Presented on July 1, 2013, at the Distributed Event-Based Systems (DEBS) 2013 Conference: http://www.orgs.ttu.edu/debs2013/index.php

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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
Networ
k
Data
Centers
Data
Centers
QoS
Management
System
Networ
k
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
GW3G Access
AP
GW4G/LTE
AP
GWWiFi
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