Different InterCriteria Analysis of Variants of ACO algorithm for Wireless Sensor Network Positioning

Wireless sensor networks are formed by spatially distributed sensors, which communicate in a wireless way. This network can monitor various kinds of environment and physical conditions like movement, noise, light, humidity, images, chemical substances etc. A given area needs to be fully covered with minimal number of sensors and the energy consumption of the network needs to be minimal too. We propose several algorithms, based on Ant Colony Optimization, to solve the problem. We study the algorithms behavior when the number of ants varies from 1 to 10. We apply InterCriteria analysis to study relations between proposed algorithms and number of ants and analyse correlation between them. Four different algorithms of ICrA—\(\mu \)-biased, Balanced, \(\nu \)-biased and Unbiased—are applied. The obtained results are discussed in order to find the stronger correlations between considered hybrid ACO algorithms.