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Page 1 of 14, © Strategy Analytics 2014
Value Based Backhaul Monitoring for Small Cells
How Network Operations can Contribute to the 'Bottom Line'
Based on Report and Webinar Sponsored by
Viewpoint Snapshot
This paper investigates the benefits to LTE Operators of Value Based Monitoring for Small Cell
Backhaul. Such Monitoring and Management solutions leverage End to End, Real Time network
monitoring and Selective Visibility to assure high quality Mobile Broadband network service and
fast problem resolution for superior Customer Experience Management and Policy Control. At
the same time the right solution can transform the role of Network Operations to enable
fast Service Activation and Subscriber Service Management that reduces network total cost
of operations (TCO) and customer dissatisfaction while helping to create value from new
services.
June 2014
Wireless Networks & Platforms Service
Sue Rudd, [email protected]
Page 2 of 14, © Strategy Analytics 2014
Executive Summary
Traffic Growth driven by Video and WiFi integration followed by LTE-Advanced (LTE-A) Carrier
Aggregation is creating the need for Small Cells. To deliver good End to End (E2E) customer
performance expansion of the Radio Access Network (RAN) and small cell capacity must be matched
with appropriate backhaul capacity. We estimated the required incremental capacity for backhaul in
an earlier report ‘Closing the Mobile 'Backhaul Gap' will Improve Profit Margins’ and forecast the
incremental investment needed to close the ‘Backhaul Gap’.
As small cell are deployed over the next two years we project an increase the use of fiber backhaul
for high capacity clusters of small cells. Many of these clusters will share backhaul transport and
increase the peak backhaul bandwidth required. Fiber connectivity will follow. See our most recent
report ‘Small Cells Taking Off, Need Fiber Backhaul Soon’.
Customer Experience and performance management depend not just on high capacity mobile
broadband access but on three key network monitoring and management capabilities:
End to End (E2E) Network Visibility
Real-Time Monitoring
Selective Data for Analytics
End to End (E2E) network visibility on a link by link basis downstream of the metro aggregation
points is essential to isolate physical layer faults in seconds not tens of minutes and redirect traffic
before congestion cascades across the metro area network.
Real Time Monitoring of performance is important to capture events and alarms as they occur to
resolve problems in milliseconds or seconds. This enables operators to guarantee QoS and offer
Service Level Agreements (SLAs) that ensure levels customer experience are met profitably.
Selective Monitoring of the critical key parameters which are relevant to deliver good customer
experience allows operators to understand customer applications and service needs and reduce
churn - even as lower layer Deep Packet Inspection(DPI) monitors ‘go dark’ due to secure tunneling
for Google and facebook access and Netflix encoding etc..
If Mobile Operators add monitoring that will accelerate deployment testing, maximize network
visibility, lower response time and reduce customer dissatisfaction they will lower Total Cost of
Operations, enhance Customer Satisfaction, reduce Churn and improve Margins.
