Advertisement

Enhancing Efficient Link Performance in ZigBee Under Cross-Technology Interference

  • Zhenquan Qin
  • Yingxiao Sun
  • Junyu Hu
  • Wei Zhou
  • Jialin Liu
Article
  • 11 Downloads

Abstract

The coexistence of heterogenous wireless networks has long been a problem especially with the explosive development in recent years. These heterogenous, such as WiFi, ZigBee and Bluetooth operating in the crowded ISM band, have to compete with each other for scarce spectrum resources, generating cross-technology interference (CTI). Since CTI may lead to severe performance degradation of ZigBee networks, especially under high density WiFi interference. In this paper, we propose a novel adaptive packet delivery (APD) algorithm that enables ZigBee links to achieve enhanced performance under the presence of heavy WiFi traffic. First, we pre-analyze the coexistence of co-located networks, we find the WiFi frame cluster well follow the power law distribution model with burst WiFi traffic, then the PER analysis is also determined to help obtain the probability of delivering packets successfully. Second, we propose a new metric called channel idle state indicator (CISI) to quantify current channel quality. Third, based on CISI and the pre-analysis, we build APD to instruct ZigBee nodes to transmit, besides, we consider the occasion where the packet contains an emergency message. Extensive experimental results show that, under the coverage of different WiFi traffic, our lightweight mechanism can achieve 4x and 1.5x performance gains over WISE and CII. Particularly, when WiFi traffic is 4 Mbps, we can still obtain over 90%. Furthermore, the energy consumption efficiency can be improved markedly with compared protocols.

Keywords

CTI ZigBee WiFi Health telemonitoring system 

Notes

Acknowledgments

The work is supported by “National Natural Science Foundation of China” with No. 61733002 and “the Fundamental Research Funds for the Central University” with No. DUT17LAB16, No. DUT2017TB02. This work is also supported by Tianjin Key Laboratory of Advanced Networking (TANK), School of Computer Science and Technology, Tianjin University, Tianjin, China, 300350.

