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Scientific data management is at a critical juncture, driven by exponential data growth, increasing cross-domain dependencies, and a severe reproducibility crisis in modern research. Traditional centralized data management approaches are…
Data is the key to success for any Data-Driven Organization, and managing it is considered the most challenging task. Data Architecture (DA) focuses on describing, collecting, storing, processing, and analyzing the data to meet business…
FIR filters are used in many performance/power critical applications such as mobile communication devices, analogue to digital converters and digital signal processing applications. Design of appropriate FIR filters usually causes the order…
Today the cloud plays a central role in storing, processing, and distributing data. Despite contributing to the rapid development of IoT applications, the current IoT cloud-centric architecture has led into a myriad of isolated data silos…
In many open environment applications, data are collected in the form of a stream, which exhibits an evolving distribution over time. How to design algorithms to track these evolving data distributions with provable guarantees, particularly…
Crater detection can provide valuable information for humans to explore the topography and understand the history of extraterrestrial planets. Due to the significantly varying scenario distributions, existing detection models trained on…
As organizations struggle with processing vast amounts of information, outsourcing sensitive data to third parties becomes a necessity. To protect the data, various cryptographic techniques are used in outsourced database systems to ensure…
Conditions Data in high energy physics experiments is frequently seen as every data needed for reconstruction besides the event data itself. This includes all sorts of slowly evolving data like detector alignment, calibration and…
Most generic performance tools display only system-level performance data using 2-dimensional plots or diagrams and this limits the informational detail that can be displayed. Moreover, a modern relational database system, like Oracle, can…
An extensible, component-based framework has been developed at Fermilab to promote software reuse and provide a common platform for developing a family of test and data analysis systems. The framework allows for configuring applications…
One of the purposes of Big Data systems is to support analysis of data gathered from heterogeneous data sources. Since data warehouses have been used for several decades to achieve the same goal, they could be leveraged also to provide…
Data is found everywhere, from health and human infrastructure to the surge of sensors and the proliferation of internet-connected devices. To meet this challenge, the data engineering field has expanded significantly in recent years in…
In the last three years, the architecture of Frascati Tokamak Upgrade (FTU) experimental database has undergone meaningful modifications, data and codes have been moved from mainframe to UNIX platforms and AFS (Andrew File System) has been…
Recently, a new generation of P2P systems capable of addressing data integrity and authenticity has emerged for the development of new applications for a "more" decentralized Internet, i.e., Distributed Ledger Technologies (DLT) and…
Today's international corporations such as BASF, a leading company in the crop protection industry, produce and consume more and more data that are often fragmented and accessible through Web APIs. In addition, part of the proprietary and…
Flexible manufacturing has given rise to complex scheduling problems such as the flexible job shop scheduling problem (FJSP). In FJSP, operations can be processed on multiple machines, leading to intricate relationships between operations…
Up until recently, relational databases were considered as the de-facto technology for persisting and managing large volumes of data. This came to change with the emergence of enterprises producing extremely large datasets and having…
Rapid growth of datacenter (DC) scale, urgency of cost control, increasing workload diversity, and huge software investment protection place unprecedented demands on the operating system (OS) efficiency, scalability, performance isolation,…
Modern storage systems, often deployed to support multiple tenants in the cloud, must provide performance isolation. Unfortunately, traditional approaches such as fair sharing do not provide performance isolation for storage systems,…
One of the challenges currently problems in the use of cloud services is the task of designing of specialized data management systems. This is especially important for hybrid systems in which the data are located in public and private…