Internet of Things (IOT) Clustered Recursive Routing Chain Architecture for Low Latency Diffusion: New prospects for Nigeria Health care system

Abstract

In this paper, a novel Recursive Edge-Cloud Orchestration Infrastructure is investigated. The System characterization for
recursive Routing Network (RRN) architecture using computational modeling is achieved. Bayesian Machine learning technique
is introduced for the IoT access control into the cloud. Established complexity-driven algorithms are derived for network
orchestration. The system leverages robust design architecture, and availability data center model for end-to-end services and
communication for service provisioning. To ensure service accessibility for each IoT device in a cluster, an unbiased uniform
estimator was computed for the data-center model. A computational service-oriented software modularization framework is
derived for IoT edge sensors. Simulation of the Cloud-Fog orchestration infrastructure is done using Riverbed Modeler V.17.5 to
determine the responsiveness of QoS metrics in a validation study. Simulation results reveal that the proposed offloading
optimization strategy built into Recursive routing network (RRN) architecture is resilient. With Restful-Application
Programmable Interface(R-API) and Recursive routing chain algorithm (RRCA), the proposed algorithm outperforms the other
selected model in terms of cost economy, throughput, latency, and utilization metrics. The work suggests that IoT edge sensing
and monitoring solutions infused on the device hardware can greatly improve service delivery and reduce maternal mortality
significantly in Nigeria.