Advertisement

Mobile Networks and Applications

, Volume 21, Issue 5, pp 856–864 | Cite as

SPSIC: Semi-Physical Simulation for IoT Clouds

  • Junfeng Wang
  • Xiaobo Shi
  • Musaed Alhussein
  • Limei Peng
  • Ying HuEmail author
Article
  • 413 Downloads

Abstract

Recent years have witnessed various successful demonstrations of the emerging IoT technologies, while the researchers still need to face a lot of technological challenges. It is necessary to verify and evaluate the relevant theories and calculations before the application of IoT, and that is why building a simulation platform for the IoT becomes so important, especially for a large scale IoT to meet the requirement of a scale perception in a large scope. The IoT which always contains a complicated network and communication system has made the network simulation software OPNET Modeler to be a good choice for it. Moreover, the IoT has transfer all kinds of “objects” that humans need into the form of data by various sensing equipment and intelligent devices, and those data will be stored, analyzed and processed by cloud computing finally. The paper presents an innovative method to establish an intelligent, independent and expandable data driven IoT service platform by OPNET’s Semi-Physical Simulation to combine the simulated network for IoT with the real Cloud computing(SPSIC) which applies real network to achieve the long-term surveillance, management, sharing and analysis of the collected data at any time.

Keywords

Internet of things(IoT) System in the loop(SITL) Semi-physical OPNET 

Notes

Acknowledgments

Thanks for the visiting professor program at King Saud University for supporting this research work.

