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In the financial field of the United States, the application of big data technology has become one of the important means for financial institutions to enhance competitiveness and reduce risks. The core objective of this article is to…
On the rise of distributed computing technologies, video big data analytics in the cloud have attracted researchers and practitioners' attention. The current technology and market trends demand an efficient framework for video big data…
Enterprises in their journey to the cloud, want to decompose their monolith applications into microservices to maximize cloud benefits. Current research focuses a lot on how to partition the monolith into smaller clusters that perform well…
Performance analysis of microservices can be a challenging task, as a typical request to these systems involves multiple Remote Procedure Calls (RPC) spanning across independent services and machines. Practitioners primarily rely on…
Microservices have transformed software architecture through the creation of modular and independent services. However, they introduce operational complexities in service integration and system management that makes swift and accurate…
Over the last two decades, the field of computational science has seen a dramatic shift towards incorporating high-throughput computation and big-data analysis as fundamental pillars of the scientific discovery process. This has…
There is an increasing interest in the development of new data-driven models useful to assess the performance of communication networks. For many applications, like network monitoring and troubleshooting, a data model is of little use if it…
The ADS platform is undergoing the biggest rewrite of its 20-year history. While several components have been added to its architecture over the past couple of years, this talk will concentrate on the underpinnings of ADS's search layer and…
Microservices are quite widely impacting on the software industry in recent years. Rapid evolution and continuous deployment represent specific benefits of microservice-based systems, but they may have a significant impact on non-functional…
Dataflow architectures are growing in popularity due to their potential to mitigate the challenges posed by the memory wall inherent to the Von Neumann architecture. At the same time, high-level synthesis (HLS) has demonstrated its efficacy…
Software as a service (SaaS) has recently enjoyed much attention as it makes the use of software more convenient and cost-effective. At the same time, the arising of users' expectation for high quality service such as real-time information…
Expectations regarding the future growth of Internet of Things (IoT)-related technologies are high. These expectations require the realization of a sustainable general purpose application framework that is capable to handle these kinds of…
Bayesian data analysis (BDA) is today used by a multitude of research disciplines. These disciplines use BDA as a way to embrace uncertainty by using multilevel models and making use of all available information at hand. In this chapter, we…
Machine Learning (ML) techniques have begun to dominate data analytics applications and services. Recommendation systems are a key component of online service providers. The financial industry has adopted ML to harness large volumes of data…
Functional data analysis (FDA) is a statistical framework that allows for the analysis of curves, images, or functions on higher dimensional domains. The goals of FDA, such as descriptive analyses, classification, and regression, are…
Online experiments using metaverse platforms have gained significant traction in Human-Computer Interaction and Virtual Reality (VR) research. However, current research workflows are highly fragmented, as researchers must use separate tools…
Materials science workflows rely on structured and unstructured data from the vast body of available scientific literature. However, most of the experimental details remain buried in text, tables, graphs and figures. Thus, constructing…
In recent past, big data opportunities have gained much momentum to enhance knowledge management in organizations. However, big data due to its various properties like high volume, variety, and velocity can no longer be effectively stored…
The microservice architecture allows developers to divide the core functionality of their software system into multiple smaller services. However, this architectural style also makes it harder for them to debug and assess whether the…
Model driven architecture (MDA) concentrates on the use of models during software development. An approach using models as the central development artifact is more abstract, more compact and thus more effective and probably also less error…