In this report we outline how operators can get these benefits from ‘Value Based Monitoring’
Page 3 of 14, © Strategy Analytics 2014
Contents
EXECUTIVE SUMMARY 2
LTE SMALL CELL MANAGEMENT DEMANDS THREE TYPES OF MONITORING FUNCTIONALITY 4 END TO END (E2E) NETWORK VISIBILITY 4 REAL TIME MONITORING 5 SELECTIVE DATA FOR ANALYTICS 6 MATCHING MONITORING TO SERVICE REQUIREMENTS 6
MONITORING AT DIFFERENT PHASES OF SMALL CELL BACKHAUL LIFECYCLE 8 PHASE 1. PLAN, DEPLOY AND ACTIVATE 8 PHASE 2. OPERATE 8 PHASE 3.DELIVER VALUE 9
IMPLICATIONS FOR OPERATORS 9 NETWORK OPERATIONS CAN PROACTIVELY MANAGE NETWORKS TO IMPROVE MARGINS 9 LOWER COST OF OPERATIONS 9 ENABLES NETWORK OPERATIONS CENTER (NOC) EXPERTS TO IMPACT ‘BOTTOM LINE’ 10 DELIVERS BETTER BACKHAUL PERFORMANCE TO REDUCE CHURN AND IMPROVE OPERATOR’S
BOTTOM LINE 11 ADDS NEW VALUE FROM SERVICE LEVEL AGREEMENT (SLA) GUARANTEES AND PRIORITY ON-
DEMAND SERVICES 12 INCREASED COMPETITIVE ADVANTAGE FOR FIBER TRANSPORT PROVIDERS WHO DEPLOY
MICROPROBES AND REDUCE TOTAL COST OF OPERATIONS (TCO) FOR THEIR OPERATOR
CUSTOMERS 12 BENEFITS OF AN INTELLIGENT MICROPROBE SOLUTION 13
CONCLUSIONS 13
CONTACT THE AUTHOR OF THIS REPORT: 14
Page 4 of 14, © Strategy Analytics 2014
LTE Small Cell Management Demands Three Types of Monitoring Functionality
There are three major new types of functionality that LTE requires:
End to End (E2E) Network Visibility
Real-Time Monitoring
Selective Data for Analytics
We discuss these in turn below.
End to End (E2E) Network Visibility
LTE needs E2E functionality including network, subscriber and session awareness to deliver Quality
of Service (QoS) across the entire network from the device to the Cloud or between users. The
Radio Access Network (RAN) can easily become the blind spot in E2E network Visibility. Maintaining
visibility across a complex LTE RAN with its multiple small cell clusters and partial mesh backhaul is
increasingly difficult. Historically mobile backhaul traffic was aggregated at Macro Cell Sites where
routers or lower layer DPI boxes could monitor both connectivity and service traffic. But today
downstream link level visibility at hub locations is lost when operators use IP backhaul beyond the
aggregation point. Statistical correlation of data at selected network elements to find physical
problems or isolate the cause of traffic congestion across network elements from multiple vendors
can take many minutes or even hours and does not yield complete E2E analysis – leading to poor
service, unhappy users and customer churn.
Chart 1. IP Backhaul network loses link level visibility beyond the aggregation point
Source: JDSU Small Cell Backhaul Solutions
Page 5 of 14, © Strategy Analytics 2014
Strategy Analytics has estimated that almost 50 percent of customer dissatisfaction with Mobile
Broadband performance derives from backhaul problems. When an Operator has no link level
visibility there is no E2E visibility and QoS cannot be ensured. It is therefore essential to have
vendor independent visibility downstream of the aggregation points on a link by link basis to isolate
physical layer faults – e.g. using transparent probes such as the SFProbes™ from JDSU.
Real Time Monitoring
It is also essential for LTE small cell pro-active management to perform traffic monitoring with a
very small response ‘window’ and the ability to guarantee QoS in near real time. Historically many
traditional probes have not continuously monitored real time data but rather created ‘synthetic’
traffic – or ‘pings’ - either at specified intervals or when triggered by network events and operator
requests. These synthetic probes typically send traffic onto the network to ‘sample’ its behavior. In
some instances it is as simple as sending an ICMP ECHO packet (‘ping’), or specific packet streams –
e.g. RFC 2544 or ITU Y.1731, or to transfer synthetic traffic e.g. a sample video or VoIP stream that
‘loops back’ to return traffic statistics. Such techniques are appropriate for turn up testing, before
live services are added to a network, but the non-real-time nature of the information returned
make these approaches less valuable for performance monitoring.
The low latency requirements of LTE signaling and the need for more dynamic proactive
management of small cell traffic loads - either with Self Organizing Networks (SON) or load
management and traffic optimization techniques - demand Real Time Monitoring.
Since the time slot for sampling data must be much shorter than the time frame within which
action must be taken, for LTE the ‘time granularity’ for monitoring key failures or congestion
queues must be a few seconds or even milliseconds, rather than tens of seconds or minutes or even
the hours traditionally spent to do statistical
analysis at the Network Operations Center
(NOC). Network element based probing and
intelligent microprobe based monitoring are
therefore likely to replace statistical correlation
for fault isolation of LTE small cell transport
problems. And live traffic monitoring may
displace synthetic simulation – at least in part.