References

  1. 1.
    Tao MX, Chen E, Zhou H, Yu W (2015) Contentcentric Sparse Multicast Beamforming for Cacheenabled Cloud RAN, IEEE Transaction on Wireless, arXiv:1512.06938
  2. 2.
    Chen M, Hao Y, Li Y, Lai C, Wu D (2015) On the computation offloading at ad hoc cloudlet: Architecture and service models. IEEE Commun 53(6):18–24CrossRefGoogle Scholar
  3. 3.
    Zhang Y, Chen M, Mao S, Hu L, Leung V (2014) CAP: Crowd activity prediction based on big data analysis. IEEE Netw 28(4):52–57CrossRefGoogle Scholar
  4. 4.
    Chen M, Qian Y, Mao S, Tang W, Yang X (2016) Software-Defined Mobile Networks Security, ACM/Springer Mobile Networks and Applications, doi: 10.1007/s11036-015-0665-5
  5. 5.
    Chen M, Zhang Y, Li Y, Mao S, Leung V (2015) EMC: Emotion-aware mobile cloud computing in 5G. IEEE Netw 29(2):32– 38CrossRefGoogle Scholar
  6. 6.
    Chen M, Zhang Y, Hu L, Taleb T, Sheng Z (2015) Cloud-based wireless network: virtualized, reconfigurable, smart wireless network to enable 5G technologies. ACM/Springer Mob Netw Appl 20(6):704–712CrossRefGoogle Scholar
  7. 7.
    Ge X, Cheng H, Guizani M, Han T (2014) 5G wireless backhaul networks: challenges and research advances. IEEE Netw 28(6):6–11CrossRefGoogle Scholar
  8. 8.
    Chen E, Tao MX (2013) A network and device aware qos approach for cloud-based mobile streaming. IEEE Trans Multimed 15(4):747–757MathSciNetCrossRefGoogle Scholar
  9. 9.
    Li H, Wu D, Li G-X, Ke Y-H, Liu W-J, Zheng Y-H, Lin X-L (2015) Enhancing telco service quality with big data enabled churn analysis: infrastructure, model, and deployment. J Comput Sci Technol 30(6):1201–1214CrossRefGoogle Scholar
  10. 10.
    Lai C-F, Wang H, Chao H-C, Nan G (2013) A network and device aware qos approach for cloud-based mobile streaming. IEEE Trans Multimed 15(4):747–757CrossRefGoogle Scholar
  11. 11.
    Zheng K, Zhao L, Mei J, Dohler M, Xiang W, Peng Y (2015) 10 Gb/s hetsnets with millimeter-wave communications: access and networking-challenges and protocols. IEEE Commun Mag 53(1):222–231CrossRefGoogle Scholar
  12. 12.
    Zheng K, Zhao L, Mei J, Shao B, Xiang W, Hanzo L (2015) Survey of large-scale mimo systems. IEEE Commun Surv Tutorials 17(3):1738–1760CrossRefGoogle Scholar
  13. 13.
    Lai C-F, Hwang R-H, Chao H-C, Hassan M, Alamri A (2015) A buffer-aware http live streaming approach for sdn-enabled 5g wireless networks. IEEE Netw 29(1):49–55CrossRefGoogle Scholar
  14. 14.
    Wang G, Xiang W, Pickering M (2015) A cross-platform solution for light field based 3d telemedicine, Computer methods and programs in biomedicineGoogle Scholar
  15. 15.
    Xue Z, Wu D, He J, Hei X, Liu Y (2015) Playing high-end video games in the cloud: a measurement study. IEEE Trans Circ Syst Video Technol 25(12):2013–2025CrossRefGoogle Scholar
  16. 16.
    Chen M, Ma Y, Hao Y, Li Y, Wu D, Zhang Y, Song E (2016) CP-Robot: Cloud-assisted Pillow Robot for Emotion Sensing and Interaction. Industrialiot 2016, Guangzhou, ChinaGoogle Scholar
  17. 17.
    Wan J, Zou C, Ullah S, Lai C-F, Zhou M, Wang X (2013) Cloud-enabled wireless body area networks for pervasive healthcare. IEEE Netw 27(5):56–61CrossRefGoogle Scholar
  18. 18.
    Wan J, Zou C, Zhou K, Lu R, Li D (2014) Iot sensing framework with inter-cloud computing capability in vehicular networking. Electron Commer Res 14(3):389–416CrossRefGoogle Scholar
  19. 19.
    Zhou L, Yang Z, Wen Y, Rodrigues JJ (2014) Distributed wireless video scheduling with delayed control information. IEEE Trans Circ Syst Video Technol 24(5):889–901CrossRefGoogle Scholar
  20. 20.
    Zhou L, Wu D, Zheng B, Guizani M (2014) Joint physical-application layer security for wireless multimedia delivery. IEEE Commun Mag 52(3):66–72CrossRefGoogle Scholar
  21. 21.
    Chen M, Lai C, Wang H (2011) Mobile Multimedia Sensor Networks: Architecture and Routing, EURASIP Journal on Wireless Communications and Networking, Vol. 2011, doi: 10.1186/1687-1499-2011-159
  22. 22.
    Chen M (2013) Towards smart city: M2M communications with software agent intelligence. Multimed Tools Appl 67(1):167–178CrossRefGoogle Scholar
  23. 23.
    Chen M, Wan J, González S, Liao X, Leung V (2014) A survey of recent developments in home m2m networks. IEEE Commun Surv Tutorials 16(1):98–114CrossRefGoogle Scholar
  24. 24.
    Lin K, Wang X, Peng L, Zhu X (2013) Energy-efficient k-cover problem in hybrid sensor networks, The Computer Journal, p. bxt020Google Scholar
  25. 25.
    Lin K, Wang W, Wang X, Ji W, Wan J (2015) Qoe-driven spectrum assignment for 5g wireless networks using sdr. IEEE Wirel Commun 22(6):48–55CrossRefGoogle Scholar
  26. 26.
    Zhou Y, Xiang W, Wang G (2015) Frame loss concealment for multiview video transmission over wireless multimedia sensor networks. IEEE Sensors J 15(3):1892–1901CrossRefGoogle Scholar
  27. 27.
    Zheng K, Ou S, Alonso-Zarate J, Dohler M, Liu F, Zhu H (2014) Challenges of massive access in highly dense lte-advanced networks with machine-to-machine communications. IEEE Wirel Commun 21(3):12–18CrossRefGoogle Scholar
  28. 28.
    Lai C-F, Chao H-C, Lai Y-X, Wan J (2013) Cloud-assisted real-time transrating for http live streaming. IEEE Wirel Commun 20(3):62–70CrossRefGoogle Scholar
  29. 29.
    Chen M (2015) Opnet IoT simulation, Huazhong University of Science and Technology Press, vol 1Google Scholar
  30. 30.
    Wu D, Xue Z, He J (2014) Icloudaccess: Cost-effective streaming of video games from the cloud with low latency. IEEE Trans Circ Syst Video Technol 24(8):1405–1416CrossRefGoogle Scholar
  31. 31.
    Chen M, Zhang Y, Li Y, Hassan M, Alamri A (2015) Aiwac: affective interaction through wearable computing and cloud technology. IEEE Wirel Commun 22(1):20–27CrossRefGoogle Scholar
  32. 32.
    Siraj S, Gupta A, Badgujar R (2012) Network simulation tools survey. Int J Adv Res Comput Commun Eng 1(4):199– 206Google Scholar
  33. 33.
    Chen M (2004) OPNET network simulation, vol 1. Press of Tsinghua UniversityGoogle Scholar
  34. 34.
    Ge X, Yang B, Ye J, Mao G, Wang C-X, Han T (2015) Spatial spectrum and energy efficiency of random cellular networks. IEEE Trans Commun 63(3):1019–1030CrossRefGoogle Scholar
  35. 35.
    Chen B, Butler-Purry KL, Goulart A, Kundur D (2014) Implementing a real-time cyber-physical system test bed in rtds and opnet. In: North American Power Symposium (NAPS), 2014. IEEE, pp 1–6Google Scholar
  36. 36.
    Hossain MS, Muhammad G, Alhamid MF, Song B, Al-Mutib K (2016) Audio-visual emotion recognition using big data towards 5g. Mobile Networks and Applications:1–11Google Scholar
  37. 37.
    Hossain MS (2015) Cloud-supported cyber-physical localization framework for patients monitoringGoogle Scholar
  38. 38.
    Hossain MS, Muhammad G (2016) Cloud-assisted industrial internet of things (iiot)–enabled framework for health monitoring. Computer NetworksGoogle Scholar
  39. 39.
    Fortino G, Parisi D, Pirrone V, Di Fatta G (2014) Bodycloud: a saas approach for community body sensor networks. Futur Gener Comput Syst 35:62–79CrossRefGoogle Scholar
  40. 40.
    Fortino G, Di Fatta G, Pathan M, Vasilakos AV (2014) Cloud-assisted body area networks: state-of-the-art and future challenges. Wirel Netw 20(7):1925–1938CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Junfeng Wang
    • 1
    • 2
  • Xiaobo Shi
    • 1
    • 3
  • Musaed Alhussein
    • 4
  • Limei Peng
    • 5
  • Ying Hu
    • 1
    Email author
  1. 1.School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanChina
  2. 2.School of Information EngineeringZhengzhou UniversityZhengzhouChina
  3. 3.College of Computer and Information TechnologyHenan Normal UniversityXinxiangChina
  4. 4.Computer Engineering DepartmentKing Saud UniversityRiyadhSaudi Arabia
  5. 5.Department of Industrial EngineeringAjou UniversitySuwonSouth Korea

Personalised recommendations