Efficient micro data centres deployment for mobile healthcare monitoring systems in IoT urban scenarios

TL;DR

This paper presents a modeling and simulation approach to optimize micro data center deployment for mobile healthcare IoT systems in urban environments, aiming to reduce power consumption and improve infrastructure efficiency.

Contribution

It introduces a novel simulation methodology to analyze power consumption of MDCs in healthcare IoT scenarios within urban settings.

Findings

Different MDC configurations impact power consumption significantly

Urban infrastructure layout influences data center efficiency

Simulation results guide optimal deployment strategies

Abstract

In the last decade, the Internet of Things paradigm has caused an exponential increase in the number of connected devices. This trend brings the Internet closer to everyday activities and enables data collection that can be used to create and improve a great variety of services and applications. Despite its great benefits, this paradigm also comes with several challenges. More powerful storage and processing capabilities are required to service all these devices. Additionally, the need to deploy and manage the infrastructure to efficiently support these resources continues to pose a challenge. Modeling and simulation can help to design and analyze these scenarios, providing flexible and powerful mechanisms to study and compare different strategies and infrastructures. In this scenario, Micro Data Centers (MDCs) can be used as an effective way of reducing overwhelmed Cloud Data Center infrastructures. This paper explores an M\&S methodology to study the overall power consumption of a healthcare IoT scenario. The patients wear non-intrusive monitoring devices that periodically generate tasks to be executed in MDCs. We extract the layout of existing urban infrastructures, simulate the monitored population's behavior, and compare the power consumption of several data center configurations.