increasing. According to statistics, the market share of industrial sensors in 2001 was 11 billion US dollars, and its installation and use costs (mainly wiring costs) exceeded 100 billion US dollars. Therefore, the low cost and ease of use of Wireless Sensor Networks (WSNs) have attracted widespread attention in the industry. Internationally renowned control system companies, such as Emerson, Honeywell, and General Electric, have launched industrial wireless Research and de...

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Problems solved by technology

However, the basic HS algorithm uses real numbers or discrete coding, and is mainly used for optimization problems in continuous space and discrete space. For IWSNs layout optimization problems and binary coding optimization problems, the basic harmony search algorithm pitch adjustment operation will degenerate and fail. Therefore, the basic HS algorithm is not suitable for binary coded optimization problems

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