Big data services drive mobile crowd embedded opportunistic control mechanism for biological engineering

Abstract

Big data of biological engineering and mobile control increase the complexity of system control. In order to resolve the above problems and improve biological engineering system performance, this paper proposes a large data-driven and mobile crowd embedded opportunistic control mechanism. First of all, the measurement model of established big data-driven biological embedded engineering was proposed based on the research of biological engineering with non-linear and unpredictability. Based on the characteristics of the mobile crowd terminal perception outside interference, we proposed the mobile crowd biological engineering optimization opportunities control mechanism. The experimental results show that the established control mechanism in a long-term, large-scale performance still has high performance and high temperature. In addition, under different pressure, the rate of convergence of the scheme established is superior to the biological engineering control scheme based on coordination control.