analysys mason: "revolutionizing mobile assurance in the era of 4g

Revolutionizing mobile assurance in the era of 4G/LTE August 2014 Patrick Kelly (Research Director, Analysys Mason) and Tara Van Unen (JDSU)

Executive summary Network and service providers have spent a lot of time and money creating advanced mobile networks as a way to provide more bandwidth and faster services to customers worldwide, but even with these investments 40% of customers that leave their current provider do so because of service issues. How can this be possible?

Today’s networks are more complex and dynamic than ever before. LTE technology is a major step forward in creating an intelligent network where handsets can talk to the network to create the best service environment possible. But while LTE and other 4G technologies promises to facilitate more sophisticated and scalable services, the assurance solutions responsible for ensuring a high quality of experience have not evolved to the same degree. Most providers employ assurance solutions based on a model that has not significantly changed over the past decade. This model was designed for voice traffic when the networks and user behaviors were predictable in nature – not for today’s dynamic environment of personalized services and expanding mobile applications. Most importantly, it is a model that treats all traffic and problems equally, instead of prioritizing them by impact on subscriber experience – thus compromising both efficiency and bottom-line revenue.

Mobile operators are now facing significant challenges in using traditional assurance solutions that:

• are not financially scalable to meet the explosive growth in 4G/LTE “mobile broadband” • cannot drive meaningful improvements in customer experience • lack the openness required to optimize assets and share data across applications • cannot deliver the real-time traffic visibility and analysis needed to enable and assure

dynamic network and service delivery.

With billions being invested in the evolution to 4G/LTE, yet customer churn reaching an all-time high, a better assurance model is needed. A new paradigm of customer experience assurance (CEA) is emerging which takes a fundamentally different approach to assurance in order to address the opportunities and challenges of dynamic 4G/LTE networks. The goal of this new approach is to enable a real and relevant improvement in customer experience, while maximizing operator productivity and profitability. For operators, the key requirements of CEA include the ability to:

• proactively identify and resolve problems having the greatest impact on customer experience in a fraction of the time, through a multi-dimensional and real-time correlation of customer experience with network and service performance

• break the traffic growth cost curve, with a substantial improvement in capex, opex, footprint and scalability through innovative monitoring and troubleshooting processes

• integrate and correlate data from any source to any application, providing deep end-to-end visibility, reduced OSS costs, and data monetization

• enable the assurance of dynamic networks and services with real-time intelligence, delivered in the order of seconds – not minutes – and virtualization-capable features.

Revolutionizing mobile assurance in the era of 4G/LTE | 2

Introduction LTE has become the preferred technology for mobile operators who have multiple cellular network technologies and different bands of spectrum. At the end of 2013 there were 256 LTE networks commercially available, and this is forecast to increase to more than 500 networks across 128 counties by 2017.1 Advanced mobile devices operating on these higher-speed networks are driving new services and applications, and a corresponding explosion of data traffic.

This exponential growth of mobile data combined with increasing service complexity, performance sensitivity, and requirements for improved customer experience and greater ARPU have rendered traditional assurance methodology and solutions obsolete. Next-generation assurance solutions are needed to empower operators to scale with traffic growth while both reducing operational expenses and enabling new revenue streams. Furthermore, service providers are seeking to achieve better ROI and value from their assurance investment by openly sharing data assets and intelligence across multiple departments and applications. Today’s assurance solutions must be based on a truly “open” architecture, with the ability to collect data from any third-party source and to deliver purpose-driven, relevant intelligence to any third-party application. Finally, to protect investment, assurance solutions must be capable of operating and excelling within NFV-enabled2 networks of the future, with virtualization-ready features and true real-time intelligence that can adapt to changes in subscribers, services, and network resources in a matter of seconds.

This paper evaluates how the challenges and opportunities – both technical and financial – of mobile broadband are driving the need for a new assurance model, and what kind of approach operators should use to successfully enable and assure mobile services of today – and the future.

Part I: Industry trends driving change Growth in mobile broadband traffic The number of mobile connections worldwide is forecast to grow at a CAGR of 5.5% and reach 6.24 billion by 2017 (see Figure 1 below). But the growth in mobile traffic will be far greater than this: the average monthly volume of voice and data traffic per connection worldwide is forecast to grow at a CAGR of 33.7% to reach 659MB by 2017. This is an increase of more than 400% in a five-year period.

