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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
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