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Federated learning (FL) enables collaborative model training over distributed computing nodes without sharing their privacy-sensitive raw data. However, in FL, iterative exchanges of model updates between distributed nodes and the cloud server can result ...

Federated learning enables distributed model training over various computing nodes, e.g., mobile devices, where instead of sharing raw user data, computing nodes can solely commit model updates without compromising data privacy. The quality of federated ...

Despite the significant development of mobile device SoCs, they are still inefficient in computing computation-intensive workloads, such as high-resolution image processing and AR/VR applications. Offloading offers a promising way to leverage cloud or ...

The emergency of federated learning (FL) enables distributed data owners to collaboratively build a global model without sharing their raw data, which creates a new business chance for building data market. However, in practical FL scenarios, the hardware ...

Age of information (AoI) has been proposed to quantify data freshness. In some real-time applications such as surveillance systems, real-time analytics on source updates requires intensive computation resources and incurs high energy consumption. By ...

Motivated by the popularity of edge intelligence, DNN services have been widely deployed at the edge, posing significant performance pressure on edge servers. How to improve the QoS of edge DNN services becomes a crucial and challenging problem. Previous ...

Federated learning enables distributed learning in a privacy-protected manner, but two challenging reasons can affect learning performance significantly. First, mobile users are not willing to participate in learning due to computation and energy ...

In cloud and edge networks, federated learning involves training statistical models over decentralized data, where servers aggregate models through intermediate updates trained from clients. By utilizing private and local data it improves quality of ...

Nowadays, multiple heterogeneous cellular networks coexist simultaneously, and mobile devices can freely select the appropriate network for data communication. Our measurement studies show that a barrier exists between heterogeneous cellular networks and ...

Massive trajectory data with spatio-temporal information are generated from various devices everyday. Due to a wide variety of devices and data collection methods, these data differ in terms of frequency and precision, which brings challenges to data ...

In this paper, we study a small-cell caching system consisting of one privately-owned small base station (SBS) and multiple content providers (CPs), where CPs leverage the caching capabilities of SBSs to efficiently provide content delivery service to ...

For transmitting a packet over a wireless link, the energy can be saved by decreasing the transmission rate, but the rate is restricted by the arrival time and deadline. This paper proposes unidirectional-valve (UDV) based scheduling for energy-...

High density use of (mostly gasoline or diesel fueled) cars has led to a number of environmental and social problems in urban environments. Towards addressing these challenges, shifting urban transportation modes from private cars to other more ...

With the emergence of cloud computing, big data, and mobile networks, the computing paradigm and related technologies have experienced significant development over the past 10 years. Concomitantly, the prevalence of smartphones, wearable devices, and ...

Service delivery is becoming a hot topic in transparent computing (TC). However, transfers in TC lack adequate support for applications with nonresident content and lower-latency requirements. In this article, the authors analyze the quantitative ...

The growing demand on the performance of transparent computing systems requires good cache schemes in order to overcome the prolonged network latency. However, evaluating cache schemes, especially measuring the performance of a transparent computing ...

Mobile online social networks (OSNs) are emerging as the popular mainstream platform for information and content sharing among people. In order to provide Quality of Experience (QoE) support for mobile OSN services, in this paper we propose a socially-...

Transparent computing TC provides a large number of intelligent information services. Recommendation can help users rapidly locate their desired content. Collaborative filtering CF is a suitable recommending technology for TC, but data sparsity and ...

This study proposes a unidirectional‐valve (UDV) algorithm for energy‐efficient transmission, where the packets arrived at different times must be transmitted before a common deadline. The UDV algorithm divides the total transmission time into a series ...

This paper proposes an algorithm of delay-based weighted proportional fair (DBWPF) for downlink packet scheduling in the long term evolution cellular networks. Besides the tradeoff between throughput and throughput fairness, which is the target of the ...