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A Study on MDE Approaches for Engineering Wireless Sensor Networks

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27th August 2014. My presentation at SEAA 2014 (http://esd.scienze.univr.it/dsd-seaa-2014) about our a study on model-driven engineering approaches for engineering Wireless Sensor Networks (WSNs).

Accompanying paper: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6928805

Abstract:
Model-Driven Engineering (MDE) can be considered as the right tool to reduce the complexity of Wireless Sensor Network (WSN) development through its principles of abstraction, separation of concerns, reuse and automation. In this paper we present the results of a systematic mapping study we performed for providing an organized view of existing MDE approaches for designing WSNs.
A total number of 780 studies were analysed; among them, we selected 16 papers as primary studies relevant for review. We setup a comparison framework for these studies, and classified them based on a set of common parameters. The main objective of our research is to give an overview about the state-of-the-art of MDE approaches dedicated to WSN design, and finally, discuss emerging challenges that have to be considered in future MDE approaches for engineering WSNs.

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A Study on MDE Approaches for Engineering Wireless Sensor Networks

  1. 1. A Study on MDE Approaches for Engineering Wireless Sensor Networks Ivano Malavolta Henry Muccini
  2. 2. Roadmap Background Contributions Research instrument Results Challenges Conclusions
  3. 3. Wireless sensor networks (WSNs) WSNs consist of spatially distributed sensors that cooperate to accomplish some tasks. Sensors are: – small – battery-powered – with limited processing power – with limited memory They can be easily deployed to monitor different environmental parameters such as temperature, movement, sound and pollution.
  4. 4. WSN applications Sensors can be distributed on roads, vehicles, hospitals, buildings, people and enable different applications such as: • environmental monitoring • medical services • battlefield operations • crisis response • disaster relief
  5. 5. Some WSN issues The unique characteristics of WSNs introduce additional issues in different fields, such as • programming • security • software engineering From the SESENA 2013 CfP: “the development of WSN software is still carried out in a rather primitive fashion, by building software directly atop the operating system and by relying on an individuals hard-earned programming skills” read as: ABSTRACTION NEEDED
  6. 6. Model-Driven Engineering (MDE) MDE shifts the focus of software development from coding to modeling modeling In MDE, domain-specific modeling languages can be used to build a model of the system: 1. by focussing on some selected aspects of the system 2. to perform some types of analysis 3. to generate some types of artifact http://mdse-book.com
  7. 7. Roadmap Background Contributions Research instrument Results Challenges Conclusions
  8. 8. The study to better understand how MDE techniques are used for designing and analysing WSNs systematic mapping study that surveys and classifies state-of- the-art MDE approaches for engineering a WSN • comparison framework for past and future MDE approaches for WSNs • systematic overview of current MDE approaches for engineering WSNs • discussion of emerging research challenges for future MDE approaches for WSNs GOAL INSTRUM ENT OUTPUTS
  9. 9. Related work This study is the first investigation into the usage of MDE for modeling, analysing, and developing WSNs In [2] and [3], the focus is on approaches for programming wireless sensor networks, rather than on how to model them A survey about modeling techniques for WSNs is also presented in [4]. However: – our investigation is specifically tailored to MDE approaches (rather than model-based ones), – our study is systematic*, rather than an informal exploration We follow the guidelines of Kitchenham et al. [5]
  10. 10. Roadmap Background Contributions Research instrument Results Challenges Conclusions
  11. 11. Research questions What are the existing MDE approaches for modeling, RQ1analysing and developing WSNs? How to compare existing MDE approaches for RQ2modeling analysing and developing WSNs? RQ1 focusses on approaches that – are based on a modeling language for WSNs – manipulate in some way the WSN models RQ2 explores how the previously selected MDE approaches compare w.r.t. a common comparison framework
  12. 12. Approaches selection 780 documents 16 primary studies1 selection criteria 1 A summary of the selected articles is available here: http://goo.gl/eCxw2
  13. 13. Selection criteria Inclusion criteria Exclusion criteria 1. Any article declaring that its main contribution is the definition of a new MDE approach for WSNs 2. Any article that have been published in or after 2007 3. Any article that have been published in English 1. Articles that have been extended by another article that have been previously considered in our survey 2. Articles that do not present any specific approach in details 3. Articles with incomplete information about our comparison framework 4. Articles that are an editorial, abstract, position paper, short paper, tool paper, poster summary, keynote, opinion, tutorial, introduction to conference proceedings, workshop summary, panel summary 5. Articles that are not peer reviewed
  14. 14. The comparison framework 3 clusters representing the main viewpoints from which an MDE approach can be analysed The features are orthogonal to the scope and applicability of each approach MDE approach for WSNs Modeling language features Goals Technological aspects
