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CellIQ : Real-Time Cellular Network Analytics at Scale

Authors: 

Anand Padmanabha Iyer, University of California, Berkeley; Li Erran Li, Bell Labs; Ion Stoica, University of California, Berkeley

Abstract: 

We present CellIQ, a real-time cellular network analytics system that supports rich and sophisticated analysis tasks. CellIQ is motivated by the lack of support for realtime analytics or advanced tasks such as spatio-temporal trac hotspots and hando sequences with performance problems in state-of-the-art systems, and the interest in such tasks by network operators. CellIQ represents cellular network data as a stream of domain specific graphs, each from a batch of data. Leveraging domain specific characteristics—the spatial and temporal locality of cellular network data—CellIQ presents a number of optimizations including geo-partitioning of input data, radiusbased message broadcast, and incremental graph updates to support ecient analysis. Using data from a live cellular network and representative analytic tasks, we demonstrate that CellIQ enables fast and ecient cellular network analytics—compared to an implementation without cellular specific operators, CellIQ is 2x to 5x faster.

Anand Iyer, University of California, Berkeley

Li Erran Li, Bell Labs

Ion Stoica, University of California, Berkeley

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