A Comparison of Allocation Algorithms for Partially Replicated Databases
- Increasing demand for analytical processing capabilities can be managed by replication approaches. However, to evenly balance the replicas' workload shares while at the same time minimizing the data replication factor is a highly challenging allocation problem. As optimal solutions are only applicable for small problem instances, effective heuristics are indispensable. In this paper, we test and compare state-of-the-art allocation algorithms for partial replication. By visualizing and exploring their (heuristic) solutions for different benchmark workloads, we are able to derive structural insights and to detect an algorithm's strengths as well as its potential for improvement. Further, our application enables end-to-end evaluations of different allocations to verify their theoretical performance.
| Author details: | Stefan Halfpap, Rainer SchlosserORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1109/ICDE.2019.00226 |
| ISBN: | 978-1-5386-7474-1 |
| ISBN: | 978-1-5386-7475-8 |
| ISSN: | 1084-4627 |
| ISSN: | 2375-026X |
| ISSN: | 1063-6382 |
| Title of parent work (English): | 2019 IEEE 35th International Conference on Data Engineering (ICDE) |
| Publisher: | IEEE |
| Place of publishing: | New York |
| Publication type: | Other |
| Language: | English |
| Year of first publication: | 2019 |
| Publication year: | 2019 |
| Release date: | 2021/05/05 |
| Number of pages: | 4 |
| First page: | 2008 |
| Last Page: | 2011 |
| Organizational units: | Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH |
| DDC classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke |
| Peer review: | Referiert |
