Paper Info
Title
Cloudy: heterogeneous middleware for in time queries processing
Abstract
Parallel share-nothing architectures are currently used to handle large amounts of data arriving in real-time for processing. The continuous increase on data volume and organization, introduce several limitations to scalability and quality of service (QoS) due to processing requirements and joins. Parallelism may improve query performance, however some business require timely results (results not faster or slower than specified) which, even with additional parallelism and significant upgrade costs (both monetary and due to disturbance of normal operations), cannot be guaranteed. We propose a timely-aware execution architecture, Cloudy, which balances data and queries processing among an elastic set of non-dedicated and heterogeneous nodes in order to provide scale-out performance and timely results, nor faster or slower, using both Complex Event Processing (CEP) and database (DB). Data is distributed by nodes accordingly with their hardware characteristics, then a set of layered mechanisms rearrange queries in order to provide in timely results. We present experimental evaluation of Cloudy and demonstrate its ability to provide timely results.
Year
DOI
Venue
2013
10.1145/2513591.2513659
IDEAS
Keywords
DocType
Citations 
additional parallelism,experimental evaluation,hardware characteristic,continuous increase,query performance,heterogeneous middleware,timely result,scale-out performance,processing requirement,complex event processing,data volume,scalability,architecture
Conference
0
PageRank 
References 
Authors
0.34
22
3
Name
Order
Citations
PageRank
Pedro Martins18524.21
Maryam Abbasi282.87
Pedro Furtado320455.67