Skip to main content
SpringerLink
Log in

Application modeling for performance evaluation on event-triggered wireless sensor networks

  • Published:
Design Automation for Embedded Systems Aims and scope Submit manuscript

Abstract

This paper presents an approach for event-triggered wireless sensor network (WSN) application modeling, aiming to evaluate the performance of WSN configurations with regards to metrics that are meaningful to specific application domains and respective end-users. It combines application, environment-generated workload and computing/communication infrastructure within a high-level modeling simulation framework, and includes modeling primitives to represent different kind of events based on different probabilities distributions. Such primitives help end-users to characterize their application workload to capture realistic scenarios. This characterization allows the performance evaluation of specific WSN configurations, including dynamic management techniques as load balancing. Extensive experimental work shows that the proposed approach is effective in verifying whether a given WSN configuration can fulfill non-functional application requirements, such as identifying the application behavior that can lead a WSN to a break point after which it cannot further maintain these requirements. Furthermore, through these experiments, we discuss the impact of different distribution probabilities to model temporal and spatial aspects of the workload on WSNs performance, considering the adoption of dynamic and decentralized load balancing approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Brisolara L, Ferreira P, Soares Indrusiak L (2015) Impact of temporal and spatial application modeling on event-triggered wireless sensor network evaluation. In: Proceedings of the V Brazilian Symposium on Computing Systems Engineering

  2. Brooks C, Lee EA, Liu X, Zhao Y, Zheng H, Bhattacharyya SS, Brooks C, Cheong E, Goel M, Kienhuis B, Lee EA, Liu J, Liu X, Muliadi L, Neuendorffer S, Reekie J, Smyth N, Tsay J, Vogel B, Williams W, Xiong Y, Zhao Y, Zheng H (2005) Ptolemy ii: heterogeneous concurrent modeling and design in java. Technical report

  3. Caliskanelli I, Harbin J, Indrusiak LS, Mitchell P, Polack F, Chesmore D (2013) Bioinspired load balancing in large-scale WSNs using pheromone signalling. Int J Distrib Sens Netw 9(7):172012. doi:10.1155/2013/172012

  4. Delicato FC, Pires PF, Pirmez L, da Costa Carmo LFR (2003) A flexible middleware system for wireless sensor networks. In: Proceedings of the ACM/IFIP/USENIX 2003 International Conference on Middleware, Middleware ’03. Springer, New York, pp 474–492

  5. Doddapaneni K, Ever E, Gemikonakli O, Malavolta I, Mostarda L, Muccini H (2012) A model-driven engineering framework for architecting and analysing wireless sensor networks. In: Proceedings of the Third International Workshop on Software Engineering for Sensor Network Applications, SESENA ’12. IEEE Press, Piscataway, pp 1–7

  6. Dohare U, Lobiyal DK, Kumar S (2014) Energy balanced model for lifetime maximization in randomly distributed wireless sensor networks. Wirel Pers Commun 78(1):407–428

    Article  Google Scholar 

  7. Ferreira P, Brisolara L, Soares Indrusiak L (2016) Eboracum project. http://sourceforge.net/projects/eboracum/

  8. Ferreira P, Brisolara L, Soares Indrusiak L (2015) Decentralised load balancing in event-triggered wsns based on ant colony work division. In: Proceedings of the 41st Euromicro Conference on Software Engineering and Advanced Applications (SEAA), pp 69–75

  9. Grassi PR, Beretta I, Rana V, Atienza D, Sciuto D (2012) Knowledge-based design space exploration of wireless sensor networks. In: Proceedings of the Eighth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS ’12. ACM, New York, pp 225–234

  10. Haghighi M (2013) Dynamic data storage estimation for multiple concurrent applications using probability distribution modeling in wsns. J Adv Comput Netw 1(3):254–259

    Article  Google Scholar 

  11. Imran M, Said A, Hasbullah H (2010) A survey of simulators, emulators and testbeds for wireless sensor networks. In: Proceedings of the 2010 International Symposium in Information Technology (ITSim), vol 2, pp 897–902

  12. nc M. Iris: Wireless measurement system. http://www.memsic.com/userfiles/files/Datasheets/WSN/IRIS_Datasheet.pdf

  13. Iova O, Theoleyre F, Noel T (2015) Using multiparent routing in rpl to increase the stability and the lifetime of the network. Ad Hoc Netw 29(C):45–62

    Article  Google Scholar 

  14. Isik S, Donmez MY, Tunca C, Ersoy C (2013) Performance evaluation of wireless sensor networks in realistic wildfire simulation scenarios. In: Proceedings of the 16th ACM International Conference on Modeling, Analysis ‘I&’ Simulation of Wireless and Mobile Systems, MSWiM ’13. ACM, New York, pp 109–118

  15. Jin Y, Wei D, Gluhak A, Moessner K (2010) Latency and energy-consumption optimized task allocation in wireless sensor networks. In: Proceedings of the 2010 IEEE Conference on Wireless Communications and Networking Conference (WCNC), pp 1–6

  16. Juang P, Oki H, Wang Y, Martonosi M, Peh LS, Rubenstein D (2002) Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with zebranet. In: Proceedings of the 10th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS X. ACM, New York, pp 96–107

