FiFo: Fishbone Forwarding in Massive IoT Networks

TL;DR

FiFo introduces a novel forwarding method for massive IoT networks that enhances data dissemination efficiency by clustering devices and optimizing forwarding paths, outperforming existing algorithms in real-world and simulated scenarios.

Contribution

The paper proposes FiFo, a new forwarding technique that improves efficiency in IoT networks by combining clustering, Gaussian mixture modeling, and principal component analysis.

Findings

FiFo outperforms benchmark algorithms in forwarding efficiency.

FiFo effectively clusters devices for optimized data dissemination.

Real-world data validates FiFo's superior performance.

Abstract

Massive Internet of Things (IoT) networks have a wide range of applications, including but not limited to the rapid delivery of emergency and disaster messages. Although various benchmark algorithms have been developed to date for message delivery in such applications, they pose several practical challenges such as insufficient network coverage and/or highly redundant transmissions to expand the coverage area, resulting in considerable energy consumption for each IoT device. To overcome this problem, we first characterize a new performance metric, forwarding efficiency, which is defined as the ratio of the coverage probability to the average number of transmissions per device, to evaluate the data dissemination performance more appropriately. Then, we propose a novel and effective forwarding method, fishbone forwarding (FiFo), which aims to improve the forwarding efficiency with acceptable computational complexity. Our FiFo method completes two tasks: 1) it clusters devices based on the unweighted pair group method with the arithmetic average; and 2) it creates the main axis and sub axes of each cluster using both the expectation-maximization algorithm for the Gaussian mixture model and principal component analysis. We demonstrate the superiority of FiFo by using a real-world dataset. Through intensive and comprehensive simulations, we show that the proposed FiFo method outperforms benchmark algorithms in terms of the forwarding efficiency.