Page 360 - Big data - Concept and application for telecommunications

7 Big data - Concept and application for telecommunications

− Creating new service models using big data analytics.
Big data technology reduces cost by:
− Scale-out of data storage;

− Identifying and reducing inefficiencies.

7 Related technical areas of big data

7.1 Cloud computing
Cloud computing is a paradigm for enabling network access to a scalable and elastic pool of shareable physical
or virtual resources with self-service provisioning and administration on-demand. Key characteristics of cloud
computing are [ITU-T Y.3500]:
− Broad network access: a feature where physical and virtual resources are available over a network
and accessed through standard mechanisms that promote use by heterogeneous client platforms;
− Measured service: a feature where the metered delivery of cloud services is such that usage can be
monitored, controlled, reported, and billed. This is an important feature needed to optimize and
validate the delivered cloud service;
− Multi-tenancy: a feature where physical or virtual resources are allocated in such a way that
multiple tenants and their computations and data are isolated from, and inaccessible to, one
another;
− On-demand self-service: a feature where a cloud service customer can provision computing
capabilities, as needed, automatically or with minimal interaction with the cloud service provider;
− Rapid elasticity and scalability: a feature where physical or virtual resources can be rapidly and
elastically adjusted, in some cases automatically, to quickly increase or decrease resources;

− Resource pooling: a feature where a cloud service provider's physical or virtual resources can be
aggregated in order to serve one or more cloud service customers.

Big data needs on-demand high-performance data processing and distributed storage as well as a variety of
tools required to accomplish activities of the big data ecosystem. The burst nature of workloads makes cloud
computing more appropriate for big data challenges such as scalability and timeliness [ITU-T Y.3600].

The relationship of cloud computing and big data mainly concerns two aspects:
1) Cloud computing can support big data using cloud infrastructure and services;
2) Big data services can provide public cloud analysis services, such as big data as a service (BDaaS).

7.2 Internet of things

The Internet of things (IoT) is a global infrastructure for the information society, enabling advanced services
by interconnecting (physical and virtual) things based on existing and evolving interoperable information and
communication technologies [ITU-T Y.2060].
The IoT can be perceived as a far-reaching vision with technological and societal implications. From the
perspective of technical standardization, the IoT can be viewed as a global infrastructure for the information
society, enabling advanced services by interconnecting (physical and virtual) things based on existing and
evolving interoperable ICT. Through the exploitation of identification, data capture, processing and
communication capabilities, the IoT makes full use of "things" to offer services to all kinds of applications,
while ensuring that security and privacy requirements are fulfilled.
Big data in the context of IoT has some specific characteristics which do not necessarily pertain to big data in
other technical areas. The prominent characteristics of big data in the context of IoT are: high variety
(heterogeneity of data types and sources), high velocity (high frequency of data generation) and high
volatility (data generated in a non-persistent stateless manner).

352 Standardization efforts at a glance – roadmap