RACE: real-time applications over cloud-edge

Authors:
Badrish Chandramouli;Joris Claessens;Suman Nath;Ivo Santos;Wenchao Zhou
Affiliations:
Microsoft Research, Redmond, WA, USA;Microsoft Research, Aachen, Germany;Microsoft Research, Redmond, WA, USA;Microsoft Research, Aachen, Germany;University of Pennsylvania, Philadelphia, PA, USA
Venue:
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Year:
2012

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Abstract

The Cloud-Edge topology - where multiple smart edge devices such as phones are connected to one another via the Cloud - is becoming ubiquitous. We demonstrate RACE, a novel framework and system for specifying and efficiently executing distributed real-time applications in the Cloud-Edge topology. RACE uses LINQ for StreamInsight to succinctly express a diverse suite of useful real-time applications. Further, it exploits the processing power of edge devices and the Cloud to partition and execute such queries in a distributed manner. RACE features a novel cost-based optimizer that efficiently finds the optimal placement, minimizing global communication cost while handling multi-level join queries and asymmetric network links.