Recommendation ITU-T Y.3601 provides a framework for data exchange in a big data ecosystem. Big data exchange covers multiple processes for data import and data export within a big data ecosystem. Big data exchange is used for exchanging data of multiple types and multiple formats from a data source to a data target.
In a mobile network, a great deal of traffic data which reflects the real status of the mobile network and customers' actual experience is generated all the time. Based on the big data generated from the mobile network more efficient management and reasonable planning of mobile networks can be achieved.
Recommendation ITU-T Y.3519 describes the functional architecture for big data as a service (BDaaS). The functional architecture is defined on the basis of the analysis of requirements and activities of cloud computing-based big data described in Recommendation ITU-T Y.3600.
Recommendation Y.3600 provides requirements, capabilities and use cases of cloud computing based big data as well as its system context. Cloud computing based big data provides the capabilities to collect, store, analyze, visualize and manage varieties of large volume datasets, which cannot be rapidly transferred and analysed using traditional technologies.
Mobile Internet services harvest data in their big data infrastructure from multiple sources and multiple data dimensions with characteristics including scale, diversity, speed and possibly others like credibility or business value. Big data analysis drives nearly every aspect of mobile Internet services to improve service quality and user experience.
The purpose of this Recommendation is to specify requirements and capabilities of the IoT for Big Data. This Recommendation complements the developments on common requirements of the IoT [ITU-T Y.2066] and functional framework of the IoT [ITU-T Y.2068] in terms of the specific requirements and capabilities that the IoT is expected to support in order to address the challenges related to Big Data. Also, it constitutes a basis for further standardization work (e.g. functional entities, APIs and protocols) concerning Big Data in the IoT.
The present document is part 1 of a multi-part deliverable that define the fourth generation of high-speed data-overcable systems, commonly referred to as the DOCSIS® 3.1 specifications. This specification was developed for the benefit of the cable industry, and includes contributions by operators and vendors from North and South America, Europe, and Asia.
This generation of the DOCSIS® specifications builds upon the previous generations of DOCSIS® specifications (commonly referred to as the DOCSIS® 3.0 and earlier specifications), leveraging the existing Media Access Control (MAC) and Physical (PHY) layers, but with the addition of a new PHY layer designed to improve spectral efficiency and provide better scaling for larger bandwidths (and appropriate updates to the MAC and management layers to support the new PHY layer). It includes backward compatibility for the existing PHY layers in order to enable a seamless migration to the new technology.
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 describes a method for distributed deployment and centralized control of a DOCSIS cable broadband access system in which the cable network equipment is used in a plant where fibre is run to the cabinet (e.g. in the basement of a customer's multiple dwelling unit) and coax to each customer. This architecture is collectively referred to as Cabinet DOCSIS or "C-DOCSIS". It has been developed to meet the operability and manageability requirements for cable networks that offer a variety of high-bandwidth services and provide QoS guarantees for these services in a distributed architecture. This architecture applies to the operations, administration and management (OAM) of cable broadband access networks.
The present document defines optional implementation architectures for CMTS equipment intended for use in distributed deployments. It defines the functional modules within the CMTS, three different system architectures utilizing the functional modules and the data and control interfaces between these modules for each of those architectures. It also defines general device requirements for the different distributed CMTS architectures.
The present document corresponds to the CableLabs C-DOCSIS specification
ISO/IEC TR 20547-2:2018 provides examples of big data use cases with application domains and technical considerations derived from the contributed use cases.
You can see here the preview of the standard.
This document discusses how a number of privacy threats apply to technologies designed for IPv6 over various link-layer protocols, and it provides advice to protocol designers on how to address such threats in adaptation-layer specifications for IPv6 over such links.
Security-related misbehaviour detection mechanism based on big data analysis for connected vehicles.
The connectivity of vehicles is increasing and the number of vulnerabilities is also increasing with the complex technology development. It makes the connected vehicles face more threats. Big data analysis improves security analysis a lot, and the huge amount of automotive data analysis is very useful for connected vehicles security. This Recommendation addresses security-related misbehaviour detection mechanism based on big data analysis for connected vehicles, which could be helpful for stakeholders to utilize the automotive data to improve vehicle security.
This recommendation is now under study.
