M2M-Based Cross-Industry Application
As a part of the Internet of Things (IoT), machine to machine (M2M) communications brings great changes to industrial and business worlds. It is widely applied to fields such as industry automation, logistics, smart grid, smart city, healthcare, and national defence. The ratio of M2M communication services to traditional communication services will reach 30 to 1 by the year 2020 according to analysts at Forrester. M2M is set to be the next trillion-dollar communication service.
Multiple participants are involved in the M2M value chain, at the core of which is the M2M service support platform. As the bridge between terminals and applications, the M2M service support platform ensures proper division of labour among the roles in the value chain. This platform promotes the development of the entire value chain, and reduces the operation cost of carriers through standard protocol and open development environment.
Normalisation and standardisation are the basis for large-scale M2M development. Unified standards enables M2M to transit from vertical development to horizontal development, and provide the basis for labour division among participants in the value chain.
The motivations for telecom operators to enter the M2M field are as follows:
Telecom service providers are at an obvious advantages in the M2M market due to their abundant customer resources, powerful communication networks, and rich network operation experience. Telecom operators can help improve M2M standards and establish the M2M service support platform based on the existing network resources by delivering on the following objectives:
- Maximize the advantages of existing communications networks by optimising networks and transforming the support systems for large-scale M2M applications, or transforming enterprise service systems to adapt to M2M market requirements.
- Forging an alliance with industry partners, actively participating in the establishment of M2M standards, including the M2M terminal management interface, industry applications interface, and unified industry data format.
- Actively constructing the M2M service support platform, providing resources and service integration over this platform, and providing ICT integration capacity, standard flow, and standard middleware service for industry M2M applications.
- Getting involved in industry M2M services while enhancing pipe services, and providing application integration service and business operation service.
The deployment of ultra-broadband networks, combined with the popularity of intelligent terminals, and the mass production of Internet of Things terminals has resulted in rapid data convergence in the cloud. Data accumulated in the cloud is driving the development of Big Data-based applications.
The huge amounts of data produced within communication networks are strategic assets of telecom operators with the mining and use of Big Data becoming a new engine for the development of carriers. The mining of Big Data helps improve carriers’ operational efficiency and network quality, optimise network performance, improve CRM levels, and achieve accurate marketing. In addition, DaaS (Data as a Service) and data sharing allows carriers to efficiently apply their strategic assets to government management and enterprise customer management/marketing. In this case, value is added to the data.
The huge amounts of data produced within communications networks includes signaling data, network management data, log information, DPI data, accounts, charges, and customer service information. The data is not structured, and is dynamically processed. It is difficult for traditional technologies to fully use such huge amounts of data. This leaves a great development space for Big Data technology.
Big Data technology represents the combination of cloud computing and commercial intelligence. Hadoop (a cross platform, open-source software framework for distributed storage and distributed processing of very large data sets) has become the de facto industry standard in the distributed middleware field of Big Data. However, native Hadoop cannot perfectly adapt to actual application requirements. In application scenarios of telecom Big Data, native Hadoop still needs to be optimised in terms of system management, operation and maintenance, system reliability, data throughput, and service scheduling, and needs parameter modification in actual operation.
Ensuring the security of privacy is central to the success of Big Data applications. Only those operators trusted by customers are able to mine, analyze and act on customer data. When using Big Data, telecom operators must comply with related laws and regulations. Additionally, operators need to encrypt the storage and transmission of sensitive customer information, and allow only authorised access to such sensitive information.
Building on its experience in the telecommunications industry, ZTE has created a core technology platform for Big Data that leverages its technology accumulation in cloud computing and distributed middleware. ZTE has obvious advantages over its competitors in fields such as telecom data collection, pre-processing, real-time stream processing, storage, and analysis, and can apply its capabilities to data mining and analysis.
There are multiple application scenarios for telecom Big Data. Sitting at the core of these scenarios, ZTE cooperates with telecom operators to form a great number of commercial solutions, including Big Data services based on a great deal of location information, multi-dimensional analysis based on signaling monitoring, network management analysis, wireless network optimisation, traffic operation, accurate marketing, personalised recommendation, Big Data-based spam message monitoring, and Big Data centre solution.
As Big Data is applied outside of the telecom operators’ network, ZTE actively cooperates with operators in order to develop innovative business models in fields such as smart city, smart transportation, and banking and finance.