Standard

This document proposes a framework that identifies and characterizes the information and relationships needed to describe and measure properties of cloud services that are representative, accurate and reproducible. This information can be used in a variety of ways including, collection, comparison, gap analysis, and assessment or description of metrics at the technical or business levels. These metrics can connect information intended for decision-making, for the service agreements between provider and customer, for the runtime performance measurement and the underlying properties within the provider’s system.

Big Data is a term used to describe the large amount of data in the networked, digitized, sensor- laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is outpacing scientific and technological advances in data analytics. To advance progress in Big Data, the NIST Big Data Public Working Group (NBD-PWG) is working to develop consensus on important, fundamental concepts related to Big Data. The results are reported in the NIST Big Data Interoperability Framework (NBDIF) series of volumes. This volume, Volume 2, contains the Big Data taxonomies developed by the NBD-PWG. These taxonomies organize the reference architecture components, fabrics, and other topics to lay the groundwork for discussions surrounding Big Data.

The present document provides specifications of infrastructure related ITS services to support communication between infrastructure ITS equipment and traffic participants using ITS equipment (e.g. vehicles, pedestrians). It defines services in the Facilities layer for communication between the infrastructure and traffic participants. The specifications cover the protocol handling for infrastructure-related messages as well as requirements to lower layer protocols and to the security entity.

The present document is part of a series of specifications that defines the fourth generation of high-speed data-over-cable systems, commonly referred to as the DOCSIS 3.1 specifications. The present document was developed for the benefit of the cable industry, and includes contributions by operators and vendors from North and South America, Europe and Asia.

The present document provides a framework for concurrent tests of multiple services, using a top-level approach which is also modular and scalable with respect to new services. Also, the framework explicitly integrates measurement methodology, in particular reproducibility aspects.

The present document's scope is to provide guidance on OTT video streaming testing approach with a set of minimum desired and most meaningful QoE centric QoS parameters along with recommendations to create a figure of merit quantifying the OTT video streaming session quality, where possible. In addition, the set of introduced QoE centric QoS parameters aim to help with the identification of the possible roots of video quality degradation. The present document also offers means to understand aspects related with network and services optimization and troubleshooting, such as the trade-off between bandwidth usage or controlled throttling and end-to-end video quality.

The present document describes the Single Illumination System, which allows to deliver Parent Signals for direct reception by consumer receivers and, at the same time, for a deterministic generation of daughter streams for terrestrial retransmission. Parent Signals can be provided to the daughter site via all defined TS-based DVB means - be it satellite, cable or terrestrial. Metadata may be provided as part of the Parent Signal(s) (called "in-band" in the present document). Part of the metadata may also be provided "out-of-band".

Recommendation ITU‑T Y.3602 describes a model and operations for big data provenance. Also, this Recommendation provides the functional requirements for big data service provider (BDSP) to manage big data provenance. The reliability of data is an important factor in determining the reliability of the analysis result. Data provenance aims to ensure the reliability of data by providing transparency of the historical path of the data. In a big data environment, complex data processing and migration due to the big data lifecycle and data distribution cause various difficulties in managing data provenance.

The OASIS KMIP TC works to define a single, comprehensive protocol for communication between encryption systems and a broad range of new and legacy enterprise applications, including email, databases, and storage devices. By removing redundant, incompatible key management processes, KMIP will provide better data security while at the same time reducing expenditures on multiple products.

SCOPE: The aim of this Technical Report is to study and specify how to collect data and how to feedback data analytics to the network functions.

This document defines a mechanism by which web developers can control the resources which a particular page can fetch or execute, as well as a number of security-relevant policy decisions.

This specification describes an imperative API enabling a website to request a user’s credentials from a user agent, and to help the user agent correctly store user credentials for future use.