An Energy-Aware Adaptation Model for Big Data Platforms
2016 (English)In: 2016 IEEE International Conference on Autonomic Computing (ICAC) / [ed] IEEE, IEEE, 2016, 349-350 p.Conference paper (Refereed)
Platforms for big data includes mechanisms and tools to model, organize, store and access big data (e.g. Apache Cassandra, Hbase, Amazon SimpleDB, Dynamo, Google BigTable). The resource management for those platforms is a complex task and must account also for multi-tenancy and infrastructure scalability. Human assisted control of Big data platform is unrealistic and there is a growing demand for autonomic solutions. In this paper we propose a QoS and energy-aware adaptation model designed to cope with the real case of a Cassandra-as-a-Service provider.
Place, publisher, year, edition, pages
IEEE, 2016. 349-350 p.
Big Data;fault tolerant computing;power aware computing;quality of service;resource allocation;Amazon SimpleDB;Apache Cassandra;Big Data platforms;Cassandra-as-a-Service provider;Dynamo;Google BigTable;Hbase;energy-aware adaptation model;human assisted control;infrastructure scalability;multitenancy;resource management;Adaptation models;Big data;Cloud computing;Optimization;Runtime;Scalability;Throughput;Apache Cassandra;Autonomic computing;Big Data;Cloud computing;Green computing
IdentifiersURN: urn:nbn:se:bth-13669DOI: 10.1109/ICAC.2016.13ISI: 000390681200054ISBN: 978-1-5090-1654-9OAI: oai:DiVA.org:bth-13669DiVA: diva2:1059892
IEEE International Conference on Autonomic Computing (ICAC), Würzburg