  17. Kacimi R, Dhaou R, Beylot AL (2013) Load balancing techniques for lifetime maximizing in wireless sensor networks. Ad Hoc Netw 11(8):2172–2186

    Article  Google Scholar 

  18. Lee E (2008) Cyber physical systems: design challenges. In: Proceedings of the 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing (ISORC), pp 363–369

  19. Levis P, Lee N, Welsh M, Culler D (2003) Tossim: Accurate and scalable simulation of entire tinyos applications. Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, SenSys ’03. ACM, New York, pp 126–137

  20. Menichelli F, Olivieri M (2010) Tiktak: a scalable simulator of wireless sensor networks including hardware/software interaction. Wirel Sens Netw 2(11):815–822

    Article  Google Scholar 

  21. Mozumdar M, Song ZY, Lavagno L, Sangiovanni-Vincentelli AL (2014) A model-based approach for bridging virtual and physical sensor nodes in a hybrid simulation framework. Sensors 14(6):11,070

    Article  Google Scholar 

  22. Navarro M, Liang Y (2016) Efficient and balanced routing in energy-constrained wireless sensor networks for data collection. In: Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks, EWSN ’16. Junction Publishing, pp 101–113

  23. Ochirsuren E, Indrusiak L, Glesner M (2008) An actor-oriented group mobility model for wireless ad hoc sensor networks. In: Proceedings of the 28th International Conference on Distributed Computing Systems Workshops, pp 174–179

  24. Park S, Savvides A, Srivastava MB (2000) Sensorsim: a simulation framework for sensor networks. In: Proceedings of the 3rd ACM International Workshop on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWIM ’00. ACM, New York, pp 104–111

  25. Pathak A, Prasanna VK (2010) Energy-efficient task mapping for data-driven sensor network macroprogramming. IEEE Trans Comput 59(7):955–968

    Article  MathSciNet  Google Scholar 

  26. Potdar V, Sharif A, Chang E (2009) Wireless sensor networks: a survey. In: Proceedings of the 2009 International Conference on Advanced Information Networking and Applications Workshops, pp 636–641

  27. Rodrigues T, Dantas P, Delicato F, Pires P, Pirmez L, Batista T, Miceli C, Zomaya A (2011) Model-driven development of wireless sensor network applications. In: Proceedings of the 2011 IFIP 9th International Conference on Embedded and Ubiquitous Computing (EUC), pp 11–18

  28. Rosello V, Portilla J, Krasteva Y, Riesgo T (2009) Wireless sensor network modular node modeling and simulation with visualsense. In: Proceedings of the 35th Annual Conference of IEEE Industrial Electronics, pp 2685–2689

  29. Ruiz LB, Siqueira IG, Oliveira LBe, Wong HC, Nogueira JMS, Loureiro AAF, (2004) Fault management in event-driven wireless sensor networks. In: Proceedings of the 7th ACM International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWiM ’04. ACM, New York, pp 149–156

  30. Salhi I, Ghamri-Doudane Y, Lohier S, Roussel G (2010) Network coding for event-centric wireless sensor networks. In: Proceedings of the 2010 IEEE International Conference on Communications (ICC), pp 1–6

  31. Santi P (2012) Mobility models for next generation wireless networks: ad-hoc, vehicular and mesh networks. Wiley, Hoboken

    Book  Google Scholar 

  32. Senthilkumar J, Chandrasekaran M, Suresh Y, Arumugam S, Mohanraj V (2012) Advertisement timeout driven bee’s mating approach to maintain fair energy level in sensor networks. Appl Soft Comput 12(7):1884–1890

    Article  Google Scholar 

  33. Sobeih A, Chen WP, Hou J, Kung LC, Li N, Lim H, ying Tyan H, Zhang H (2005) J-sim: a simulation environment for wireless sensor networks. In: Proceedings of the 38th Annual Simulation Symposium, pp 175–187

  34. Soong TT (2004) Fundamentals of probability and statistics for engineers. Wiley-Backwall, New York

    MATH  Google Scholar 

  35. Sungur C, Spiess P, Oertel N, Kopp O (2013) Extending bpmn for wireless sensor networks. In: Proceedings of the 2013 IEEE 15th Conference on Business Informatics (CBI), pp 109–116

  36. Zeng Z, Liu A, Li D, Long J (2008) A highly efficient dag task scheduling algorithm for wireless sensor networks. In: The 9th International Conference for Young Computer Scientists, pp 570–575

Download references

Author information

Authors and Affiliations

  1. Centro de Desenvolvimento tecnológico (CDTEC), Universidade Federal de Pelotas (UFPel), Pelotas, Brazil

    Lisane Brisolara & Paulo R. Ferreira Jr.

  2. Department of Computer Science, University of York, York, UK

    Leandro Soares Indrusiak

Authors
  1. Lisane Brisolara
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paulo R. Ferreira Jr.
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Leandro Soares Indrusiak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lisane Brisolara.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Brisolara, L., Ferreira, P.R. & Indrusiak, L.S. Application modeling for performance evaluation on event-triggered wireless sensor networks. Des Autom Embed Syst 20, 269–287 (2016). https://doi.org/10.1007/s10617-016-9177-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10617-016-9177-1

Keywords

Search

Navigation