IoT; Device grouping; IEEE 802.11 ah; Random access
Résumé :
[en] The recent advances in Internet of Things (IoT) have led to numerous emerging applications ranging from eHealthcare to industrial control, which often demand stringent Quality of Service (QoS) requirements such as low-latency and high system reliability. However, the ever-increasing number of connected devices in ultra-dense IoT networks and the dynamic traffic patterns increase the channel access delay and packet collision rate. In this regard, this paper proposes a sector-based device grouping scheme for fast and efficient channel access in IEEE 802.11ah based IoT networks such that the total number of the connected devices within each sector is dramatically reduced. In the proposed framework, the Access Point (AP) divides its coverage area into different sectors, and then each sector is further divided into distinct groups based on the number of devices and their location information available from the cloud-center. Subsequently, individual groups within a sector are assigned to specific Random Access Window (RAW) slots, and the devices within distinct groups in different sectors access the allocated RAW slots by employing a spatial orthogonal access mechanism. The performance of the proposed sectorized device grouping scheme has been analyzed in terms of system delay and network throughput. Our simulation results show that the proposed scheme can significantly enhance the network throughput while simultaneously decreasing the system delay as compared to the conventional Distributed Coordination Function (DCF) and IEEE 802.11ah grouping scheme.
J. Lin and et al, "A survey on Internet of Things: Architecture, enabling technologies, security and privacy, and applications," IEEE Internet Things J., vol. 4, no. 5, pp. 1125-1142, Oct 2017.
L. D. Xu, W. He, and S. Li, "Internet of Things in industries: A survey," IEEE Trans. Ind. Informat., vol. 10, no. 4, pp. 2233-2243, Nov 2014.
ITU-R, "Minimum requirements related to technical performance for IMT-2020 radio interface(s)," https://www.itu.int/md/R15-SG05-C-0040/en, Feb. 2017, document 5D/TEMP/300(Rev.1).
M. Kamel, W. Hamouda, and A. Youssef, "Ultra-dense networks: A survey," IEEE Commun. Surveys Tuts., vol. 18, no. 4, pp. 2522-2545, Fourthquarter 2016.
T. C. Chang, C. H. Lin, K. C. J. Lin, and W. T. Chen, "Load-balanced sensor grouping for IEEE 802.11ah networks," in Proc. IEEE Globecom, Dec 2015, pp. 1-6.
S. K. Sharma and X. Wang, "Live data analytics with collaborative edge and cloud processing in wireless IoT networks," IEEE Access, vol. 5, pp. 4621-4635, 2017.
T. Adame and et al, "IEEE 802.11ah: the WiFi approach for M2M communications," IEEE Wireless Commun., vol. 21, no. 6, pp. 144-152, Dec 2014.
N. Nawaz and et al, "Throughput enhancement of restricted access window for uniform grouping scheme in IEEE 802.11ah," in Proc. IEEE ICC, May 2017, pp. 1-7.
E. Khorov, A. Krotov, and A. Lyakhov, "Modelling machine type communication in IEEE 802.11ah networks," in Proc. IEEE ICCW, June 2015, pp. 1149-1154.
L. Tian, J. Famaey, and S. Latre, "Evaluation of the IEEE 802.11ah restricted access window mechanism for dense IoT networks," in Proc. IEEE WoWMoM, June 2016, pp. 1-9.
J. O. Seo, C. Nam, S. G. Yoon, and S. Bahk, "Group-based contention in IEEE 802.11ah networks," in Proc. IEEE ICTC, Oct 2014, pp. 709-710.
S. Aust, R. V. Prasad, and I. G. M. M. Niemegeers, "Sector-based RTS/CTS access scheme for high density WLAN sensor networks," in Proc. IEEE LCNW, Sept 2014, pp. 697-701.
S.-G. Yoon, J.-O. Seo, and S. Bahk, "Regrouping algorithm to alleviate the hidden node problem in 802.11ah networks," Comput. Netw., vol. 105, pp. 22-32, 2016.
S. Aust, R. V. Prasad, and I. G. M. M. Niemegeers, "IEEE 802.11ah: Advantages in standards and further challenges for sub 1 GHz Wi-Fi," in Proc. IEEE ICC, June 2012, pp. 6885-6889.
L. Zheng and et al, "Performance analysis of group-synchronized DCF for dense IEEE 802.11 networks," IEEE Trans. Wireless Commun., vol. 13, no. 11, pp. 6180-6192, Nov 2014.
P. Sthapit and J.-Y. Pyun, "Station grouping strategy for minimizing association delay in IEEE 802.11ah," IEICE Trans. Commun., vol. E100.B, no. 8, pp. 1419-1427, 2017.
S. Bhandari, S. K. Sharma, and X. Wang, "Cloud-assisted device clustering for lifetime prolongation in wireless IoT networks," in Proc. IEEE CCECE, April 2017, pp. 1-4.
S. K. Sharma and et al, "Physical layer aspects of wireless IoT," in Proc. IEEE ISWCS, Sept 2016, pp. 304-308.
S. Bhandari, S. K. Sharma, and X. Wang, "Latency minimization in wireless IoT using prioritized channel access and data aggregation," in Proc. IEEE Globecom, Dec 2017, pp. 1-6.
P. Chatzimisios, A. C. Boucouvalas, and V. Vitsas, "Packet delay analysis of IEEE 802.11 MAC protocol," Electron. Lett., vol. 39, no. 18, pp. 1358-1359, Sept 2003.
G. Bianchi, "Performance analysis of the IEEE 802.11 distributed coordination function," IEEE J. Sel. A. Commun., vol. 18, no. 3, pp. 535-547, March 2000.
Y. Kim and et al, "Optimal throughput analysis of a super dense wireless network with the renewal access protocol," in Proc. IEEE ICCW, June 2015, pp. 2194-2199.