This document discusses migrating a Java-based mashup execution platform (MEP) to Scala to improve performance. It presents the design of the original MEP and describes how actors in Scala provide an event-driven concurrency model that is more efficient than threads. The authors mapped the orchestrator and services to Scala actors and evaluated the new implementation, finding it outperformed the original Java version with faster execution times and fewer threads. Future work may include additional testing and improving the service proxy adaptation.

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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

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

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1. Introduction (2/5)
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.
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1. Introduction (3/5)
The Mashup Creation Platform

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1. Introduction (4/5)
The Mashup Creation Platform
Event Date: July 1st, 2012
Event Title: Final Match
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1. Introduction (5/5)
System overview
Mashup Creation Platform
Mashup Repository
Mashup Execution Platform
(Server-side platform)

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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

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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
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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

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3. The Scala programming language (2/4)
 Here is the typical Scala Actor’s body
(pseudocode)
Loop{
onMessage{
Case Message1=>
Process Message1;
Case Message2=>
Process Message2;
…
}
}
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3. The Scala programming language (3/4)
 Case 1: onMessage=receive primitive
The concurrency model falls back to the Thread model
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3. The Scala programming language (4/4)
 Case 2: onMessage=react primitive
The concurrency model is event driven (a.k.a., threadless
model)
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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

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4. A Scala-based MEP (2/4)
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4. A Scala-based MEP (3/4)
 The reference example OAI=Orchestrator Actor Instance
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4. A Scala-based MEP (4/4)
The Orchestrator component in Scala (code)
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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
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5. Performance Evaluation (2/2)
The results
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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
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Thank you for
your attention!
Michele Stecca
Follow me on Twitter: @steccami
Email: m.stecca@cipi.unige.it 21