University of StuttgartUniversitätsstr. 3870569 StuttgartGermany

Phone +49-711-685 88337 Fax +49-711-685 88472

ResearchResearch

Santiago Gómez Sáez, Vasilios Andrikopoulos, Frank Leymann, and Steve StrauchInstitute of Architecture of Application Systems

{gomez-saez, andrikopoulos, leymann, strauch}@iaas.uni-stuttgart.de

Evaluating Caching Strategies for Cloud Data Access using an

Enterprise Service Bus

IEEE IC2E 2014

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Agenda

Motivating Scenario CDASMix Architecture & Realization Evaluation Conclusion and Future Work

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Motivating Scenario

Presentation Layer

Application

Business Layer

SQL

Data Access Layer

SQL

Data Access LayerCloud-Enabled Data Access Layer

SQL

Registry

Public Cloud Public CloudTraditional

Application Layers

DeploymentModels

Assumptions Database layer has already been

migrated Focus on Relational Databases

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CDASMix - Architecture

Presentation

BusinessLogic

Resources

Web Service API

Configuration Registry Manager

Tenant Registry Manager

Service Registry Manager

JBI Container Manager

Service Assembly Manager

Service RegistryDatabase Cluster

ConfigurationRegistry Database

JBI ContainerInstance Cluster

Access Layer

Web UI

Tenant RegistryDatabase

Message Broker

(1) Strauch et al.: Transparent Access to Relational Databases in the Cloud Using a Multi-tenant ESB. CLOSER’14 (2) ESBMT Project: www.iaas.uni-stuttgart.de/esbmt/

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CDASMix – Cloud Data Access ESB Instance

OSGi Environment

JBI Environment

Standardized Interfaces for Service Engines

Standardized Interfaces for Binding Components

Normalized Message Router

External Application

SMX-Camel-mt

MySQL Proxy

SMX-Camel

Camel cdasmixJDBC

Backend Cloud Data Store Provider

Legend

Message Flow

OSGi Component

JBI Component

NMR API

Cache ClusterInstance

1Instance

1Instance

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• Ehcache 2.6.0• LRU, LFU & FIFO• Multi-tenancy

Awareness

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Evaluation – Methodology & Data Set Measure how caching mitigates the performance degradation

when accessing data through CDASMix Analyze the optimal cache eviction algorithm (in tandem with the

MySQL instances) Cache Hit rate in % and throughput in Req./s TPC-H 1 GB data distributed in 8 tables Discrete uniform (1/N) generated workload from 5 adapted TPC-H

queries -> read intensive (2.5 MB per query) constituted by 100 queries from initial sample of 9 queries

Generated Load publicly available at https://santiago.studiforge.informatik.uni-stuttgart.de/svn/publications/IC2E14/queries4Load/generatedLoad 5-100.csv

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Evaluation Setup

VM0 (Flexiscale)

Apache JMeter 2.9 CDASMix

MySQL 5.1

TPC-H

Amazon RDSMySQL 5.1 instance

VM1 (Amazon EC2)

MySQL 5.1

D1D2 D3E3 E2 E1

Legend

Message Flow

Measurement PointThroughput andTransfer Rate

Built-in Cache

E

TPC-H

TPC-H

QueryGen.sh

load.csv

MySQL & Ehcache cache size 16MB

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Evaluation – MySQL in IaaS Flexiscale & AWS EC2

Flexiscale AWS EC2

-51%

-14%

-10%

+17%

-39%

+21%

+30%

+16%

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Evaluation – MySQL in IaaS Flexiscale & AWS EC2

Flexiscale AWS EC2

-51%

+43%

+46%

+42%

-39%

+50%

+53%

+48%

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Evaluation – MySQL in AWS RDS

-93%

-89% -89%

-89%

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Evaluation – MySQL in AWS RDS

-93%

+37% +37%

+37%

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Evaluation – CDASMix Cache Hit Ratio

Flexiscale AWS EC2 AWS RDS

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Conclusion & Future Work

Design and realization of CDASMix, a multi-tenant aware ESB solution that enables transparent data access

Caching support for ameliorating the performance Evaluation based on

different database deployment scenarios the utilization of different caching eviction algorithms

Extend CDASMix towards supporting PostgreSQL CDASMix horizontal scalability & distributed caching Further evaluation

+ Caching Eviction Algorithms Different workloads

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Thanks for your attention!!