Publication Details
Scheduling Decisions in Stream Processing on Heterogeneous Clusters
Škoda Petr, RNDr. (DCGM FIT BUT)
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT)
scheduling; resource-awareness; benchmarking; heterogeneous clusters; stream processing; Apache Storm
Stream processing is a paradigm evolving in response to well-known limitations of widely adopted MapReduce paradigm for big data processing, a hot topic of today's computer world. Moreover, in the field of computation facilities, heterogeneity of data processing clusters, intended or unintended, is starting to be relatively common. This paper deals with scheduling problems and decisions in stream processing on heterogeneous clusters. It brings an overview of current state of the art of stream processing on heterogeneous clusters with focus on resource allocation and scheduling. Basic scheduling decisions are discussed and demonstrated on naive scheduling of a sample application. The paper presents a proposal of a novel scheduler for stream processing frameworks on heterogeneous clusters, which employs design-time knowledge as well as benchmarking techniques to achieve optimal resource-aware deployment of applications over the clusters and eventually better overall utilization of the cluster.
@INPROCEEDINGS{FITPUB10569, author = "Marek Rychl\'{y} and Petr \v{S}koda and Pavel Smr\v{z}", title = "Scheduling Decisions in Stream Processing on Heterogeneous Clusters", pages = "614--619", booktitle = "2014 Eighth International Conference on Complex, Intelligent and Software Intensive Systems", year = 2014, location = "Birmingham, GB", publisher = "IEEE Computer Society", ISBN = "978-1-4799-4325-8", doi = "10.1109/CISIS.2014.94", language = "english", url = "https://www.fit.vut.cz/research/publication/10569" }