A Resource Oriented Framework for Service Choreography over Wireless Sensor and Actor Networks

  • Clément Duhart
  • Pierre Sauvage
  • Cyrille Bertelle
Article

Abstract

Current Internet of Things (IoT) development requires service distribution over Wireless Sensor and Actor Networks (WSAN) to deal with the drastic increasing of network management complexity. Because of the specific constraints of WSAN, some limitations can be observed in centralized approaches. Multi-hop communication used by WSAN introduces transmission latency, packet errors, router congestion and security issues. As it uses local services, a model of decentralized services avoids long path communications between nodes and applications. But the two main issues are then to design (1) the composition of such services and to map (2) them over the WSAN. This contribution proposes a model for decentralized services based on Resource Oriented Architecture in which their communications are designed thanks to an adaptation of Petri Network (1). In addition, the problem of decentralized service mapping and its deployment over a WSAN is successfully resumed by a Pseudo-Boolean Optimization in order to minimize network communication load (2). These contributions are presented using a proposed EMMA middleware as unifying thread.

Keywords

Internet of Things (IoT) Wireless Sensor and Actor Network (WSAN) Middleware Resource Oriented Architecture (ROA) Service Choreography (SC) 

Notes

Acknowledgments

The authors thank Dr. Courbin Pierre for the discussions and its reviews during the writing of this document and also Mr. Mardegan Nicolas for its contribution on the implementation of EMMA framework.

