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Massive Network Deployment – who moved my skill? (Part II - Big Data)

By Dudy Cohen

In our previous blog post, we discussed the challenges service providers and operators face as their networks evolve and densify. It is clear that the main operational challenge lies in the planning, installation and commissioning phase. However, additional challenges also arise during the management, maintenance and optimization phase.

This blog describes those challenges and recommends ways to mitigate them. 

The massive-network challenge

The growing number of elements in the network and the complexity of the network architecture contribute to the fact that network management, maintenance and optimization tasks become far more challenging and require more resources.

In the case of small to medium networks, tasks such as root-cause-analysis can be performed manually based on fault-monitoring inputs from the network elements and/or the network management system. However, in the case of  bigger networks, these tasks take more time as the human resource analyzing the information gathered from multiple layers of network elements and management systems needs to sort through a massive amount of information to isolate the root-cause of the fault before restoring service.

This lengthy procedure affects the service provider’s quality of service and ability to hold up to the SLA signed with customers, and may result in fines and churn.

Additional tasks related to quality-of-service are the identification of network bottlenecks, resource optimization and network expansion. These tasks involve an ongoing review of link and element performance based on performance-monitoring data gathered from network elements. Once again, these are manageable tasks in the case of small and medium networks. They become more challenging in bigger networks as the enormous amount of data is overwhelming. This typically leads to a reactive approach to bottlenecks and performance degradation instead of a proactive one, which in turn can result in reduced quality-of-service and increasing churn.

What’s the solution?

As in the planning, installation and commissioning case, automated tools can help solve these challenges as well.

The common factor in the abovementioned challenges and similar ones is the sheer amount of data retrieved from the network, which needs to be analyzed to maintain a high level of quality of service and resource utilization. Big-data analytics solutions can be implemented to handle this amount of data more efficiently and effectively.

These implementations can speed up root-cause analysis tasks and shorten service restoration time, and also continuously monitor the entire network and alert (or even act) when network configurations change or expansion is required to streamline operations.

The automation of these processes can help to significantly improve your workforce productivity, enhance your customers’ quality of experience and increase resource utilization. For this reason, we recommend that operators examine the availability of such services and tools when choosing network vendors, even if your network is currently smaller and a massive-network seems to be far from your current architecture.

In our next blog, we will discuss additional tools that expedite the creation of services, network optimization and service restoration.

 

 

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