X-BRAiN for Smart Network Planning

FULLY AUTOMATED AND AI POWERED

HIGHLY ACCURATE AND 10 TIMES
FASTER – BASED ON X-BRAiN

The automatic performance of network planning tasks, regardless of whether it concerns Ethernet cables, fibre optical cables or others, is an essential first step as it defines how a network is build, therefore strongly impacting the deployment cost of ISPs.

As a cloud native and big data driven IoT platform, X-BRAiN is able to perform AI based network planning based on powerful cloud computing abilities. Based on our deployment architecture that introduces dedicated micro services per service packet, X-BRAiN provides the flexibility to quickly react to recent changes and adjust the mathematical models that are used for calculating the final network plans.

X-BRAiN FiBRE for FTTH network planning has been engineered while having several key performance indicators in mind. This includes the generation of network plans within hours, a flexible setup strategy for respecting architecture rules by design and easily change requirements as well as a readily available and consistent output including the used KPIs.

As an example, our AI based xPON network planning optimisation tool generates different network topologies and evaluates the most suitable one for getting the optimal solution. In the past, X-BRAIN FiBRE has been used to automatically generate network plans that provide highly accurate results while being in overall 10 times faster than competitors.

WHAT WE ASPIRE TO

What we offer

Value-oriented planning
Step-by-step development
Seamless integration
Automated operation

Our Mission

More efficiency with X-BRAIN integration

Our Vision

We are developing X-CITE to be one of the leading managed public cloud providers in Europe. For large and mid-sized companies, we are the strategic partner for all challenges on the way to and in the cloud – from the development of a strategy to final operation.

Corporate Culture

We are a technology company that continuously strives for excellence and drives forward innovation. Our work is customer-oriented and fast. At X-CITE, we are always striving to develop our expertise.

At a Glance

PLANNING STEPS & PROCESS

Optimisation Constraints

X-BRAiN for network planning allows to add constraints to the applied algorithm. This includes the assignment of specific nodes for dedicated tasks, e.g. splitters. Other types of constraints are the minimum/maximum length of cables, the minimum/maximum number of splitters, specific routing strategies and associated topology constraints and more.

Network Planning Outputs

The final network plans that are generated by the internal X-BRAiN algorithms include the complete set of all required output parameters. This features the placement of specific nodes like first/second stage splitters, aggregation nodes, cable routes and more. The final output also includes a complete bill of material (BoM), the applied KPIs and an overall cost estimation.

Applicable KPIs

The AI and ML algorithms that are used for the network planning process are able to follow a specific set of KPIs that can be defined. This includes the number of residential or business addresses that are covered, the total metres of used cable or other KPIs that are relevant for the business of the specific ISP.

Forecasting

In addition to the basic network planning task, X-BRAiN is able to forecast the material and human resource demand in order to initiate a dedicated planning. In this context, X-BRAiN is ready to integrate with business internal job orchestration systems in order to provide timelines, scheduling proposals and the required bill of material (BoM).

Tuning of initial Output

The generated network plans can be forwarded to be used in surveying tasks. Potential issues that have been detected on the field can be adjusted a-posteriori by the surveyor and a re-calculation of the network plan can be triggered by X-BRAiN at any time. This includes potential geographical optimisations like the usage of streets with lower build costs or locations where build jobs can be performed more conveniently.

Data Validation & Cleansing

Depending on the available data that is used by X-BRAiN for performing the network planning process, data validation and cleansing will be applied to highlight and/or correct incorrect data before using it as an input for internal algorithms. Potential applicable services for importing and exporting data, e.g. integration to geo servers including an evaluation, styling or enriching of data can be applied.

Input Parameters

The Ai and ML based network planning algorithms are considering multiple types of input parameters. This includes geographical data like the existing infrastructure in the form of ducts, poles, cabinets or OLTs, next to the connectivity demand like addresses, buildings or P2P connections. Moreover, additional parameters like material requirements, e.g. splitting ratios, or resilience requirements are considered.