Query optimization for parallel execution
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
The state of the art in distributed query processing
ACM Computing Surveys (CSUR)
Optimization of parallel query execution plans in XPRS
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Selection of Views to Materialize in a Data Warehouse
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Parallel Query Scheduling and Optimization with Time- and Space-Shared Resources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Automated Selection of Materialized Views and Indexes in SQL Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Publish/Subscribe Tree Construction in Wireless Ad-Hoc Networks
MDM '03 Proceedings of the 4th International Conference on Mobile Data Management
Dynamic Load Management for Distributed Continuous Query Systems
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Dynamic Load Distribution in the Borealis Stream Processor
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Fault-tolerance in the Borealis distributed stream processing system
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Declarative networking: language, execution and optimization
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Impact of multi-query optimization in sensor networks
DMSN '06 Proceedings of the 3rd workshop on Data management for sensor networks: in conjunction with VLDB 2006
Network-aware query processing for stream-based applications
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Database research opportunities in computer games
ACM SIGMOD Record
Value-based notification conditions in large-scale publish/subscribe systems?
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
SODA: an optimizing scheduler for large-scale stream-based distributed computer systems
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Minimizing Communication Cost in Distributed Multi-query Processing
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Feeding frenzy: selectively materializing users' event feeds
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Walking in facebook: a case study of unbiased sampling of OSNs
INFOCOM'10 Proceedings of the 29th conference on Information communications
Feed following: the big data challenge in social applications
Databases and Social Networks
SQPR: Stream query planning with reuse
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Accurate latency estimation in a distributed event processing system
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Multi-query optimization for sensor networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Towards expressive publish/subscribe systems
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Shepherding social feed generation with Sheep
Proceedings of the Fifth Workshop on Social Network Systems
RACE: real-time applications over cloud-edge
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
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In feed-following applications such as Twitter and Facebook, users (consumers) follow a large number of other users (producers) to get personalized feeds, generated by blending producers- feeds. With the proliferation of Cloud-connected smart edge devices such as smartphones, producers and consumers of many feed-following applications reside on edge devices and the Cloud. An important design goal of such applications is to minimize communication (and energy) overhead of edge devices. In this paper, we abstract distributed feed-following applications as a view maintenance problem, with the goal of optimally placing the views on edge devices and in the Cloud to minimize communication overhead between edge devices and the Cloud. The view placement problem for general network topology is NP Hard; however, we show that for the special case of Cloud-edge topology, locally optimal solutions yield a globally optimal view placement solution. Based on this powerful result, we propose view placement algorithms that are highly efficient, yet provably minimize global network cost. Compared to existing works on feed-following applications, our algorithms are more general--they support views with selection, projection, correlation (join) and arbitrary black-box operators, and can even refer to other views. We have implemented our algorithms within a distributed feed-following architecture over real smartphones and the Cloud. Experiments over real datasets indicate that our algorithms are highly scalable and orders-of-magnitude more efficient than existing strategies for optimal placement. Further, our results show that optimal placements generated by our algorithms are often several factors better than simpler schemes.