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Unlocked vs. Prepaid Phones: Making the Right Choice - Vimarsana News

Unlocked vs. Prepaid Phones: Making the Right Choice

Choosing a new mobile phone is not just about the device itself but also about the service plan that goes with it. Two common options are unlocked phones and prepaid phones, each with its unique benefits and considerations. In this guide, we'll compare unlocked and prepaid phones to help you make the right choice for your mobile needs. Unlocked Phones: A Closer Look Advantages of Unlocked Phones Network Freedom: Unlocked phones can be used with any compatible carrier, providing flexibility to switch carriers without changing your device.Cost Savings: While unlocked phones often have a hig...

"A Comprehensive Overview of IoT-Based Federated Learning: Focusing on " by Naghmeh Khajehali, Jun Yan et al. - Vimarsana News

"A Comprehensive Overview of IoT-Based Federated Learning: Focusing on " by Naghmeh Khajehali, Jun Yan et al.

The integration of the Internet of Things (IoT) with machine learning (ML) is revolutionizing how services and applications impact our daily lives. In traditional ML methods, data are collected and processed centrally. However, modern IoT networks face challenges in implementing this approach due to their vast amount of data and privacy concerns. To overcome these issues, federated learning (FL) has emerged as a solution. FL allows ML methods to achieve collaborative training by transferring model parameters instead of client data. One of the significant challenges of federated learning is tha...

Source: uow.edu.au
"Data Collection and Information Freshness in Energy Harvesting Network" by Lei Zhang - Vimarsana News

"Data Collection and Information Freshness in Energy Harvesting Network" by Lei Zhang

An Internet of Things (IoT) network consists of multiple devices with sensor(s), and one or more access points or gateways. These devices monitor and sample targets, such as valuable assets, before transmitting their samples to an access point or the cloud for storage or/and analysis. A critical issue is that devices have limited energy, which constrains their operational lifetime. To this end, researchers have proposed various solutions to extend the lifetime of devices. A popular solution involves optimizing the duty cycle of devices; equivalently, the ratio of their active and inactive/slee...

Source: uow.edu.au
"On Devices Selection in RF-Energy Harvesting Wireless Networks" by Lei Zhang and Kwan Wu Chin - Vimarsana News

"On Devices Selection in RF-Energy Harvesting Wireless Networks" by Lei Zhang and Kwan Wu Chin

In this article, we consider a network with a hybrid access point (HAP) and radio frequency (RF)-energy harvesting wireless devices. The HAP is responsible for charging these devices and receiving their data. Our problem is to select a set of devices to transmit in each time slot so as to maximize a given reward over a planning horizon. In contrast to prior works, we consider the challenging case whereby the HAP has imperfect channel state information (CSI) nor information about the battery state of devices. We also consider nonlinear RF-energy conversion rates and battery leakage. We propose ...

Source: uow.edu.au
"A Distributed Device Selection Method to Minimize AoI in RF-Charging N" by Lei Zhang and Kwan Wu Chin - Vimarsana News

"A Distributed Device Selection Method to Minimize AoI in RF-Charging N" by Lei Zhang and Kwan Wu Chin

This letter considers optimizing information freshness in a network with Radio Frequency (RF)-energy harvesting wireless devices. A Hybrid Access Point (HAP) charges these devices and instructs a subset of devices to carry out sampling and transmit their sample. We outline a Distributed Q-Learning (DQL) algorithm that allows the HAP to select devices without knowing their uplink channel state and battery state. Our results show that DQL achieves at most 48%, 57%, and 61% lower average AoI than Round Robin (RR), Random Pick (RP), and AoI-Greedy (AG), respectively. The average AoI of DQL is only...

Source: uow.edu.au