Robust Gossiping for Distributed Average Consensus in IoT Environments

Abstract

As communication technologies have enlarged the set of devices with networking capabilities, a new conception of the Internet of Things (IoT) is emerging. The incorporation of devices with advanced diagnosis and actuating capabilities to the IoT provides an appealing environment to control external processes using its sensing, actuating, and computational power, yet it difficults the operation. In this setting, consensus algorithms are an interesting alternative to support the operation of the IoT and to enable its potential as a distributed control network. Although consensus algorithms are mature well studied strategies that naturally adjust to networks, their performance deteriorates when faced with phenomena such as stochastic delays, sequential transmissions and receptions, and unreliability in the information exchanging process; all pervasive in an IoT environment. In this work, an algorithm for achieving average consensus over an IoT environment is presented and evaluated in an IoT testbed. The proposed algorithm is inspired by gossips, yet it is deadlock-free by design, and shows convergence to the average in all cases.