Mobile QoS Management using Complex Event Processing

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Mobile QoS Management using Complex Event Processing

Distributed Event-Based Systems (DEBS) 2013 Conference Mauricio Arango July 1, 2013

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Mobile Quality of Service Management

•  This work focuses on quality of mobile broadband data services

•  Key performance indicators (KPIs) include: –  Transaction latency –  Input and output throughput

•  Involves monitoring and detection & resolution of performance issues

Network Data

Centers Data

Centers

QoS Management

System

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Mobile Network Quality of Service User experience-driven trend •  Success of mobile applications largely depends on performance

perceived by end-users •  Involves device-based monitoring vs. network-only monitoring •  Very large scale of monitoring and analysis – from from 10s of

thousands network elements to 10s of millions devices •  Mobile networks are large-scale sensor networks – mobile

devices are sensors

Network

Data Centers Data

Centers

QoS Management

System

Network

Data Centers Data

Centers

QoS Management

System

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Mobile Network Quality of Service Near real-time trend

•  High end-user performance requires end-to-end QoS monitoring and management, involving: –  Device-based apps –  Network –  Data center/cloud-based apps

•  Mobile networks are massive dynamic systems – constantly reconfiguring –  Requires rapid response to dynamic user context, application

context, network conditions

•  Proactive identification and correction of problems impacting user experience

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WiFi Offload for QoS Management •  Switch devices from mobile networks to carrier-based WiFi

networks •  Mitigate or avoid congestion

GW 3G Access AP

GW 4G/LTE AP

GW WiFi AP

Core Network

Internet

QoS Management

with WiFi Offload

Network Provisioning & Management

Subscriber Information

Event & control flows

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CEP-based QoS Management with WiFi Offload Application description

•  Input events: –  Device-based measurements

•  Transaction latency •  Bandwidth capacity usage per transaction

–  Data center transaction latency measurements

•  Detect: –  Devices experiencing high-network latency (QoS problem)

•  Infer: –  Congested base stations (QoS problem) –  Device speed (mobility state)

•  Actions - for every device: –  If device network latency is high AND –  Device is in a congested base station AND –  Device is static THEN

•  Offload to closest available WiFi hotspot (QoS solution)

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Implementation Architecture

Oracle OEP

MASON multi-agent simulation

toolkit

Oracle WLS Oracle MapViewer

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CEP Application – QoS Management Event Processing Network

QoS problem detection – Qos solution: WiFi

offload

Input streams merge and enrichment

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Input stream correlation and enrichment

Join device stream with mobile base station table

Join device stream with data center

stream

Derive device speed from

location stream

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Device speed calculation from location stream

•  Partition stream, one stream per device

•  Determine device’s mobility state: static or moving

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QoS Problem Detection & QoS Solution: WiFi Offload

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Geospatial processing and CEP

•  Mobile QoS management is a location-based application

•  Processing highly simplified with use of a geospatial library integrated with CEP platform

•  Oracle Event Processing library –  Input events and internal events mapped to a geospatial grid –  Simplified definition of queries involving location, eg: •  Nearest neighbor •  Distance •  Inclusion within boundary

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Map-based Web Application

High-latency and congestion rendering

WiFi offload rendering

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Future work

•  Predictions – mobile network infrastructure is becoming more more reconfigurable; predict congestion & react on time: –  Identify boundaries around high density areas – city, centers,

airports, stadiums, etc and obtain early predictions of the load that is heading towards them.

–  Identification of the speed, intensity, direction of load movement – location and time to congestion

•  Map location of points where WiFi offload would be required –  For carriers planning to deploy WiFi offload, measure events

where there were congestion/service issues that could be solved by offload.

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Future work – cont.

•  Interactions with other infrastructure systems, eg. transportation, power utilities –  Receive key events from them –  Provide key events to them – congestion near airport,

congestion in part of city

•  Interactions with services systems and the environment: –  Weather –  Sports –  Media programming

•  Privacy is a fundamental issue: –  All of above can be and should done with anonymized data

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Key Messages

•  Event processing and CEP platforms simplify development of real-time monitoring and management systems for mobile communications, requiring: –  Monitoring and tracking location context of very large

numbers of moving and reconfigurable components –  Very high scalability

•  Geospatial processing is a key requirement for CEP platforms supporting location-based applications

•  Mobile monitoring intersects with and can benefit other infrastructure systems