A Bio-Inspired Service Discovery and Selection Approach for IoT Applications

Abstract

Traditional service discovery and selection approaches which rely mostly on centralized architectures, have been proven inadequate in the pervasive environment of the Internet of Things (IoT). In such settings, where decentralization of decision-making is mandatory, bio-inspired computing paradigms have emerged due to their inherent capability to operate without any central control. In this paper, taking inspiration from the widely studied bio-inspired Response Threshold Model, a decentralized service discovery and selection model is proposed. Preliminary results indicate that the proposed approach exhibits efficient scalability and routing performance.