LTE also offers an opportunity to monetize differences in QoS and provide Service Level Agreements
(SLAs) for enterprise VPNs – similar to those for fixed enterprise and cloud customers – networks
that guarantee specific delay and throughput parameters. To achieve the SLA targets and avoid
penalties an operator must be able to identify, isolate and remedy small cell backhaul problems in
near real time independent of the network equipment used. Real time monitoring therefore
becomes a critical part of the mechanism that guarantees the service. Enterprise SLAs are likely to
become a major revenue source for service providers as small cells are deployed in campuses and
office buildings (See ‘Small Cells Taking Off, Need Fiber Backhaul Soon’).
..Operator must be able to identify, isolate and remedy small cell backhaul problems in near real time independent of the network equipment used
Page 6 of 14, © Strategy Analytics 2014
Neither can the monitoring process itself be allowed to introduce delay as some network element
based probing and flow-based monitoring do. See ‘LTE Network Monitoring - Comparing 6
Approaches for End-to-End visibility, Real Time Response and key Data Analytics’.
Selective Data for Analytics
As the passion for ‘Big Data’ Analytics has grown and operators have focused on E2E Customer
Experience Management (CEM) they have found themselves creating a ‘Tsunami’ of monitoring
data on the signaling channel that could potentially interfere with network performance. Not only
could this huge volume of data clog the network and reduce available capacity but it is becoming
costly to collect and impossible to analyze fast enough to be useful. To address the problem some
operators have imposed blanket filters on monitoring traffic but lost potentially valuable insights as
a result.
Matching Monitoring to Service Requirements
There is therefore a need to match the level of monitoring selectively to both its cost and the value
of the service it supports. In a recent TMForum Webinar JDSU provided examples of three levels
characterized either by Service or Customer parameters with separate policies that select the
different parameters to be monitored for each – See Chart below.
Chart 2. Defining Selective Monitoring Policies by Service or by Customer
Service Level
/Customer Examples Monitoring Parameters
Premium Services VoLTE, Bloomberg
Netflix™
Deep Visibility of Key Performance
Indicators (KPIs)
Top ARPU Customers facebook™, Lync™ Personalized Visibility, KPIs plus
OTT analysis
Low Value Service YouTube™
BitTorrent™
Basic Visibility – Packet Counts and
Usage
Source: ‘A New Paradigm in Customer Experience Assurance for 4G/LTE in the Era of Big Data’
Traffic is growing too fast for the cost of monitoring to be allowed to grow in proportion to the
traffic. Revenue per GB continues to decline and
costs must decline at least as fast. But blanket
filtering is too arbitrary. Value based dynamic
‘selective data monitoring’ is therefore a
preferred way to align monitoring costs with the
value of the revenue generating service. Operator managers should set the policies and then match
them to the network, subscriber or session parameters that are to be tracked. If this is done at least
one case study shows a dramatic reduction in operations costs as shown in the Chart below.
Traffic is growing too fast for the cost of monitoring to be allowed to grow in proportion to the traffic.
Page 7 of 14, © Strategy Analytics 2014
Chart 3. Case Study indicates Significant Cost savings from Selective Data Monitoring
Source: ‘A New Paradigm in Customer Experience Assurance for 4G/LTE in the Era of Big Data’
Selective data monitoring facilitates smarter Customer Experience Management, in part because
customer policies are planned in advance and modified as customer value becomes apparent.
This can lead to savings of over 50 percent in the network Total Cost of Operations (TCO) - as
indicated above - as the new approach impacts different phases of the small cell deployment
lifecycle.
Page 8 of 14, © Strategy Analytics 2014
Monitoring at Different Phases of Small Cell Backhaul Lifecycle
The complexity of a small cell backhaul ecosystem and the relative importance of the different
types of functionality described above can be better understood by looking at the three phases
of the operator’s lifecycle – Planning, Deployment and Activation, Operations and Value
Delivery.