1 Source: GSMA, The Mobile Economy 2014 2 NFV: Network Functions Virtualization – see discussion below.


Figure 1: Mobile connections and traffic per connection, by region, 2012–2017 [Analysys Mason, 2012]

This growth in data traffic is being driven in large part by the adoption of smartphones, tablets, and high speed data USB modems in developed economies. On average, LTE users consume 46MB of mobile data per day, which is 168% more data than a 3G subscriber.3 The heaviest users consume 10 times more data when they move from 3G to 4G/LTE.4 According to the latest Cisco Visual Network Index, global mobile data traffic grew 81% in 2013, and is forecast to increase at a CAGR of 61% between 2013 and 2018 to reach 15.9 exabytes per month.

4G/LTE has created a dilemma for the traditional monitoring and assurance paradigm, where cost scales linearly with traffic, and has driven the need for a new model that can scale with traffic growth at a significantly lower cost than exists today. Customer experience impacts ARPU and churn

Given the growth of mobile data, it is not surprising that the ARPU for wireless data is increasing at a five-year CAGR of 16% while the ARPU for wireless voice is declining at 7.8%. In fact, data usage is expected to account for 95% of all global mobile revenues by 2015.5 However, in order to seize the revenue opportunity associated with increasing data growth, operators need to ensure a personalized and high quality of experience for the subscribers who are consuming the underlying services and applications.

Quality of experience is a powerful competitive differentiator that enables operators to improve customer lifecycle value and reduce churn – which is as high as 24% in mature markets.6 Research 3 Source: Alcatel-Lucent Research, October 2013 4 Source: JDSU Arieso Hungry Handsets Report, January 2014 5 Source: Ericsson 6 Source: Analysys Mason


shows that customer experience is directly related to quality of service and the underlying network performance. CSPs also rate network QoS as the most important factor contributing to customer satisfaction: 56% of CSPs believe network QoS influences customers’ willingness to recommend a CSP.7

Figure 2: Customer lifecycle value [Analysys Mason, 2013]

However, recent studies indicate that current assurance solutions are not capable of achieving real and relevant improvements in customer experience and service performance, and that poor QoS is responsible for 40% of all customer churn.8 The traditional approach to assurance is not efficient or effective in the era of enriched and personalized service offerings: a new model is needed that delivers continuous improvement in customer experience and enables innovative services and higher revenues.

Operators need greater insight and value

Declining profitability and continued competition from OTT players have put network operators under immense pressure to both optimize and integrate their data assets and B/OSS systems in order to improve opex, increase efficiency, and gain better insight. Operators are seeking to achieve improved ROI from their monitoring and assurance systems, enabling multiple departments to leverage the same data assets/investment and the enriched contextual intelligence of relevance to their business. For example:

• operational data from the NOCs is required by the contact and service operations center • customer care is leveraging real-time network data to proactively resolve network service

issues before they affect service • cross-domain data sharing is a requirement for end-to-end service management.

However, traditional assurance solutions are generally “closed” systems that lack the ability to openly collect, mediate, and deliver intelligence outside the proprietary system. In recent surveys by the TM Forum, global service providers noted “data integration issues” as the number one challenge to success in both big data-analytic and customer-experience programs, and their ability to realize

7 Source: Analysys Mason, 2013 8 Source: Analysys Mason, 2013


higher business benefits from the amount and type of data available in their environment. This presents a major challenge for the initiatives that CSPs are rolling out in the area of customer experience and the monetization of big data.

The evolution to customer experience assurance must address this challenge though truly open data mediation, and correlation that has the ability to integrate and correlate data from the end-to-end network in much less time, and at much greater scale, than current solutions.

Virtualization of the network – NFV and SDN In addition to the robust growth of mobile data services, CSPs are also pursuing the virtualization of their networks to deliver key benefits such as resource elasticity and better capital efficiency. This evolution is starting in the core and will expand to the RAN. It requires low-cost management systems with the ability to orchestrate, optimize, and assure end-to-end QoS in a virtualized and dynamic environment. As self-optimizing networks (SON) and virtualization in the access network become more mainstream, service assurance systems must be able to adapt to rapid changes in the network topology, understand service demands, and link together the network domain with the service layer domain. This new architecture demands a real-time network monitoring system.

Part II: Next-gen assurance requirements and methodology Solution scalability: breaking the traffic growth cost curve Figure 1 highlighted the forecast increase in traffic volumes through 2017, but this exponential traffic growth is not matched by the growth in operator revenues. As shown in Figure 3, mobile broadband traffic growth is exceeding operators’ ability to meet network capacity demand, and ARPU rates are not increasing sufficiently to offset bandwidth demand, despite the move to tiered data packages in many countries. This combined effect is putting pressure on operators to improve capital efficiency through measures which include RAN sharing, Wi-Fi offloading, and selectively targeting capex in specific areas of the network.