  15. 15. Comparing language features (1) MDE approach for WSNs Modeling language features Goals Technological aspects Modeling language Structure VS behaviour Computation scope [2] Mobility[2] DSML = Domain-specific GENERIC = generic Structure, behaviour, both S = static MN = mobile nodes MS = mobile sinks N = node-level G = group-level NET = network-level
  16. 16. Comparing language features (2) MDE approach for WSNs Modeling language features Goals Technological aspects Abstraction level[2] Physical deployment Power consumption Location awareness A = application S = system service OS = operating system MAC = media access H = hardware true/false true/false true/false
  17. 17. Comparing goals MDE approach for WSNs Modeling language features Goals Technological aspects Overall goal Analysis type CO = code generation AN = analysis T = test cases generation D = documentation Target language PE = performance FT = fault tolerance PO = power consumption SEC = security C++, NesC, Java, etc.
  18. 18. Comparing technological aspects MDE approach for WSNs Modeling language features Goals Technological aspects Used technologies Concrete syntax Extensibility Eclipse Stand-alone application etc, GRAPH = graphical TEXT = textual MIX = both of them L = extensible language F = extensible framework NO = no extensibility
  19. 19. Roadmap Background Contributions Research instrument Results Challenges Conclusions
  20. 20. Modeling languages features (1) Modeling language 12 2 2 14 12 10 8 6 4 2 0 New DSL Simulink UML Structure VS behaviour 4 7 5 8 7 6 5 4 3 2 1 0 Structure Behaviour Both 12 Mobility 1 0 3 14 12 10 8 6 4 2 0 Static Mobile Synk Mobile Nodes No info 8 Computation scope 5 One approach supports N,G,NET at the same time 2 2 9 8 7 6 5 4 3 2 1 0 Node-level Group-level Network-level No info
  21. 21. Modeling languages features (2) Abstraction level Physical deployment 6 9 1 7 6 5 4 3 2 1 10 8 6 4 2 0 Yes No No info Power consumption 6 9 1 10 9 8 7 6 5 4 3 2 1 0 Yes No No info Localization awareness 3 12 1 14 12 10 8 6 4 2 0 Yes No No info 1 5 1 3 6 0 Application System Service Operating System MAC Hardware All of them do code generation
  22. 22. Goals 13 13 Many approaches support both analysis and code generation No approach supports only documentation 3 3 14 12 10 8 6 4 2 0 Analysis Code Generation Test Case Generation Documentation Goals 10 5 2 1 3 Performance Power Consumption Security Fault tolerance No analysis 12 10 8 6 4 2 0 Analysis Type 7 3 1 2 3 8 7 6 5 4 3 2 1 0 Nes C Ansi C Java Not Specified No code generation Target Language
  23. 23. Technological aspects Used Technologies 8 8 9 8 7 6 5 4 3 2 1 0 Eclipse Unknown 4 Concrete Sintax 6 6 7 6 5 4 3 2 1 0 Textual Graphical Mixed 3 Extensibility 5 2 6 7 6 5 4 3 2 1 0 Language Framework No Unknown Great variability here
  24. 24. Roadmap Background Contributions Research instrument Results Challenges Conclusions
  25. 25. Identified challenges (1) Standard language for WSNs Many approaches propose their own ad-hoc modeling language for representing a WSN à Researchers should avoid this proliferation of different modeling languages in favor of an extensible standard language for WSNs Separation of concerns Almost all studied approaches are built on a single monolithic modeling language comprising all the concepts to model the WSN à Researchers should focus on a better separation of concerns when dealing with WSNs
  26. 26. Identified challenges (2) Support for mobility Almost all the presented approaches do not provide means for modeling nodes mobility à Researchers should support this increasingly relevant aspect of WSNs Mask complexity Many approaches mix together notions and concepts coming from both MDE and WSN communities à MDE researchers should take care in masking the complexity of the used MDE techniques to WSN engineers
  27. 27. How to proceed*? Research community around MDE for WSNs à helps in reasoning on the standard language for WSNs - for example see what did for real-time distributed systems à better communication with practitioners and nodes vendors à solving real problems Support multiple views – for example, see the ISO/IEC/IEEE 42010:2011, Systems and software engineering — Architecture description standard [5] Support for mobility - with run-time support * Disclaimer: this slide is heavily based on our experience in the domain of software architecture modeling.
  28. 28. Roadmap Background Contributions Research instrument Results Challenges Conclusions
  29. 29. Conclusions
  30. 30. References [1] Doddapaneni, Ever, Malavolta, Mostarda, Muccini (2012). A Model-Driven Engineering Framework for Architecting and Analysing Wireless Sensor Networks. In Proceedings of the 3rd ICSE Workshop on Software Engineering for Sensor Network Applications (SESENA 2012), Zurich, Switzerland, pp. 1-7. [2] L. Mottola and G. P. Picco, “Programming wireless sensor networks: Fundamental concepts and state of the art,” ACM Comput. Surv., vol. 43, pp. 19:1–19:51, Apr. 2011. [3] R. Sugihara and R. K. Gupta, “Programming models for sensor networks: A survey,” ACM Trans. Sen. Netw., vol. 4, no. 2, pp. 8:1–8:29, Apr. 2008. [Online]. Available: http:// doi.acm.org/10.1145/ 1340771.1340774 [4] J.K.Jacoub,R.Liscano,andJ.S.Bradbury ,“A survey of modeling techniques for wireless sensor networks,” in Proc. of the 5th International Conference on Sensor Technologies and Applications (SENSORCOMM 2011), Aug. 2011, pp. 103–109. [5] ISO/IEC/IEEE42010, Systems and software engineering — Architecture description, ISO, December 2011.
  31. 31. Ivano Malavolta | Gran Sasso Science Institute + 39 380 70 21 600 iivanoo ivano.malavolta@gssi.infn.it www.ivanomalavolta.com Contact

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