An energy-aware adaptation model for Big Data platforms

被引：2

作者：

Casalicchio, Emiliano ^{[1
]}

Lundberg, Lars ^{[1
]}

Shirinbad, Sogand ^{[1
]}

机构：

[1] Blekinge Inst Technol, Dept Comp Sci & Engn, Karlskrona, Sweden

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING (ICAC) | 2016年

关键词：

Autonomic computing; Cloud computing; Green computing; Apache Cassandra; Big Data;

D O I：

10.1109/ICAC.2016.13

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：349 / 350

页数：2

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