Figure 3: Mobile growth and revenue forecasts


Operators’ expense budgets are currently on a divergent curve from traffic volumes. This poses many challenges, among which is that the scaling cost curve associated with traditional assurance solutions tracks in a linear fashion with the exponential traffic growth. This cost trajectory renders current assurance solutions financially unviable for the era of 4G/LTE mobile broadband and beyond.

The model for next-generation mobile assurance must be capable of decoupling cost from traffic growth in order to scale in a much more financially efficient and sustainable fashion, while maintaining technical integrity and effectiveness. Three innovations in assurance solutions have evolved to address these objectives: value-based monitoring, streamlined troubleshooting processes, and the ability to scale individual components of the solution independently.

Value-based monitoring equips operators with a model to address the data growth dilemma that is breaking assurance solutions’ scalability and budgets. Traditional assurance solutions use a one-size-fits-all model that monitors and treats all traffic equally, regardless of value. A new value-based assurance model customizes network monitoring and analytics according to the unique needs of different service types and customers, and their associated business value. The ability to deliver deeper analysis and metrics for premium services and high-ARPU customers while minimizing investment and visibility for less valuable traffic helps operators manage data growth in a way that aligns with their budget and customers.

Figure 4: Traditional versus value-based monitoring

There is an equal need to achieve improvements in cost and efficiency with a more streamlined troubleshooting process. For the troubleshooting (specifically, transactional tracing) process, the traditional methodology involves pre-building xDRs for all monitored calls and data sessions. But when you consider that less than 0.1% of stored xDRs are actually used for troubleshooting, this renders more than 99.9% of xDR pre-build processing of no value – yet carried out at considerable cost! In order to optimize processing and storage costs, it makes more sense to only perform xDR-like processing for those calls or data sessions for which troubleshooting is required, i.e. to process only on demand. This innovative approach requires improved storage and retrieval technology, where the required data can be identified, correlated and retrieved in a matter of seconds, making tracing query response times acceptable to the assurance solution user.

Assurance solution architectures consist of many data-processing and storage components, and in traditional solutions these components are typically highly dependent and linked in such a way that all components must be scaled simultaneously, and by the same factor, in order to achieve performance

“One Size Fits All” MonitoringTCO increases linearly with traffic growth

“Value-Based” MonitoringTCO decoupled from traffic growth


improvements. This interdependency results in significant inefficiency, an issue that is addressed by new assurance architectures that have the flexibility to scale individual components of the solution independently, thereby significantly improving both cost and speed.

By employing these innovations, new assurance solutions can be deployed with a significantly lower total cost of ownership (TCO), where the costs scale in line with revenues (not traffic), and effectiveness is maintained. In cost-projection exercises conducted with tier-1 mobile operators in EMEA and Asia–Pacific, JDSU forecast significant cost savings using the above innovative models when compared to the approach currently utilized: operators could achieve greater than 63% TCO savings over a four-year period (assuming 20% year-on-year traffic growth). Other innovative approaches that have evolved to improve assurance costs and scalability include time-based KPIs (versus traditional flow-based) and KPIs based on statistical sampling of traffic.

Solution effectiveness: improving customer experience and revenue

Traditionally, the relationship between network/service performance and customer experience was simple – all customers generally used a small number of services (voice calls, texts, and simple emails) in exactly the same way, and it was therefore a relatively easy task to correlate network/service issues with their impact on customers and on the operator’s revenues.

The mobile broadband era has significantly changed this picture – customers with their smartphones and downloaded applications now use mobile operators’ services in a myriad of different ways, and the services themselves are becoming more complex as operators bundle various types of OTT content into their application-based packages. But the different types of OTT content have different revenue value, and also require different levels of network performance to deliver a high-quality customer experience (VoLTE, for example, is a service that has very stringent network performance requirements). This makes the task of correlating network and service issues with their impact on customers and revenues much more complicated. Furthermore, the smart devices themselves (through their OS functionality and settings) can also have a major impact on the customer’s experience.

This great variety in mobile broadband usage is driving new requirements in assurance solutions in order to ensure a high quality of customer experience and maximize operator revenues. Specifically, these tools must be able to simultaneously analyze network performance across multiple dimensions including the customer, OTT application, and device; and must also deliver this multi-dimensional performance analysis in real time. Only with such functionality can operators’ engineering teams identify how customers and revenues are being impacted by network/service issues.

