Exploiting Safe Parallelism in Wireless Sensor Networks: A Generic - - PowerPoint PPT Presentation

Exploiting Safe Parallelism in Wireless Sensor Networks: A Generic and Reconfigurable Approach

Jó Ueyama, Danny Hughes, Paul Grace, Edmundo R. M. Madeira

Institute of Mathematics and Computer Science University of Sao Paulo (USP)

Liverpool, 14th December ,2012

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Why Parallelism?

 Parallelism is widely utilized in a diverse range of devices, such as:

• Desktop computers
• Smartphones
• Sensor motes (mPlatform – by Microsoft)

 Parallelism is implemented with the aid of several tools

• Java Threads
• Pthreads
• MPI

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How to help developers?

Generic tool?

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How to help developers?

Generic tool?

MPI

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Any problem with parallelism?

 Parallelism can bring race conditions and deadlock problems  This can be problematic particularly in critical systems such as:

• Wireless sensor networks (WSN) monitoring

nuclear reactor

• or for healthcare (e.g. real-time heart rate)

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Is parallelism a problem in all applications?

 However, not all applications would face problems with concurrency problems

• E.g. non critical systems – WSN for car parking

 Solution?

• We need a reconfigurable and generic approach

to handle the real world problems

• Using a single tool
• Advantages?
• Less learning curve and transferable skills

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Our Approach: FlexPar Middleware

• FlexPar Architecture consists of:

– Microkernel style (ensures deployment in resource constrained devices) – Extensions

• Loaders (enables deployment of a particular style of

parallel software)

• Binders (connects processes of a particular style)

– Parallel deadlock-free systems

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Essentially, a unique tool for parallel environments

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Diving into details of our approach

• Some implementation issues
• We implemented two plugins based on:
• CSP (Communicating Sequential Processes)

– in a nutshell:

– CSP Processes (e.g. functions, methods) do not share data – Each process do not invoke functions implemented in other processes – This avoids concurrency problems such as deadlocks and race conditions.

Bob Alice

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The first plugin

• The first plugin was based on
• Transterpreter (Transputer Interpreter)
• Virtual machine for parallel applications written in occam
• Highly portable (~2000 lines of code in pure ANSI C)

gcc

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Other Tools at UKC

 JCSP (Java CSP)

– CSP library for Java programmers – One can use the CSP disciplines where JVM is supported – Advantage: CSP is reachable by the large community of Java programmers – Drawback: performance

JCSP CSP in Java

Java Developers

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Why not use those tools?

 The above mentioned tools have the following

limitations:

– Static configuration

• Transterpreter, KroC (occam compiler)
• CSP processes cannot be connected and disconnected at

runtime

• Dynamic reconfiguration can tailor the software to the

desired target domain

– Sensor nets, routers

– Limited interoperability

• Processes in occam and JCSP cannot interoperate

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FlexPar Quantitative Evaluation

 We performed evaluation such as memory

footprint, performance and overhead

– This was carried out on the Gumstixs

 Commstime Benchmark evaluation

– Measure context switch, iteration between processes and communtion overhead

 We ported FlexPar to two platforms

– Gumstixs – Sun SPOTs

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FlexPar Qualitative Evaluation

 This is still under construction  Evaluate FlexPar on our river monitoring

system which has three processes

– Monitors floods – Reads water poluttion – Sends data to base station

 The river monitoring system is considered to

be critical because...

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 Flash floods takes places particularly on rainy

seasons (December from March)

 Our urban rivers are highly polluted

Why is it critical?

Floods Pollution

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 The full prototype deployed at Monjolino urban river  Base station at the porter's lodge

Port FlexPar to the deployed node?

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Acknowledgements

We would like to thank FAPESP, CNPq and RNP for funding our research project

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Thank you for your attention!

Email: joueyama@icmc.usp.br

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We are all waiting for your visit to Brazil