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Scientific problems that depend on processing large amounts of data require overcoming challenges in multiple areas: managing large-scale data distribution, controlling co-placement and scheduling of data with compute resources, and…
As the rate of data collection continues to grow rapidly, developing visualization tools that scale to immense data sets is a serious and ever-increasing challenge. Existing approaches generally seek to decouple storage and visualization…
In the coming years, the interconnection of a large number of devices is expected, which will lead to a new form of interaction between the real and the virtual world. In this promising scenario, known as the Internet of Things, it is…
Nowadays, Internet of Things platforms are being deployed in a wide range of application domains. Some of these include use cases with security requirements, where the data generated by an IoT node is the basis for making safety-critical or…
It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large…
Cloud computing is recognized as one of the most promising solutions to information technology, e.g., for storing and sharing data in the web service which is sustained by a company or third party instead of storing data in a hard drive or…
We present CleanQ, a high-performance operating-system interface for descriptor-based data transfer with rigorous formal semantics, based on a simple, formally-verified notion of ownership transfer, with a fast reference implementation.…
Compute infrastructure hosted by a cloud provider allows an application to scale without limit. The application developer no longer needs to worry about the up-front investment in a server farm provisioned for a worst-case load scenario.…
In this article we present our relocatable distributed collections library. Building on top of the AGPAS for Java library, we provide a number of useful intra-node parallel patterns as well as the features necessary to support the…
This paper emphasizes the critical role of interoperability in enabling efficient and secure communication for the fragmented distributed ledger ecosystem, particularly within on-chain finance. The purpose of this study is to streamline and…
As scientific frameworks become sophisticated, so do their data structures. Current data structures are no longer simple in design and they have been progressively complicated. The typical trend in designing data structures in scientific…
The ability to collect and analyze large amounts of data is a growing problem within the scientific community. The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity…
Many secure communication libraries used by distributed systems, such as SSL, TLS, and Kerberos, fail to make a clear distinction between the authentication, session, and communication layers. In this paper we introduce CEDAR, the secure…
Protecting computer systems handling possible sensitive information is of the utmost importance. Those systems are typically air-gapped with data diodes to assure that no information can physically flow back. Traditional computer protocols…
Every research project necessitates data, often requiring sharing and collaborative review within a team. However, there is a dearth of good open-source data sharing and reviewing services. Existing file-sharing services generally mandate…
Acquisition and processing of point clouds (PCs) is a crucial enabler for many emerging applications reliant on 3D spatial data, such as robot navigation, autonomous vehicles, and augmented reality. In most scenarios, PCs acquired by remote…
The growing disparity between computational power and on-chip communication bandwidth is a critical bottleneck in modern Systems-on-Chip (SoCs), especially for data-parallel workloads like AI. Efficient point-to-multipoint (P2MP) data…
Dataset storage, exchange, and access play a critical role in scientific applications. For such purposes netCDF serves as a portable and efficient file format and programming interface, which is popular in numerous scientific application…
This chapter details how Big Data can be used and implemented in networking and computing infrastructures. Specifically, it addresses three main aspects: the timely extraction of relevant knowledge from heterogeneous, and very often…
Any information is valuable as long as it has related data. If related data are not put together, the information is meaningless as unrelated data has no value. The mapped information is required only by authenticated users. So there is no…