Simply adding a customer experience management (CEM) solution to a portfolio of existing network and service assurance tools will not meet these new needs. Viewing the network and services through the eyes of the customer can only be achieved if the assurance tools are initially designed with user devices and OTT applications as well as the customer in mind. A new paradigm of customer experience assurance (CEA) has emerged that integrates the previously separate network, service, and customer assurance functionality, as shown in Figure 5.

Figure 5: Customer experience assurance


However, along with the multi-dimensional analysis provided by CEA, new and refined performance measurements are also required. For example, when voice becomes just another LTE data service (as VoLTE), the measurement of voice quality will again be required, and must be of sufficient resolution to identify all customer experience issues. This requires solutions that can provide mean opinion scores (MOS) measured every few seconds during a call, and not just an MOS score averaged over the call duration.

In the mobile broadband environment, the effectiveness of an assurance solution is measured by the degree to which the customer experience data can be correlated (via multi-dimensional analysis) to an underlying network, service, or other problem. With such analysis, assurance staff can conclude which customers and revenues are truly being negatively impacted, and identify which issues should have the highest priority for resolution. Figure 6 provides an example of a multi-dimensional performance analysis display from the JDSU xSIGHT CEA solution.

Figure 6: Multi-dimensional analysis of customer experience

It should also be noted that having the ability to uncover all typical problems in today’s mobile broadband era requires assurance solutions that can access data from all points and equipment in the service delivery chain, from the head-end content servers to user devices. Collecting data from operational equipment and devices has become increasingly important as (performance-impacting) network intelligence has become more distributed in modern mobile broadband networks. Also, with performance analysis by individual service and customer now a requirement, the ability for assurance solutions to automatically collect data from OSSs such as provisioning systems is becoming a necessity, since manual reconfiguration is no longer able to cope with the scale and speed of changes. Such demands require CEA solutions to have an open architecture, allowing external performance and reference data sources to be quickly and easily integrated into the assurance analytics.


Solution ROI: OSS optimization and data monetization The previous section of this paper considered the evolution of assurance functionality to deliver a high quality of customer experience and to reap incremental revenues and profits in an era where service usage and revenue models have fundamentally changed. In addition to the evolution of these market needs, there are two major new demands being placed on assurance solutions: support for OSS optimization, and the monetization of assurance-based intelligence. Both of these demands place similar and overlapping requirements on the architecture and functionality of assurance solutions.

Consider first OSS optimization. Established operators typically have hundreds of OSSs, and are now running rationalization programs to significantly reduce the number of systems employed. Traditional assurance solutions are “closed” systems, with the ability to access only their proprietary data sources and feed their proprietary applications. A tier-1 mobile operator will typically have a multitude of these systems deployed across different technology domains in their network, often provided by multiple vendors, and generating data and records in a wide range of formats. This reality is due to the fact that the network ecosystem is constantly evolving, and therefore old and new technologies coexist for some time, as we see in today’s heterogeneous networks and hybrid physical/virtual environments.

In this situation, an assurance solution with an open southbound architecture can support OSS rationalization by integrating data access sources from various vendors and feeding a common set of applications, as illustrated in Figure 7. Through this approach, many independent closed assurance solutions can be replaced by a single open solution that can cost-effectively integrate a wide variety of data sources, each providing a different data set asynchronously to other sources, while managing and mediating the diversity of data outputs to openly feed the applications that are evolving.

Figure 7: Rationalization of assurance OSSs

An open northbound architecture also provides opportunities to leverage assurance intelligence for use models in departments beyond network operations. As the variety of data collected and analyzed within assurance solutions grows to include, for example, customer experience, location, device and OTT content usage, the value and opportunities for use of such intelligence beyond network operations also grows. As illustrated in Figure 8, operators are seeking a better return on their assurance investment by openly feeding multiple departments, such as customer care, marketing, and sales, with enriched intelligence to improve business results, optimize processes, and monetize data through the identification of new revenue opportunities.


Figure 8: The variety of user communities for evolved assurance solutions

The key challenge in supplying assurance intelligence to users in departments beyond operations is providing only the information they require and in a format that they, or their OSS/BSS tools, can understand, bearing in mind that many of these users will have no background in mobile networks or assurance solutions. This requires an assurance solution that has the ability to select only the required intelligence (down to the level of specific fields of information), and an open northbound API to format this intelligence in a way that the target external user or application will accept and understand. Selection of required intelligence must cover control-plane and user-plane data, and offer enrichment, correlation, and aggregation-based processing. For export formatting, support for open standards such as HTTP, J2EE, XML and Oracle database formats will enable the easiest and fastest integration with external applications.