Chart 3 The Three Phases of the Small Cell Backhaul Lifecycle
Phase 1. Plan, Deploy and Activate
This phase includes selecting, planning and optimizing the small cell solutions based on
understanding of customer and network behavior. Backhaul planning and monitoring are an
integral part of small cell deployment and increasingly they are part of the monthly or
quarterly Radio Access Network (RAN) planning process and forecasting of E2E throughput
requirements.
This phase requires automated backhaul service activation followed immediately by E2E
Monitoring to trigger new deployments and test new links as they are installed, with Real
Time testing of the throughput achieved. Policy decisions are also made in this phase to
decide what to Selectively Monitor.
Phase 2. Operate
This phase maintains the dynamic network environment and requires visibility both across the
network and at every node and link to isolate faults. Network, subscriber and session
awareness, monitoring and troubleshooting are principal tasks. Operations demands very
short monitoring response times with the ability to act to optimize live traffic data.
This phase requires E2E Monitoring to trigger alerts related to user performance but
continuous Real Time input is the most basic requirement for the NOC to spot and remedy
failures or growing congestion so that problems can be mitigated within seconds. And the NOC
Page 9 of 14, © Strategy Analytics 2014
will be better positioned to do this fast when only the relevant parameters are selectively
monitored. Real Time monitoring is also essential to monitor Service Level Agreements and
detect violations in order to mitigate any customer problems that would impact revenue.
Phase 3.Deliver Value
After initial network completion operators need to focus on ‘value-based’ monitoring of the
network and service applications with Customer Experience Management (CEM), Customer
Relationship Management (CRM) tools and services. This needs to be done in conjunction with
upstream network and data partners to minimize the number of dissatisfied customers who are
likely to switch to another operator i.e. ‘churn’. This phase focuses on what will positively
impact the ‘bottom line’ e.g. guaranteeing SLAs and premium QoS to generate new revenues.
The idea of monetizing network intelligence is still relatively new but E2E knowledge of the
user experience is essential to Customer Experience Management systems; and Real Time inputs
that lead to problem resolution almost before the customer is aware of it can reduce
expensive churn; while Selective Monitoring driven by Policy can ensure that ‘potentially
customer impacting events’ are given priority handling.
Implications for Operators
Network Operations can Proactively Manage Networks to Improve Margins
Intelligent monitoring e.g. with link-by-link microprobes can provide a means for operators to
simultaneously:
Lower cost of operations
Enable Network Operations Center (NOC) experts to directly impact the ‘bottom line’
Deliver better backhaul performance to reduce churn and improve the operator’s ‘bottom
line’
Add new value from Service Level Agreement (SLA) guarantees, QoS and Priority On-
Demand Services
Increase competitive advantage for their fiber wholesale providers who offer microprobes
We discuss each of these in turn below.
Lower Cost of Operations
Comparing the cost of a complete NID based solution with intelligent microprobes the latter are
significantly less expensive as shown in the chart below. Factored into these comparisons are
savings from operational efficiencies including a reduction in the number of tests required during
backhaul service activation, as well as improved ‘mean time to identify’ during live traffic
performance monitoring.
Page 10 of 14, © Strategy Analytics 2014
Chart 4. Cost Comparison of Implementation of traditional NIDs vs. Microprobes
Source: JDSU ‘Small Cells and the Evolution of Backhaul Assurance’
Enables Network Operations Center (NOC) Experts to impact ‘Bottom Line’
NOC experts are concerned about the increasing complexity of the RAN and the need for Self
Organizing Networks (SON), Network Function Virtualization (NFV) and Software Defined
Networking (SDN). They are finding that the parameters they used to tweak are now transparently
optimized by algorithms or buried by virtualization software and that they must deal with a much
greater level of network element and path abstraction. But these changes also create significant
opportunities for the NOC to enhance the operator’s bottom line.
Agile Network Service Activation
The role of the NOC is changing as operators find opportunities to better monetize their networks.
