Adaptive rate stream processing for smart grid applications on clouds

Authors:
Yogesh Simmhan;Baohua Cao;Michail Giakkoupis;Viktor K. Prasanna
Affiliations:
University of Southern California, Los Angeles, CA, USA;University of Southern California, Los Angeles, CA, USA;University of Southern California, Los Angeles, CA, USA;University of Southern California, Los Angeles, CA, USA
Venue:
Proceedings of the 2nd international workshop on Scientific cloud computing
Year:
2011

Citing 9
Cited 3

Congestion avoidance and control

SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
TelegraphCQ: continuous dataflow processing

Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Static optimization of conjunctive queries with sliding windows over infinite streams

SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
A survey of application layer techniques for adaptive streaming of multimedia

Real-Time Imaging
The CQL continuous query language: semantic foundations and query execution

The VLDB Journal — The International Journal on Very Large Data Bases
Memory-limited execution of windowed stream joins

VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
IBM infosphere streams for scalable, real-time, intelligent transportation services

Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Towards optimising distributed data streaming graphs using parallel streams

Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Towards Reliable, Performant Workflows for Streaming-Applications on Cloud Platforms

CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

Adaptive optimization for multiple continuous queries

Data & Knowledge Engineering
End-to-End QoS on Shared Clouds for Highly Dynamic, Large-Scale Sensing Data Streams

CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Revenue-Based resource management on shared clouds for heterogenous bursty data streams

GECON'12 Proceedings of the 9th international conference on Economics of Grids, Clouds, Systems, and Services

Quantified Score

Hi-index	0.00

Visualization

Abstract

Pervasive smart meters that continuously measure power usage by consumers within a smart (power) grid are providing utilities and power systems researchers with unprecedented volumes of information through streams that need to be processed and analyzed in near realtime. We introduce the use of Cloud platforms to perform scalable, latency sensitive stream processing for eEngineering applications in the smart grid domain. One unique aspect of our work is the use of adaptive rate control to throttle the rate of generation of power events by smart meters, which meets accuracy requirements of smart grid applications while consuming 50% lesser bandwidth resources in the Cloud.