New regulation around data privacy is also driving requirements for greater control and selectivity in the information fields being collected and exported by assurance solutions. For example, some countries in Europe already ban operators from profiling subscribers based on the online content they consume, and thus marketing departments require assurance solutions with the flexibility to collect and export data on user profiles and service usage patterns while complying with data privacy regulations.

Future-proof solutions: assurance in virtualized and NFV-enabled networks Recent research shows that the majority of mobile operators plan to deploy network functions virtualization (NFV) for their core network within the next 2–3 years. This means that assurance solutions must be capable of monitoring and troubleshooting both physical and virtual environments, and monitoring the dynamic services they carry. Wherever possible, hardware probes must be replaced by orchestrated software agents, as traditional probing approaches are impractical in virtualized environments. Software agents eliminate blind spots by providing visibility into the virtual layer, and can be deployed on demand or as part of complex service chains for end-to-end service continuity.

A key requirement for this evolution, and one which traditional assurance solutions are ill equipped to address, is a significant improvement in the meaning of “real time”, which can now be measured in seconds rather than minutes. As the network configuration changes, the configuration of the associated assurance solution must adapt and track these changes and metrics in real time to maintain the integrity of the assurance analytics. Traditional assurance solutions were never designed to dynamically reconfigure, and lack the speed to effectively control these changes. Assurance solutions must be purpose-built to enable adaptive assurance via tight integration with


network orchestration, true real-time intelligence and analytics, and dynamic reconfiguration of data-monitoring assets to follow changing network resources. In accordance with the ETSI NFV architecture model, open interfaces are required at multiple levels in the solution hierarchy such as at data collection, mediation, and reporting, in order to integrate assurance solution components into multi-vendor systems such as policy servers, active and assignable inventory databases, and service design and creation systems.

Part III: Operator recommendations and reference A fundamental shift is required in assurance methodology and tools in order to exploit the opportunities and full potential of 4G/LTE and dynamic (NFV, SDN) networks. These network technologies are driving new assurance requirements, which if not properly addressed, will jeopardize the large investments being made and the business strategies that rely on them. The recommendations below can guide operators who are defining and evaluating assurance-solution proposals and their ability to satisfy key requirements regarding cost, customer experience, ROI, and virtualization.

In order to break the traffic growth cost curve, and scale with continued traffic growth in a financially viable fashion, operators should seek the following capabilities from their assurance solution:

• value-based monitoring and analytics • on-demand transactional tracing (troubleshooting) processing • flexible solution architecture where all processing and storage components can scale

independent of each other.

Optimizing customer experience, alongside operator revenues and profits, requires assurance solutions with the ability to:

• correlate customer experience with network and service performance in real time • analyze customer experience from multiple dimensions, including both hosted and OTT

services and applications • measure KPIs with a granularity of seconds • collect performance and reference data from all sources, including network elements and other

OSSs • provide and correlate geo-location information with application-aware performance data.

In order to improve assurance ROI through the rationalization of OSS systems and monetization of assurance intelligence, operators should look for solutions with an entirely open architecture that:

• easily integrates data from third-party data sources via an open southbound API • quickly feeds tailored data (for example, selected information only, formatted appropriately) to

third-party applications via an open northbound API. Finally, assurance in virtualized and NFV-enabled networks requires major changes to the architecture and responsiveness of assurance systems, including the ability to:

• support both virtualized and non-virtualized environments • deliver KPIs and data in a matter of seconds (not minutes) • integrate with NFV operational orchestrator units and multi-vendor systems • analyze orchestrator updates in real time (within seconds or faster) • reconfigure data collection agents in real time to track network configuration changes.


Figure 9 shows an example of a next-generation customer experience solution designed to satisfy the above industry inflections, opportunities, and requirements.

Figure 9: The JDSU xSIGHT customer experience assurance solution


About Analysys Mason • We analyze, track and forecast the different services accessed by consumers and enterprises, as

well as the software, infrastructure and technology delivering those services. • Research clients benefit from regular and timely intelligence in addition to direct access to our

team of expert analysts.

For more information, please visit www.analysysmason.com/research.

About JDS Uniphase JDSU is the worldwide leading provider of network and service enablement solutions, including testing, monitoring, assurance, and analytics. JDSU helps customers overcome the operational challenges associated with new technology and service introductions, and is working with partners to develop next-generation virtualized solutions for the monitoring and assurance of next-generation networks.

For more information, please visit www.jdsu.com.

analysys mason: "revolutionizing mobile assurance in the era of 4g

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