Page 9 - ITU Journal Future and evolving technologies Volume 2 (2021), Issue 5 – Internet of Everything

ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 5

LIST OF ABSTRACTS
Federated learning for IoE environments: A service provider revenue

maximization framework

Pages 1-12
Benedetta Picano, Romano Fantacci, Tommaso Pecorella, Adnan Rashid
In accordance with the Internet of Everything (IoE) paradigm, millions of people and billions of devices
are expected to be connected to each other, giving rise to an ever increasing demand for application
services with a strict quality of service requirements. Therefore, service providers are dealing with the
functional integration of the classical cloud computing architecture with edge computing networks.
However, the intrinsic limited capacity of the edge computing nodes implies the need for proper virtual
functions' allocations to improve user satisfaction and service fulfillment. In this sense, demand
prediction is crucial in services management and exploitation. The main challenge here consists of the
high variability of application requests that result in inaccurate forecasts. Federated learning has
recently emerged as a solution to train mathematical learning models on the users' site. This paper
investigates the application of federated learning to virtual functions demand prediction in IoE based
edge cloud computing systems, to preserve the data security and maximise service provider revenue.
Additionally, the paper proposes a virtual function placement based on the services demand prediction
provided by the federated learning module. A matching based tasks allocation is proposed. Finally,
numerical results validate the proposed approach, compared with a chaos theory prediction scheme.
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IoE: Towards application-specific technology selection

Pages 13-27
Biswajit Paul, Gokul Chandra Biswas, Habib F. Rashvand
Determining the suitability of any technology for an Internet of Everything (IoE) application is essential
in the presence of diverse technologies and application requirements. Some of the IoE applications
include smart metering, wearables, healthcare, remote monitoring, inventory management and
industrial automation. Energy efficiency, scalability, security, low-cost deployment and network
coverage are some of the requirements that vary from one application to another. Wireless technologies
such as WiFi, ZigBee, Bluetooth, LTE, NB-IoT, LoRa and SigFox will play crucial roles in enabling
these applications. Some of the technological features are transmission range, bandwidth, data rate,
security schemes and infrastructure requirements. As there is no one-size-fits-all network solution
available, the key is to understand the diverse requirements of different IoE applications and specific
features offered by different IoE enabling technologies. Application-specific technology selection will
ensure the best possible utilization of any technology and the quality of service requirements. An
overview of network performance expectations from various IoE applications and enabling
technologies, their features and potential applications are presented in this paper.

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