RUbIn: A framework for reliable and ubiquitous inference in WSNs

Document Type : Article

Authors

1 Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

2 School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract

Development of IoT applications brings a new movement to the functionality of wireless sensor networks (WSNs) from only environment sensing and data gathering to collaborative inferring and ubiquitous intelligence. In intelligent WSNs, nodes collaborate to exchange the information needed to achieve the required inference or smartness. Efficiency or correctness of many smart applications relies on the efficient, timely, reliable, and ubiquitous inference of information. In this paper, we introduce the RUbIn framework which provides a generic solution for such ubiquitous inferences. RUbIn brings the reliability and ubiquity for inferences using the redundancy characteristic of the gossiping protocols. With RUbIn, the implementation of such inferences and the control of their speed and cost is abstracted by providing developers with a proposed middleware and some dissemination control services.

We develop a prototype implementation of the RUbIn framework and a few inference examples on TinyOS. For evaluation, we utilize both the TOSSIM simulator and a testbed of MicaZ motes in various densities and different number of nodes. Results of the evaluations demonstrate that in all nodes, the inferring time after a change is about a few seconds and the cost of maintenance in stability state is about a few sends per hour.

Keywords

Main Subjects


1. Rawat, P., Singh, K.D., Chaouchi, H., and Bonnin, J. Wireless sensor networks: a survey on recent developments and potential synergies", The Journal of Supercomputing, 68(1), pp. 1-48 (2014). 2. Huang, C. Study on cloud-dust based intelligent maximum performance analysis system for power generation with solar energy", Scientia Iranica. Transactions B, Mechanical Engineering, 22(6), pp. 2170-2177 (2015). 3. Stojkoska, B.L.R. and Trivodaliev, K.V. A review of internet of things for smart home: Challenges and solutions", Journal of Cleaner Production, 140, pp. 1454-1464 (2017). 4. Sobral, J.V.V., Rodrigues, J.J.P.C., Rabelo, R.A.L., Filho, J.C.L., Sousa, N., Araujo, H.S., and Filho, R.H. A framework for enhancing the performance of internet of things applications based on RFID and wsns", J. of Network and Computer Applications, 107, pp. 56-68 (2018). 5. Ndiaye, M., Hancke, G.P., and Abu-Mahfouz, A.M. Software de_ned networking for improved wireless sensor network management: A survey", Sensors, 17(5), p. 1031 (2017). 6. Sahni, Y., Cao, J., and Liu, X. Midshm: A middleware for wsn-based shm application using serviceoriented architecture", Future Generation Computer Systems, 80, pp. 263-274 (2017). 7. Portocarrero, J.M.T., Delicato, F.C., Pires, P.F., Costa, B., Li, W., Si, W., and Zomaya, A.Y. RAMSES: A new reference architecture for self-adaptive middleware in wireless sensor networks", Ad Hoc Networks, 55, pp. 3-27 (2017). 8. Al-Jaroodi, J. and Mohamed, N. Service-oriented middleware: A survey", Journal of Network and Computer Applications, 35(1), pp. 211-220 (2012). 9. Fortino, G., Galzarano, S., Gravina, R., and Li, W. A framework for collaborative computing and multi-sensor data fusion in body sensor networks", Information Fusion, 22, pp. 50-70 (2015). 10. Zhu, C., Leung, V.C., Yang, L.T., and Shu, L. Collaborative location-based sleep scheduling for wireless sensor networks integratedwith mobile cloud computing", IEEE Transactions on Computers, 64(7), pp. 1844- 1856 (2015). 11. Srinivasan, S., Duttagupta, S., Kulkarni, P., and Ramamritham, K. A survey of sensory data boundary estimation, covering and tracking techniques using collaborating sensors", Pervasive and Mobile Computing, 8(3), pp. 358-375 (2012). 12. Plata-Chaves, J., Bertrand, A., Moonen, M., Theodoridis, S., and Zoubir, A.M. Heterogeneous and multitask wireless sensor networks-algorithms, applications, and challenges", J. Sel. Topics Signal Processing, 11(3), pp. 450-465 (2017). 13. Xiao, K., Wang, R., Fu, T., Li, J., and Deng, P. Divide-and-conquer architecture based collaborative sensing for target monitoring in wireless sensor networks", Information Fusion, 36, pp. 162-171 (2017). A. Shamsaie et al./Scientia Iranica, Transactions D: Computer Science & ... 26 (2019) 3540{3555 3555 14. Gharib, M., Youse_'Zadeh, H., and Movaghar, A. A survey of key pre-distribution and overlay routing in unstructured wireless networks", Scientia Iranica. Transactions D, Computer Science & Engineering, Electrical, 23(6), pp. 2831-2844 (2016). 15. Levis, P. and Culler, D.E. Mat_e: a tiny virtual machine for sensor networks", 10th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-X), San Jose, California, USA, pp. 85-95 (2002) 16. Saginbekov, S. and Jhumka, A. E_cient code dissemination in wireless sensor networks", Future Generation Computer Systems, 39, pp. 111-119 (2014). 17. Byun, H. and So, J. Node scheduling control inspired by epidemic theory for data dissemination in wireless sensoractuator networks with delay constraints", IEEE Trans. Wireless Communications, 15(3), pp. 1794- 1807 (2016). 18. Hoeer, T., Barak, A., Shiloh, A., and Drezner, Z. Corrected gossip algorithms for fast reliable broadcast on unreliable systems", 2017 IEEE International Parallel and Distributed Processing Symposium, Orlando, FL, USA, pp. 357-366 (2017). 19. Gnawali, O., Fonseca, R., Jamieson, K., Kazandjieva, M.A., Moss, D., and Levis, P. Ctp: An e_cient, robust, and reliable collection tree protocol for wireless sensor networks", TOSN, 10(1), pp. 16:1-16:49 (2013). 20. Chen, J., D__az, M., Rubio, B., and Troya, J.M. Psquasar: A publish/subscribe qos aware middleware for wireless sensor and actor networks", Journal of Systems and Software, 86(6), pp. 1650-1662 (2013). 21. Fonseca, R., Gnawali, O., Jamieson, K., and Levis, P. Four-bit wireless link estimation", Sixth Workshop on Hot Topics in Networks (HotNets), Atlanta, Georgia, USA (Nov. 2007). 22. Levis, P., Patel, N., Culler, D.E., and Shenker, S. Trickle: A self-regulating algorithm for code propagation and maintenance in wireless sensor networks", 1st Conference on Symposium on Networked Systems Design and Implementation (NSDI'04), Berkeley, CA, USA, pp. 15-28 (2004). 23. Chang, C., Srirama, S.N., and Buyya, R. Indie fog: An e_cient fog-computing infrastructure for the internet of things",IEEE Computer, 50(9), pp. 92-98 (2017).