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As the amount of scientific data continues to grow at ever faster rates, the research community is increasingly in need of flexible computational infrastructure that can support the entirety of the data science lifecycle, including…

The proliferation of sensors over the last years has generated large amounts of raw data, forming data streams that need to be processed. In many cases, cloud resources are used for such processing, exploiting their flexibility, but these…

Modern DevOps practices have accelerated software delivery through automation, CI/CD pipelines, and observability tooling,but these approaches struggle to keep pace with the scale and dynamism of cloud-native systems. As telemetry volume…

A data commons brings together (or co-locates) data with cloud computing infrastructure and commonly used software services, tools and applications for managing, analyzing and sharing data to create an interoperable resource for a research…

Software and hardware co-design and optimization of HPC systems has become intolerably complex, ad-hoc, time consuming and error prone due to enormous number of available design and optimization choices, complex interactions between all…

Kubernetes has become the foundation of modern cloud-native infrastructure, yet its management remains complex and fragmented. Administrators must navigate a vast API surface, manage heterogeneous workloads, and coordinate tasks across…

The cloud computing platform gives people the opportunity for sharing resources, services and information among the people of the whole world. In private cloud system, information is shared among the persons who are in that cloud. For this,…

Constructing testbeds for systems which are interconnected with large networks of other software services is a challenging task. It is particularly difficult to create testbeds facilitating evaluation of the non-functional qualities of a…

OpenStack is an open-source private cloud used to run VMs and its related cloud services. OpenStack deployment, management, and upgradation require lots of efforts and manual troubleshooting. Also, workloads and services offered by…

ably successful in building a large market and adapting to the changes of the last three decades, its impact on the broader market of information management is surprisingly limited. If we were to design an information management system from…

In recent years, we have witnessed the growing interest from academia and industry in applying data science technologies to analyze large amounts of data. In this process, a myriad of artifacts (datasets, pipeline scripts, etc.) are…

Current approaches to designing energy-efficient applications typically rely on measuring individual components using readily available local metrics, like CPU utilization. However, these metrics fall short when applied to cloud-native…

Systematic exploration of hypotheses is a major part of any empirical research. In software engineering, we often produce unique tools for experiments and evaluate them independently on different data sets. In this paper, we present…

Data-sharing pipelines involve a series of stages that apply policy-based data transformations to enable secure and effective data exchange among organizations. Although numerous tools and platforms exist to manage governance and…

Cloud platforms allow users to execute tasks directly from their web browser and are a key enabling technology not only for commerce but also for computational science. Research software is often developed by scientists with limited…

Public Cloud Computing has become a fundamental part of modern IT infrastructure as its adoption has transformed the way businesses operate. However, cloud security concerns introduce new risks and challenges related to data protection,…

Cloud computing allows users to view computing in a new direction, as it uses the existing technologies to provide better IT services at low-cost. To offer high QOS to customers according SLA, cloud services broker or cloud service provider…

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere…

For many years, the distributed systems community has struggled to smooth the transition from local to remote computing. Transparency means concealing the complexities of distributed programming like remote locations, failures or scaling.…

The web ecosystem is rapidly evolving with changing business and functional models. Cloud platforms are available in a SaaS, PaaS and IaaS model designed around commoditized Linux based servers. 10 billion users will be online and accessing…