Related papers: A Novel approach for Hybrid Database
Homomorphic Encryption (HE) prevails in securing Federated Learning (FL), but suffers from high overhead and adaptation cost. Selective HE methods, which partially encrypt model parameters by a global mask, are expected to protect privacy…
This article presents the implementation process of a Data Warehouse and a multidimensional analysis of business data for a holding company in the financial sector. The goal is to create a business intelligence system that, in a simple,…
With the development of edge networks and mobile computing, the need to serve heterogeneous data sources at the network edge requires the design of new distributed machine learning mechanisms. As a prevalent approach, Federated Learning…
We present Project Florida, a system architecture and software development kit (SDK) enabling deployment of large-scale Federated Learning (FL) solutions across a heterogeneous device ecosystem. Federated learning is an approach to machine…
Mobile Edge Computing (MEC), which incorporates the Cloud, edge nodes and end devices, has shown great potential in bringing data processing closer to the data sources. Meanwhile, Federated learning (FL) has emerged as a promising…
Edge computing is emerging as a key enabler of low-latency, high-efficiency processing for the Internet of Things (IoT) and other real-time applications. To support these demands, containerization has gained traction in edge computing due…
Image classification is an enthusiastic research field where large amount of image data is classified into various classes based on their visual contents. Researchers have presented various low-level features-based techniques for…
The retrofitting of existing buildings with building management systems presents significant challenges, primarily due to the need for labor and cost efficiency. Wireless technology offers a promising solution to these challenges by…
Secure aggregation is commonly used in federated learning (FL) to alleviate privacy concerns related to the central aggregator seeing all parameter updates in the clear. Unfortunately, most existing secure aggregation schemes ignore two…
Sharding has emerged as a critical solution to address the scalability challenges faced by blockchain networks, enabling them to achieve higher transaction throughput, reduced latency, and optimized resource usage. This paper investigates…
A large amount of data and applications are migrated by researchers, stakeholders, academia, and business organizations to the cloud environment due to its large variety of services, which involve the least maintenance cost, maximum…
The growth in variety and volume of OLTP (Online Transaction Processing) applications poses a challenge to OLTP systems to meet performance and cost demands in the existing hardware landscape. These applications are highly interactive…
With the advent of the Internet-of-Things (IoT), handling large volumes of time-series data has become a growing concern. Data, generated from millions of Internet-connected sensors, will drive new IoT applications and services. A key…
The growing adoption of electric vehicles (EVs) is increasing peak demand in distribution systems, which can threaten grid stability and reduce operational efficiency. Dynamic electricity pricing is a promising means of mitigating these…
Federated Learning (FL) is a machine learning paradigm that safeguards privacy by retaining client data on edge devices. However, optimizing FL in practice can be challenging due to the diverse and heterogeneous nature of the learning…
Edge computing provides an agile data processing platform for latency-sensitive and communication-intensive applications through a decentralized cloud and geographically distributed edge nodes. Gaining centralized control over the edge…
Main memory database systems aim to provide users with low latency and high throughput access to data. Most data resides in secondary storage, which is limited by the access speed of the technology. For hot content, data resides in DRAM,…
This study aims to inspect and evaluate the integration of database queries and their use in e-commerce product searches. It has been observed that e-commerce is one of the most prominent trends, which have been emerged in the business…
The increasing adoption of Cloud storage poses a number of privacy issues. Users wish to preserve full control over their sensitive data and cannot accept that it to be accessible by the remote storage provider. Previous research was made…
In recent years, cloud database storage has become an inexpensive and convenient option for businesses and individuals to store information. While its positive aspects make the cloud extremely attractive for data storage, it is a relatively…