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Scalable structure-free data fusion on wireless sensor networks

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Abstract

Recent advancements in sensor technology, wireless networks and consequently wireless sensor networks and the increase in their applications in different fields have led to their great importance. One of the most important challenges of such networks is the distributed management of the huge amount of data produced by sensors in network to reduce data traffic in network and minimize the energy consumption. In this research, a distributed, dynamic fusion algorithm is introduced. Since the proposed method is dynamic, the number of neighbors sending data to a node is not known in advance. So in order to increase the chances of different data to meet, the node waiting time is calculated. By the end of waiting time, the node performs data fusion and sends the fused data to the best neighbor chosen by the proposed best neighbor algorithm. This procedure continues until data reaches the sink. The proposed algorithm, while being scalable and convergent, outperforms similar methods in terms of number of transmissions, traffic load and energy consumption.

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References

  1. Hammoudeh M, Newman R (2013) Adaptive routing in wireless sensor networks: QoS optimization for enhanced application performance. J Inf Fusion 22:3–15

    Article  Google Scholar 

  2. Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. J Comput Netw 52(12):2292–2330

    Article  Google Scholar 

  3. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Science 38(4):393–422

    Google Scholar 

  4. Mikami S, Aonishi T, Yoshino H, Ohta C, Kawaguchi H, Yoshimoto M (2006) Aggregation efficiency-aware greedy incremental tree routing for wireless sensor networks. IEICE Trans 89(10):2741–2751

    Article  Google Scholar 

  5. Zhang K, Li C, Zhang W (2013) Wireless sensor data fusion algorithm based on the sensor scheduling and batch estimate. Int J Future Comput Commun 2(4):333

    Article  Google Scholar 

  6. Li Q, Li C, Li J (2010) Data aggregation algorithm based on grid and adaptive genetic algorithm for wireless senor networks with a mobile sink. In: Intelligent Systems and Applications (ISA), pp 1–4

  7. Maraiya K, Kant K, Gupta N (2011) Study of data fusion in wireless sensor network. In: International Conference on Advanced Computing and Communication Technologies, pp 535–539

  8. Nakamura EF, Loureiro AAF, Frery AC (2007) Information fusion for wireless sensor networks: methods, models, and classifications. ACM Comput Surv 39(3):9

    Article  Google Scholar 

  9. Zhu Y, Vedantham R, Park S-J, Sivakumar R (2008) A scalable correlation aware aggregation strategy for wireless sensor networks. Inf Fusion 9(3):354–369

    Article  Google Scholar 

  10. Younis O, Fahmy S (2004) Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach. In: Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies

  11. Wenz M, Wom H (2006) Event-based production rules for data aggregation in wireless sensor networks. In: IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Heidelberg, Germany

  12. Du W, Deng J, Han YS, Varshney PK (2003) A witness-based approach for data fusion assurance in wireless sensor networks. In: GLOBECOM, vol 3, pp 1435–1439

  13. Dai X, Xia F, Wang Z, Sun Y (2005) A survey of intelligent information processing in wireless sensor network. In: International Conference on Mobile Ad-Hoc and Sensor Networks. Springer, Berlin, pp 123–132

  14. Yousefi H, Yeganeh MH, Alinaghipour N, Movaghar A (2012) Structure-free real-time data aggregation in wireless sensor networks. Comput Commun 35(9):1132–1140

    Article  Google Scholar 

  15. Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii International Conference on System Sciences, p 10

  16. Chao C-M, Hsiao T-Y (2009) Design of structure-free and energy-balanced data aggregation in wireless sensor networks. In: 11th IEEE International Conference on High Performance Computing and Communications, pp 222–229

  17. Fan K-W, Liu S, Sinha P (2007) Structure-free data aggregation in sensor networks. IEEE Trans Mob Comput 6(8):929–942

    Article  Google Scholar 

  18. Madden S, Franklin MJ, Hellerstein J, Hong W (2002) TAG: a tiny aggregation service for ad-hoc sensor networks. In: Proceedings of the Fifth Symposium on Operating Systems Design and Implementation

  19. Ding M, Cheng X, Xue G (2003) Aggregation tree construction in sensor networks. In: Proceedings of the 58th IEEE Vehicular Technology Conference, pp 2168–2172

  20. Solis I, Obraczka K (2004) The impact of timing in data aggregation for sensor networks. In: Proceedings of the IEEE International Conference on Communications (ICC04), pp 3640–3645

  21. Du H, Hu X, Jia X (2006) Energy efficient routing and scheduling for real-time data aggregation in WSNS. Comput Commun 29:3527–3535

    Article  Google Scholar 

  22. Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii International Conference on System Sciences, p 10

  23. Heinzelman WR, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670

    Article  Google Scholar 

  24. Lindsey S, Raghavendra C (2002) PEGASIS: power-efficient gathering in sensor information systems. In: Proceedings of IEEE Aerospace Conference, vol 3

  25. Lindsey S, Raghavendra CS, Sivalingam KM (2001) Data gathering in sensor networks using the energy delay metric. In: Proceedings 15th International Parallel and Distributed Processing Symposium, vol 188, pp 2001–2008

  26. Lindsey S, Raghavendra C, Sivalingam KM (2002) Data gathering algorithms in sensor networks using energy metrics. IEEE Trans Parallel Distrib Syst 13(5):924–935

    Article  Google Scholar 

  27. Zhang J, Wu Q, Ren F, He T, Lin C (2010) Effective data aggregation supported by dynamic routing in wireless sensor networks. In: Proceedings of the IEEE International Conference on Communications (ICC10), p 16

  28. Ren F, Zhang J, Wu Y, He T, Chen C, Lin C (2013) Attribute-aware data aggregation using potential-based dynamic routing in wireless sensor networks. IEEE Trans Parallel Distrib Syst 24(5):881–892

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, UC Santa Barbara, Santa Barbara, CA, USA

    Mahnaz Koupaee & Mohammad Javad Amiri

  2. School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

    Mohammad Reza Kangavari

Authors
  1. Mahnaz Koupaee
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  2. Mohammad Reza Kangavari
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  3. Mohammad Javad Amiri
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Correspondence to Mahnaz Koupaee.

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Koupaee, M., Kangavari, M.R. & Amiri, M.J. Scalable structure-free data fusion on wireless sensor networks. J Supercomput 73, 5105–5124 (2017). https://doi.org/10.1007/s11227-017-2072-0

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  • DOI: https://doi.org/10.1007/s11227-017-2072-0

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