FutureWorks Nokia technology vision 2020: personalize the network experience. Executive Summary. Nokia Networks

Size: px

Start display at page:

Download "FutureWorks Nokia technology vision 2020: personalize the network experience. Executive Summary. Nokia Networks"

Andrea McDonald
8 years ago
Views:

1 Nokia Networks FutureWorks Nokia technology vision 2020: personalize the network experience Executive Summary White paper - Nokia Technology Vision 2020: Personalize the Network Experience

2 CONTENTS Aligning resources, revenues and experience 3 to increase operator profitability In Telco data is not big it s colossal 4 and mostly real time Telco scale big data driving actions at the speed 5 of the user Turning the vast amounts of signaling data into 5 immediate business value Nokia s telco scale big data technology 7 Page 2

scale big data driving actions at the speed 5 of the user Turning the vast amounts

3 Aligning resources, revenues and experience to increase operator profitability When asked about the key optimization problem from a business perspective, a typical operator s answer may be: How do I provide best experience for my customers, ensure my limited network resources are well utilized and maximize my revenues all at the same time? The rapidly growing diversity of applications, devices and sensors and the fact that network quality is becoming the fundamental asset of competing operators demands a solution that can simultaneously meet all these objectives. A system that sees everything happening across the network, looks at user and business data and processes the information accordingly is therefore essential. As part of its Technology Vision 2020, Nokia is meeting the challenge with its Personalize network experience approach. Building on cognitive networks Personalize network experience is the other side of our cognitive networks approach. The first side is about teaching networks to be self aware (launched in January 2014) which is about networks that autonomously sense, learn and optimize themselves. Such a self aware network is enabled by big data analytics, machine learning and automation. The same technologies can be used to even optimize the experience of individual customers. Ultimately, Self-Organizing Networks (SON) and Customer Experience Management (CEM) capabilities will evolve into a Cognitive Network which will autonomously handle these complex analytical tasks. Machine learning will further improve the knowledge base and accuracy of decision making and actions over time. Page 3

The rapidly growing diversity of applications, devices and sensors and the fact that network quality is becoming the fundamental asset of competing operators demands a solution that can

4 In Telco data is not big it s colossal and mostly real time Telecom networks today generate not just big data, but colossal amounts of data every second. A wireless network with 10 million subscribers creates about one million transactions per second (tps) during peak hours. For comparison: VISA generates about 18,500 tps and Twitter produces about 143,000 tps. Every time a subscriber s device interacts with the network signaling data points are generated. Taking the entire subscriber base and network into account this adds up to a large volume and variety of data produced every second at high velocity. All this data needs to be checked by an analysis engine for its veracity. Nokia advocates the use of big data analytics to translate the volume, variety, velocity and veracity of big data into business value. What if it was possible to use all this data in real-time, correlate it with customer data and act on it immediately? The aim of Personalize network experience is to make these possibilities reality by building a telco-scale engine that captures all signaling data across the network, looks at user and business data and processes the information accordingly. Big data related technologies enhanced by machine learning and artificial intelligence and applied to telco environments help analyze this colossal amount of raw network data. Doing this quickly makes it possible to propose meaningful actions. Wireless network Twitter 143,000 1,000,000 Transactions per second (country of 10M people) Unique footprint Massive network data Every second in real-time Verified for accuracy Music most popular in the mornings QoE equals user policy Video quality links to coverage Visa 18,500 Variety Volume Velocity Veracity In Telco data is not big it s colossal and most of it is real-time Page 4

For comparison: VISA generates about 18,500 tps and Twitter produces about 143,000 tps. Every time a subscriber s device interacts with the network signaling data points are generated.

5 Telco scale big data driving actions at the speed of the user Once data has been analyzed, it needs to be acted upon. Typical actions are: Automated, real-time correction of service affecting faults Predictive performance, such a providing consistent video experience for a high value user along a travel route Dynamically detecting & adapting the network to sudden usage changes Dynamically altering policy & radio settings based on user value Such actions can be split into three broad, time-based categories: Instant action a reflex of the network, examples are re-routing and interference cancellation. Immediate action typically taken between some seconds and minutes to improve the performance of an application or to provide customer care agents with insight into arising situations. Longer term action from minutes to hours or days or even longer. These include longer term actions such as proactively adjusting the network performance by time of day based on the travel and service usage pattern of high value business commuters. Turning the vast amounts of signaling data into immediate business value Personalize network experience all comes down to profitability: 1. Exponential growth of data traffic can better be monetized by differentiation of traffic, users and offerings. 2. Churn of high ARPU customers can be lowered as network and service experience accounts for 30 to 40% of the loyalty of mobile users. 3. Different traffic streams can be much better handled according to their different requirements. This will get more and more important as the variety of different traffic patterns will increase with new applications such as machine-to-machine and HD video services. Meanwhile, subscribers will enjoy a more consistent experience as the network dynamically optimizes itself to serve each individual s connectivity requirements. Page 5

Dynamically detecting & adapting the network to sudden usage changes Dynamically altering policy & radio settings based on user value Such actions can be split into three broad, time-based

6 Operators would be empowered to combine any type of network, session, customer and business data to personalize the end user s network experience to optimize revenues, costs and available resources for higher profitability. Nokia s telco scale big data technology Nokia s FutureWorks innovation project Retina overcomes the most critical challenge of telco big data - scaling up processing capacity linearly as the volume of data grows. Through parallel computing and a virtualized architecture, Retina can handle massive volumes of telco big data in real time, with no theoretical capacity limit. In life networks it has already processed one million messages per second, reflecting the peak hour data volume of a 3G network with 10 million subscribers in a life network. Page 6

Nokia s telco scale big data technology Nokia s FutureWorks innovation project Retina overcomes the most critical challenge of telco big data - scaling up processing capacity linearly as the

7 Nokia is a registered trademark of Nokia Corporation. Other product and company names mentioned herein may be trademarks or trade names of their respective owners. Nokia Solutions and Networks Oy P.O. Box 1 FI Finland Visiting address: Karaportti 3, ESPOO, Finland Switchboard Product code C ES EN Nokia Solutions and Networks 2014

respective owners. Nokia Solutions and Networks Oy

Business aware traffic steering

Nokia Networks Business aware traffic steering Nokia Networks white paper Business aware traffic steering Contents 1. Executive Summary 3 2. Static load or QoS-based traffic steering alone is no longer