Intelligent microprobes can deliver key real time network intelligence and greater backhaul
flexibility that enable Network Operations experts to create tools to activate and manage new ‘Agile
Services’ almost instantly faster ‘Time to Market’ and new operator revenues. As the NOC monitors
traffic in real time it helps deliver a locally optimized, value added customer experience for any
service the operator decides to deploy.
Analytics for Subscriber Service Management
As small cell networks add selective monitoring network operators can also focus more efficiently
on the value of the Data Analytics - moving beyond troubleshooting towards managing subscriber
policies that reduce churn to customer monitoring that improves profit margins with service
management e.g. SLA enforcement - grows revenue.
Page 11 of 14, © Strategy Analytics 2014
Chart 5. Microprobes can be optimized E2E to create Service and Revenue Options
Source: JDSU Small Cell Backhaul Solutions
Delivers Better Backhaul Performance to reduce Churn and improve Operator’s Bottom line
As microprobes filter inputs selectively at the
source and deliver near real time status
information to the NOC, problems can be
identified and mitigated before they cascade
across the network. Faster response to pre-
empt ‘potentially customer impacting’
network problems should translate directly
to the mobile operator’s bottom line
There is good historical evidence that poor
backhaul network performance leads to user churn. Surveys have indicated that - depending on the
region - between 14% and 40% of mobile customers will list poor network service as a major
reason for leaving an operator; and it is estimated that inadequate backhaul capacity and poor
quality backhaul are responsible for approximately 50% of network performance problems.
Strategy Analytics estimates that investment in better backhaul could reduce a Mobile Operator’s
churn rate by between 4 and 7 percent depending on the Region – a net reduction in churn of 1.2
to 2.1 percent. A direct impact on the Operator’s bottom line. The Chart below shows the estimated
percentage impact on revenues and margins for a typical operator in a region.
Inadequate backhaul capacity and poor quality backhaul are responsible for approximately 50% of network performance problems. ….And poor network service is responsible for 14 – 40% of churn depending on the operator
Page 12 of 14, © Strategy Analytics 2014
Chart 6. Percent Revenue Retained if Poor Performance is reduced for Typical Operator in a
Region. Note: Payback for Churn Reduction is cumulative over time
Saved Service Revenue % 2014 2015 2016 2017
W Europe 2.4% 3.5% 4.4% 5.1%
C/E Europe 2.3% 3.3% 3.9% 4.4%
N America 2.4% 3.5% 4.4% 5.0%
C/L America 1.7% 2.4% 2.9% 3.2%
Asia-Pacific 1.8% 2.5% 3.0% 3.3%
M East/Africa 1.4% 2.0% 2.5% 2.8%
Total Worldwide All Regions 2.0% 2.9% 3.5% 3.9%
Source: Strategy Analytics ‘Closing the Mobile 'Backhaul Gap' will Improve Profit Margins’
The revenue impact of improved customer retention as a result of better backhaul performance can
have a significant impact on an operator’s bottom line.
Adds New Value from Service Level Agreement (SLA) guarantees and Priority On-Demand Services
Intelligent microprobes allow operators to move from passive network monitoring to pro-active
performance management without impacting the user experience by overburdening the network
with analytics traffic. This is critical to support key new mobile sources of revenue:
Enterprise SLAs for Seamless Mobile and Fixed VPNs
Premium Differentiated Classes of Service with guaranteed E2E Quality of Service (QoS)
e.g. for Video Conferencing
On-Demand Service Priority e.g. for temporary high priority delivery of content
Increased Competitive Advantage for Fiber Transport Providers who deploy Microprobes and reduce Total Cost of Operations (TCO) for their Operator customers
Fiber Transport providers who make an initial capital investment in microprobes as they deploy new
fiber should find themselves in a position to offer differentiated and more cost competitive fiber
leases to Mobile Operators who in turn will reduce their long run Total Cost of Operations (TCO).
