ali nouruzi

Code of Paper: VoI-Guaranteed Task Computing for Massive IoT under Demand and Resource Uncertainties

Abstract—In massive Internet of Things (IoT) deployments,

the efficient allocation of computing resources to IoT devices

while preserving devices’ data poses a significant challenge.

This paper proposes a new online probabilistic model to address

uncertainties in demand and resource allocation for IoT

networks, where the task computing of requesting devices is

addressed by serving devices. The model incorporates uncertainty

and formulates an optimization problem, concerning available

Categories:

AI-based Online VoI-Aware Healthcare and Medical Monitoring Task Computing

Abstract—In recent years, there has been a significant advancement

in the field of healthcare systems with the introduction

of fifth generation cellular communications and beyond (5GB).

This development has paved the way for the utilization of

telecommunications technologies in healthcare systems with an

level of certainty, reaching up to 99.999 percent. In this paper,

we present a novel task computing framework that can address

the requirements of healthcare systems, such as reliability. In

Categories:

CODES OF PAPER: AI-based E2E Resilient and Proactive Resource Management in Slice-enabled 6G Networks

Intelligence and flexibility are the two main requirements for next-generation networks that can be implemented in network slicing (NetS) technology.This intelligence and flexibility can have different indicators in networks, such as proactivity and resilience. In this paper, we propose a novel proactive end-to-end (E2E) resource management in a packet-based model, supporting NetS.

Categories:

Code of Paper: Smart Economic and Mobility Aware Cooperation for Resource Sharing in Multi-Tier Edge Slicing

In this paper, we propose a novel cooperative resource sharing in a multi-tier edge slicing networks which is

robust to imperfect channel state information (CSI) caused by user equipments’ (UEs) mobility. Due to the mobility

of UEs, the dynamic requirements of their tasks, and the limited resources of the network, we propose a smart joint

dynamic pricing and resources sharing (SJDPRS) scenario that can incentivize the infrastructure provider (InP) and

mobile network operators (MNOs). Aiming to maximize the profits of UEs, MNOs and the InP under the task

Categories:

Codes of paper: AI-based Resource Allocation in End-to-End Network Slicing under Demand and CSI Uncertainties

Abstract—Network slicing (NwS) is one of the main technologies

in the h-generation of mobile communication and

beyond (5G+). One of the important challenges in the NwS

is information uncertainty which mainly involves demand

and channel state information (CSI). Demand uncertainty is

divided into three types: number of users requests, amount

of bandwidth, and requested virtual network functions workloads.

Moreover, the CSI uncertainty is modeled by three

methods: worst-case, probabilistic, and hybrid. In this paper,

Categories:

Dataset Entries from this Author