References

  1. 1.
    Huang J, Xing G, Zhou G, Zhou R (2010) Beyond co-existence: exploiting wifi white space for zigbee performance assurance. In: 2010 18th IEEE international conference on network protocols (ICNP). IEEE, pp 305–314Google Scholar
  2. 2.
    Zhang X, Shin KG (2011) Enabling coexistence of heterogeneous wireless systems: case for zigbee and wifi. In: Proceedings of the twelfth acm international symposium on mobile Ad Hoc networking and computing. ACM, p 6Google Scholar
  3. 3.
    Guo P, Cao J, Zhang K, Liu X (2014) Enhancing zigbee throughput under wifi interference using real-time adaptive coding. In: Proc IEEE international conference on computer communications (INFOCOM). IEEE, pp 2858–2866Google Scholar
  4. 4.
    Noda C, Prabh S, Alves M, Voigt T, Boano CA (2012) Crawdad data set cister/rssi (v. 2012-05-17) DownloadedGoogle Scholar
  5. 5.
    Yi P, Iwayemi A, Zhou C (2011) Developing zigbee deployment guideline under wifi interference for smart grid applications. IEEEIEEE Trans Smart Grid 2(1):110–120CrossRefGoogle Scholar
  6. 6.
    Stabellini L, Zander J (2010) Energy-efficient detection of intermittent interference in wireless sensor networks. International Journal of Sensor Networks 8(1):27–40CrossRefGoogle Scholar
  7. 7.
    Botta A, Dainotti A, Pescapè A (2012) A tool for the generation of realistic network workload for emerging networking scenarios. Comput Netw 56(15):3531–3547CrossRefGoogle Scholar
  8. 8.
    Hu J, Qin Z, Sun Y, Shu L, Lu B, Wang L (2016) Cii: a light-weight mechanism for zigbee performance assurance under wifi interference. In: 2016 25th international conference on computer communication and networks (ICCCN). IEEE, pp 1–9Google Scholar
  9. 9.
    Qiu T, Chen N, Li K, Atiquzzaman M, Zhao W (2018) How can heterogeneous internet of things build our future: a survey. IEEE Communications Surveys & TutorialsGoogle Scholar
  10. 10.
    Qiu T, Zheng K, Han M, Chen CP, Xu M (2018) A data-emergency-aware scheduling scheme for internet of things in smart cities. IEEE Trans Ind Inf 14(5):2042–2051CrossRefGoogle Scholar
  11. 11.
    Qiu T, Zhao A, Xia F, Si W, Wu DO, Qiu T, Zhao A, Xia F, Si W, Wu DO (2017) Rose: robustness strategy for scale-free wireless sensor networks. IEEE/ACM Transactions on Networking (TON) 25(5):2944–2959CrossRefGoogle Scholar
  12. 12.
    Hou Y, Li M, Yuan X, Hou YT (2014) Cooperative cross-technology interference mitigation for heterogeneous multi- hop networks. In: 2014 Proceedings IEEE INFOCOM, pp 880– 888Google Scholar
  13. 13.
    Mohammad M (2015) Tackling self interference, cross-technology interference and channel fading in wireless sensor networks. In: ACM conference on embedded networked sensor systems, pp 503–504Google Scholar
  14. 14.
    Bayhan S, Zubow A, Wolisz A (2017) Coexistence gaps in space: cross-technology interference-nulling for improving lte-u/wifi coexistenceGoogle Scholar
  15. 15.
    Li S, Li S, Shafagh H, Gross J, Duquennoy S (2016) Crosszig: combating cross-technology interference in low-power wireless networks. In: International conference on information processing in sensor networks, p 10Google Scholar
  16. 16.
    Yang P, Yan Y, Li XY, Zhang Y, Tao Y, You L (2016) Taming cross-technology interference for wi-fi and zigbee coexistence networks. IEEE Trans Mob Comput 15(4):1009–1021CrossRefGoogle Scholar
  17. 17.
    Wang S, Yin Z, Song MK, He T (2017) Achieving spectrum efficient communication under cross-technology interference, pp 1–8Google Scholar
  18. 18.
    Hou Y, Li M, Yu S (2017) Making wireless body area networks robust under cross-technology interference. IEEE Trans Wirel Commun 16(1):429–440CrossRefGoogle Scholar
  19. 19.
    Chen G, Dong W, Zhao Z, Gu T (2017) Towards accurate corruption estimation in zigbee under cross-technology interference. In: IEEE international conference on distributed computing systems, pp 425–435Google Scholar
  20. 20.
    Zheng X, Cao Z, Wang J, He Y, Liu Y (2017) Interference resilient duty cycling for sensor networks under co-existing environments. IEEE Trans Commun 65(7):2971–2984CrossRefGoogle Scholar
  21. 21.
    Zheng X, Cao Z, Wang J, He Y, Liu Y (2014) Zisense: towards interference resilient duty cycling in wireless sensor networks. In: Proceedings of the 12th ACM conference on embedded network sensor systems. ACM, pp 119–133Google Scholar
  22. 22.
    Afifi G, Halawa HH, Daoud RM, Amer HH (2016) Dual protocol performance using wifi and zigbee for industrial wlan. In: 2016 24th Mediterranean conference on control and automation (MED). IEEE, pp 749–754Google Scholar
  23. 23.
    Shi G, Li K (2017) Cooperation and communication between wifi and zigbee. In: Signal interference in WiFi and ZigBee networks. Springer, pp 79–90Google Scholar
  24. 24.
    Zhang W, Zhou Y, Suresh MA, Stoleru R (2017) Performance analysis and tuning of coexisting duty cycling wifi and wireless sensor networks. In: 2017 14th annual IEEE international conference on sensing, communication, and networking (SECON). IEEE, pp 1–9Google Scholar
  25. 25.
    Kim SM, He T (2015) Freebee: cross-technology communication via free side-channel. In: Proc. ACM international conference on mobile computing and networking (MobiCom). ACM, pp 317–330Google Scholar
  26. 26.
    Yuan W, Wang X, Linnartz J-PM, Niemegeers IG (2013) Coexistence performance of IEEE 802.15. 4 wireless sensor networks under IEEE 802.11 b/g interference. Wirel Pers Commun 68(2):281–302CrossRefGoogle Scholar
  27. 27.
    Zhao Z, Wu X, Zhang X, Zhao J, Li X-Y (2014) Zigbee vs wifi: understanding issues and measuring performances of their coexistence. In: Proc IEEE performance computing and communications conference (IPCCC). IEEE, pp 1–8Google Scholar
  28. 28.
    Yan Y, Yang P, Li X-Y, Zhang Y (2017) Coffee: coexist wifi for zigbee networks: a frequency overlay approach. In: Proceedings of the ACM turing 50th celebration conference-China. ACMGoogle Scholar
  29. 29.
    Dong W, Yu J, Liu X (2016) Care: corruption-aware retransmission with adaptive coding for the low-power wireless. In: IEEE international conference on network protocols, pp 235–244Google Scholar
  30. 30.
    Kim Y, Lee S, Lee S (2016) Coexistence of zigbee-based wban and wifi for health telemonitoring systems. IEEE Journal Of Biomedical And Health Informatics 20(1):222–230CrossRefGoogle Scholar
  31. 31.
    Gomes RD, Rocha GB, Lima Filho AC, Fonseca IE, Alencar MS (2014) Distributed approach for channel quality estimation using dedicated nodes in industrial wsn. In: 2014 IEEE 25th annual international symposium on personal, indoor, and mobile radio communication (PIMRC). IEEE, pp 1943–1948Google Scholar
  32. 32.
    Liang C-JM, Priyantha NB, Liu J, Terzis A (2010) Surviving wi-fi interference in low power zigbee networks. In: Proc ACM conference on embedded networked sensor system. ACM, pp 309–322Google Scholar
  33. 33.
    Yubo Y, Panlong Y, Xiangyang L, Yue T, Lan Z, Lizhao Y (2013) Zimo: building cross-technology mimo to harmonize zigbee smog with wifi flash without intervention. In: Proc ACM international conference on mobile computing and networking (MobiCom) ACM, pp 465–476Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of SoftwareDalian University of TechnologyDalianChina

Personalised recommendations