Title
Online Scheduling and Interference Alleviation for Low-Latency, High-Throughput Processing of Data Streams.
Abstract
Data Streams occur naturally in several observational settings and often need to be processed with a low latency. Streams pose unique challenges: they have no preset lifetimes, the traffic on these streams may be bursty, and data arrival rates on these streams can be quite high. Furthermore, stream processing computations are generally stateful where the outcome of processing a data stream packet ...
Year
DOI
Venue
2017
10.1109/TPDS.2017.2723403
IEEE Transactions on Parallel and Distributed Systems
Keywords
Field
DocType
Interference,Resource management,Processor scheduling,Throughput,Optimal scheduling,Scheduling,Clustering algorithms
Data stream mining,Job shop scheduling,Fair-share scheduling,Scheduling (computing),Data stream,Computer science,Network packet,Real-time computing,Dynamic priority scheduling,Stream processing,Distributed computing
Journal
Volume
Issue
ISSN
28
12
1045-9219
Citations 
PageRank 
References 
4
0.41
31
Authors
5
Name
Order
Citations
PageRank
Thilina Buddhika191.89
Ryan Stern240.74
Kira Lindburg340.41
Kathleen Ericson4503.82
Shrideep Pallickara583792.72