CELLIQ: REAL-TIME CELLULAR NETWORK ANALYTICS AT SCALE Anand Padmanabha Iyer, Li Erran Li, Ion Stoica

Presenter: Chenqi Zhou, Yuhan Xu

WHY IMPORTANT?Cellular network operators collect large volume

of information about the network and user traffic

Provide crucial insights in network planning (e.g., deployment of new base stations), network operation (e.g., improving utilization

of limited radio resources by interference coordination), etc

Ensure satisfactory end-user experience

analysis

MAIN CONTRIBUTION

Proposed CellIQ—a system for real-timecellular network analytics that supports rich analysis tasks efficiently by leveraging domain-specific optimizations

CURRENT WORK

Periodically generate thousands of predefined reports available in a

dashboard

Handoffs at network elements

Radio resource usage

Associated base

stations

State-of-the-art Cellular Analytics Systems

Timely and more sophisticated analyses

l Detecting and monitoring spatio-temporal hotspots

l Tracking popular handoff sequences with abnormal failure rate

Improvement:

CELLIQlKey insight: cellular network data is naturally

represented as a time-evolving graphlLeverages domain specific characteristics of cellular

networks—its spatial and temporal locality—to achieve efficient analysis

lCapable of running sophisticated tasks including detection and tracking of spatial and temporal traffic hotspots, and popular handoff sequences with abnormal failures

STRUCTURElBackground

lChallenges & Solution Overview

lCellIQ System

lCellIQ Realization and Optimization

lCellIQ Performance and Evaluation

lConclusion and Future work

BACKGROUND

Data collected:• Bearer and Signaling

Records • TCP Flow Records • Network Element

Records

LTE Architecture

CHALLENGESThree broad tasksüContinuous monitoring of connections and entities üReal time detection of spatial and temporal patterns üReal time troubleshooting to identify root causes

Performing these tasks in real-time can be very challenging!

THREE OPERATIONS• Sliding Window

Operations − Persistent hotspot tracking per

sliding window

• Time Window Operations − Popular handoff sequence

tracking per time window

• Spatial Operations − Top traffic gradients tracking

SOLUTIONLeveraging cellular specific optimizations exploiting spatial and temporal locality:• Data placement • Radius based message broadcast • Spatial aggregation • Differential graph updates • Incremental graph updates

CELLIQ SYSTEM-GRAPH PARTITIONING

Graph computation frameworks rely on partitioningto minimize communication & balance computation

• vertex-cut strategy: avoid replicating edges• geo-partitioning technique: place edges to preserve spatial locality

CELLIQ SYSTEM-GRAPHREPRESENTATION

CELLIQ SYSTEM-COMPUTATION MODEL:

G-STREAMS

CELLIQ REALIZATION AND OPTIMIZATION

• 1. GeoGraph Computational Model

• 2. Gstream Computational Model

• 3. Co-partition Component Graphs

• 4. Indices and Routing Tables

GEOGRAPH API：1.RADIUS BASED MESSAGE

BROADCAST

1.RADIUS BASED MESSAGEBROADCAST

TRACKING USER TRAFFIC GRADIENTS

GEOGRAPH API：2. SPATIAL AGGREGATION

2. SPATIAL AGGREGATIONTO REALIZE

SPATIAL CLUSTERING

GSTREAM API

GSTREAM APITRACKING PERSISTENT HOTSPOTS

GOAL: DETECT AND TRACK GROUPS OF BASE STATIONS WITH HIGH TRAFFIC VOLUME

CO-PARTITION COMPONENT GRAPHS

INDICES AND ROUTING TABLES

CELLIQ EVALUATION AND PERFORMANCE

CELLIQ EVALUATION AND PERFORMANCE

CELLIQ EVALUATION AND PERFORMANCE

CELLIQ EVALUATION AND PERFORMANCE

CELLIQ EVALUATION AND PERFORMANCE

CONCLUSION AND FUTUREWORK

• Conclusion:CellIQ is a cellular network analytics system that uses domain-specific optimizations to achieve 2x to 5x improvements

• Future Work:• Using techniques in CellIQ to perform root-cause

analysis on operational LTE Networks• Generalized streaming graph analysis techniques