If Mobile Operators demand that backhaul providers implement intelligent microprobes as part of
their certification requirements, fiber transport providers who implement them could have a
significant competitive advantage.
With the right small cell monitoring and management tools for small cell backhaul operators can
reduce costs, minimize revenue losses from churn and add value with premium services.
Page 13 of 14, © Strategy Analytics 2014
Benefits of an Intelligent Microprobe Solution
One example of an intelligent microprobe solution is JDSU’s PacketPortal™ Small Cell Assurance
solution which provides the three essential E2E, Real Time and Selective Monitoring functional
capabilities. These support the management and monetization of small cell backhaul to:
Significantly reduce CAPEX costs with streamlined backhaul service activation and
transparent real time monitoring on a link-by-link basis
Lower Total Cost of Network Operations with smarter, faster responses by Network
Operations despite the escalation of small cell numbers and complexity at the edge of the
RAN
Add Value for Premium SLAs, Priority Services and QoS by focusing on real-time
monitoring and analytics of subscriber data selected by value at the source, and integrated
with third party Customer Experience Management (CEM) and Policy Control (PCRF).
Conclusions
As mobile data demands escalate, LTE small cells will become an integral part of operators’ network
rollout. The advent of LTE-Advanced Carrier Aggregation and small cells for high-traffic urban and
indoor scenarios will push small cell backhaul over the ‘Fiber Threshold’. See ‘Small Cells Taking
Off, Need Fiber Backhaul Soon’.
Small cells will multiply the complexity and processing required at edge of the network by a factor
of 10X or more and backhaul capacity must increase dramatically as self-organizing ‘clusters’ and
‘meshier’ network topologies evolve. New mechanisms are required to streamline backhaul service
activation and pro-actively monitor and manage these networks.
One solution is JDSU’s ‘Small Cell Assurance Solution’ that embeds microprobes as part of
deployment in each segment of a mobile backhaul network. Lower layer monitoring maximizes end-
to-end visibility with the probes deployed on the closest fiber and enables basic monitoring even of
‘IPsec’ secure tunnels. JDSU’s PacketPortal platform forwards microprobe packets in real-time for
analysis and routing to the relevant Customer
Experience Management (CEM) engines for
processing.
As small cell networks evolve a selective, real- time
monitoring capability like that provided by this
solution will allow mobile operators and especially their Network Operations organizations to focus
on the value of their data, and the optimization of their policy rules to maximize both network
utilization and their customers’ experience.
Mobile Operators should consider including microprobe monitoring as a certification requirement for their infrastructure suppliers
Page 14 of 14, © Strategy Analytics 2014
In this new LTE world it is essential for operators to move away from passive monitoring to
proactive ‘Assurance and Analytics’ tightly coupled to network management and service delivery.
This requires
End to End(E2E) visibility for service continuity assurance, based on inputs across the
network
Cost effective Real Time Performance Monitoring and troubleshooting
Selective Monitoring and Data Capture driven by Policy for each Service, Subscriber or
Network link to be monitored - done in a way that does not degrade network performance
in an open, multivendor vendor ecosystem
With these capabilities the NOC can expand its role as a direct contributor to the operator’s
bottom line even as TCO is reduced. JDSU is
setting a ‘de facto’ standard for operator
controlled selective monitoring, with
intelligent microprobes that measure and
capture all the data required for fast Network
Activation and complete Network
Operations visibility to guarantee the
End-to-End customer experience.
Mobile Operators should consider including
microprobe monitoring as a certification requirement for their transport infrastructure suppliers
to accelerate deployment, lower response time and reduce customer dissatisfaction.
Contact the author of this report:
To explore this topic in more detail or to hear how our solutions (Workshops, Presentations,
Consulting engagements, annual multi-client services) can support you please visit
www.strategyanalytics.com/solutions.html
If you have inquiry privileges please contact the author of this report Sue Rudd at
NOC can expand its role as a direct contributor to the operator’s bottom line even as TCO is reduced……….. Mobile Operators should consider including microprobe monitoring as a certification requirement for their transport infrastructure suppliers
