Efficient service request detection algorithm based on hormone regulation mechanism in the Internet of things

Abstract

With the raising challenges of the Internet of things (IoT), e.g. the giant-scale heterogeneous network elements, and the uncertainty of sensing information and the dynamic environment that the system resides, there is no complete and widely accepted theory. In this paper, a hormone-based service detection algorithm (HSDA) for detecting the service requests generated randomly in the IoT is proposed. Inspired by the endocrine mechanism in human body, the nodes in the network without centralized command or sinks can tune themselves spontaneously by exchanging information among regional neighbors through different hormones. A dynamic activation scheme is realized as the HSDA to guarantee the rapidness of the network on responding the service requests. Simulation results show that the HSDA algorithm entitles the network with intelligent decision-making and cooperative working abilities, based on which the stability of the network and the effectiveness for detecting service requests generated randomly can be guaranteed simultaneously.