Scc2012 Scala

cipi Centro di Ricerca sull’Ingegneria delle Piattaforme Informatiche

Event-Driven Mashup Orchestration with
Scala

Michele Stecca, Martino Fornasa, Nicholas Dall’Armellina,
and Massimo Maresca
Computer Platform Research Center (CIPI)
University of Padova & Genova (Italy)
Honolulu, HI, June 28th, 2012

Follow me on Twitter: @steccami
E-mail: m.stecca@cipi.unige.it


Agenda

1. Introduction
2. Mashup Execution Platform (MEP) Design
3. The Scala programming language
4. A Scala-based MEP
5. Performance evaluation
6. Conclusions

2


1. Introduction (1/5)
…about the ‘Mashup’ concept

 Data Mashup: combining different data sources (e.g.,
Yahoo!Pipes)
 Presentation Mashup: combining different
gadgets/widgets in a web page (e.g., iGoogle)
 Process/Functional Mashup: combining different
services/Web APIs (e.g., JackBe Presto but also IFTTT)


Reference Scenario
 Availability of contents and services through technologies
typical of the Web 2.0 philosophy such as RSS Feed,
Atom, REST-WS, SOAP-WS, etc. See
programmableweb.com for a list of more than 6000 Web
APIs

 Internet/Web of Things (need for event management)

 Availability of tools for the rapid development of
convergent Composite Services (a.k.a., Mashups) that
combine different resources such as Yahoo Pipes!, JackBe
Presto, etc.

4


The Mashup Creation Platform


The Mashup Creation Platform
Event Date: July 1st, 2012
Event Title: Final Match

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System overview

Mashup Creation Platform

Mashup Repository

Mashup Execution Platform
(Server-side platform)


2. The MEP Design (1/2)
We already implemented a Java-based MEP* whose
high level architecture is depicted in the figure

SP=Service Proxy
(i.e., a wrapper for Web APIs)

*Stecca M., Maresca M., “An Architecture for a Mashup Container in Virtualized Environments”,
Cloud, pp.386-393, 2010 IEEE 3rd International Conference on Cloud Computing, Miami,
Florida, 2010 8


2. The MEP Design (2/2)
 The MEP has been designed as a Server-side platform “in-
the-cloud” (reasons: security, performance optimization,
always-on, etc.)
 It is important to chose a suitable concurrency model
because of the huge number of Mashup executions taking
place concurrently
 Two approaches:
 Thread-based (but difficult to optimize the resource usage)
 Event-driven (but difficult to develop)
 How can we improve the existing Java-based MEP
performance without re-developing the system from the
scratch?
Possible answer: by using the Scala
programming language
9


3. The Scala programming language (1/4)
 Developed at the EPFL Lausanne,
Switzerland
 It merges the Functional Programming (FP)
and the OOP paradigms
 It is executed by a JVM  Fully compatibility
with legacy Java libraries
 Concurrency model: actors (e.g., Erlang)
 It is suitable to exploit the multi-core processors
 An actor is a “computational unit” lighter than a
system thread
 Actors communicate among each others
according to the message passing paradigm
DestinationActor ! Message 10


 Here is the typical Scala Actor’s body
(pseudocode)

Loop{
onMessage{
Case Message1=>
Process Message1;
Case Message2=>
Process Message2;
…
}
}
11


 Case 1: onMessage=receive primitive

The concurrency model falls back to the Thread model

12


 Case 2: onMessage=react primitive

The concurrency model is event driven (a.k.a., threadless
model)
13


4. A Scala-based MEP (1/4)
 The Java-based MEP has been developed in
modular way (i.e., clear separation between
the Business Logic and the Concurrency
logic)
 The idea is to exploit at the same time:
 The Java-based MEP implementation
 The efficient Scala concurrency model
based on actors
 What have we done?
 We mapped the Orchestrator component and
each SP into Scala actors
 We defined the MessageDo and the
MessageEvent Scala messages 14



15


 The reference example OAI=Orchestrator Actor Instance

16


The Orchestrator component in Scala (code)

17


5. Performance Evaluation (1/2)
The testbed
 Two nodes (QuadCore, 4GB RAM, Ubuntu OS)
 Node 1: traffic injector
 Node 2: the Scala-based MEP
 Deployment of 2 fake SPs and 1 fake Mashup
 Definition of two metrics:
 Mashup Execution Time (MET)
 #Threads

18


5. Performance Evaluation (2/2)

The results

19


6. Conclusions

 We successfully migrated the Java-based MEP
to Scala
 The evaluation tests show how the Scala-based
MEP outperforms the Java-based MEP
 Future work:
 Additional performance tests

 Focus on the Service Proxy (i.e., adpatation)

level
 Final Match vs
20


Thank you for
your attention!

Michele Stecca
Follow me on Twitter: @steccami
Email: m.stecca@cipi.unige.it 21

Scc2012 Scala

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