References

  1. 1.
    Billington J, Wheeler G, Wilbur-Ham M (1988) Protean: a high-level petri net tool for the specification and verification of communication protocols. IEEE Transactions on Software Engineering 14(3):301–316. doi:10.1109/32.4651 CrossRefGoogle Scholar
  2. 2.
    Cherrier S, Ghamri-Doudane YM, Lohier S, Roussel G (2012) Services collaboration in wireless sensor and actuator networks: orchestration versus choreography. In: Symposium on Computers and Communications (ISCC), IEEE, Cappadocia, Turkey, pp 411–418Google Scholar
  3. 3.
    Cherrier S, Salhi I, Ghamri-Doudane Y, Lohier S, Valembois P (2014) Bec 3: Behaviour crowd centric composition for iot applications. Mobile Networks and Applications 19(1):18–32. doi:10.1007/s11036-013-0481-8 CrossRefGoogle Scholar
  4. 4.
    Costa P, Mottola L, Murphy AL, Picco GP (2006) Teenylime: Transiently shared tuple space middleware for wireless sensor networks. In: International Workshop on Middleware for Sensor Networks (MidSens), ACM, New York, NY, USA, MidSens ’06, vol 1, pp 43–48. doi:10.1145/1176866.1176874
  5. 5.
    Delicato Flvia Coimbra PL Pires PauloF, da Costa Carmo Luiz Fernando Rust (2003) A flexible middleware system for wireless sensor networks. In: Endler M, Schmidt D (eds) Middleware 2003, Lecture Notes in Computer Science, vol 2672, Springer Berlin Heidelberg, pp 474–492. doi:10.1007/3-540-44892-6_24
  6. 6.
    Duhart C, Cotsaftis M, Bertelle C (2014) Wireless sensor network cloud services: Towards a partial delegation. In: International Conference on Smart Communications in NetworkTechnologies (SaCoNeT), IEEE, Vilanova i la Geltru, SpainGoogle Scholar
  7. 7.
    Dunkels A (2003) Full tcp/ip for 8-bit architectures. In: International Conference on Mobile systems, Applications and Services (MobiSys), ACM, San Francisco, CA, USA, vol 1, pp 85–98Google Scholar
  8. 8.
    Dunkels A, Gronvall B, Voigt T (2004) Contiki-a lightweight and flexible operating system for tiny networked sensors. In: International Conference on Local Computer Networks (LCN), IEEE, IEEE, Clearwater, Florida, USA, pp 455–462Google Scholar
  9. 9.
    Eduardo S, Germano G, Glauco V, Mardoqueu V, Nelson R, Carlos F (2004) A message-oriented middleware for sensor networks. In: Workshop on Middleware for Pervasive and Ad-hoc Computing (WMPAC), ACM, New York, NY, USA, MPAC ’04, pp 127–134. doi:10.1145/1028509.1028514
  10. 10.
    Fok CL, Roman GC, Lu C (2009) Agilla: A mobile agent middleware for self-adaptive wireless sensor networks. ACM Transaction on Autonomous and Adaptive Systems 4(3):16–26. doi:10.1145/1552297.1552299 Google Scholar
  11. 11.
    Guinard D, Trifa V, Wilde E (2010) A resource oriented architecture for the web of things. In: Internet of Things (IOT), 2010, IEEE, pp 1–8Google Scholar
  12. 12.
    Hackmann G, Fok CL, Roman GC, Lu C (2006) Agimone: Middleware support for seamless integration of sensor and ip networks. In: Gibbons P, Abdelzaher T, Aspnes J, Rao R (eds) Distributed Computing in Sensor Systems, Lecture Notes in Computer Science, vol 4026, Springer Berlin Heidelberg, pp 101–118. doi:10.1007/11776178_7
  13. 13.
    Hadim S, Mohamed N (2006) Middleware: Middleware challenges and approaches for wireless sensor networks. IEEE Distributed Systems Online 7(3):1–1. doi:10.1109/MDSO.2006.19 CrossRefGoogle Scholar
  14. 14.
    Holliday M, Vernon MK, et al (1987) A generalized timed petri net model for performance analysis. IEEE Transactions on Software Engineering (12):1297–1310CrossRefGoogle Scholar
  15. 15.
    Khedo K, Subramanian R (2009) A service-oriented component-based middleware architecture for wireless sensor networks. International Journal of Computer Science and Network Security 9(3):174–182Google Scholar
  16. 16.
    Ko J, Gnawali O, Culler D, Terzis A (2011) Evaluating the performance of rpl and 6lowpan in tinyos. In: Extending the Internet to Low power and Lossy Networks (IP+SN 2011), ACM, Chicago USA, vol 1, pp 193–208Google Scholar
  17. 17.
    Kovatsch M, Duquennoy S, Dunkels A (2011) A low-power coap for contiki. In: International Conference on Mobile Ad-Hoc and Sensor Systems (MASS), IEEE, Valencia, Spain, vol 1, pp 855–860. doi:10.1109/MASS.2011.100
  18. 18.
    Kuorilehto M, Hannikainen M, Hamaainen TD (2005) A survey of application distribution in wireless sensor networks. Journal Wireless Communication Network (EURASIP) 2005(5):774–788. doi:10.1155/WCN.2005.774 MATHGoogle Scholar
  19. 19.
    Kushwaha M, Amundson I, Koutsoukos X, Neema S, Sztipanovits J (2007) Oasis: A programming framework for service-oriented sensor networks. In: International Conference on Communication Systems Software and Middleware (COMSWARE), IEEE, Bangalore INDIA, pp 1–8. doi:10.1109/COMSWA.2007.382431
  20. 20.
    Liu W, Chen B (2011) Optimal control of mobile monitoring agents in immune-inspired wireless monitoring networks. Journal of Network and Computer Applications 34(6):1818–1826. doi:10.1016/j.jnca.2010.12.004, http://www.sciencedirect.com/science/article/pii/S1084804510002158, control and Optimization over Wireless Networks
  21. 21.
    Moritz G, Golatowski F, Timmermann D (2011) A lightweight soap over coap transport binding for resource constraint networks. In: International Conference on Mobile Adhoc and Sensor Systems (MASS), IEEE, Valencia, Spain, vol 1, pp 861–866. doi:10.1109/MASS.2011.101
  22. 22.
    Rahman MA (2009) Middleware for wireless sensor networks: Challenges and approaches. In: Seminar on Internetworking, Helsinki University of Technology, Finland, vol 124Google Scholar
  23. 23.
    Rubio B, Diaz M, Troya J (2007) Programming approaches and challenges for wireless sensor networks. In: Second International Conference on Systems and Networks Communications, ICSNC 2007., pp 36–36. doi:10.1109/ICSNC.2007.63 Google Scholar
  24. 24.
    Russell N, Arthur, van der Aalst WMP, Mulyar N (2006) Workflow Control-Flow Patterns: A Revised View. BPM Center Report BPM-06-22Google Scholar
  25. 25.
    Vasseur JP, Dunkels A (2010) Interconnecting Smart Objects with IP: The Next Internet. Morgan Kaufmann Publishers Inc., San Francisco, CA, USAGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, LACSCECE ParisParisFrance
  2. 2.ULH, LITIS, FR-CNRS-3638, ISCNNormandie UnivLe HavreFrance

Personalised recommendations