The traditional IEEE 802.11 network is designed for the use of small scale local wireless networks such as home or campus WLANs, where one access point serves a reasonably few number of devices like smartphones, laptops, tablets, and so on. However, the emergence of the Internet of Things (IoT) have changed the scene of wireless communications, while the number of devices rapidly increases and becomes far larger than before. Thus, recently, the IEEE task group ah (TGah) is dedicated to the standardization of a new protocol, called IEEE 802.11ah, which is customized for this type of large-scale networks. IEEE 802.11ah adopts the grouping-based MAC protocol to reduce the contention overhead of each group of devices. However, most existing designs simply randomly assign devices to groups, and less attention has been paid to the problem of forming efficient groups. Therefore, in this paper, we argue that the performance of grouping is closely related to the heterogeneous traffic demands of devices, and propose a load-balanced grouping algorithm to improve channel utilization of each group. Our evaluation shows that the proposed load-balanced grouping outperforms simple random grouping, especially when the network is almost saturated.
['Tung-Chun Chang', 'Chi-Han Lin', 'Kate Ching-Ju Lin', 'Wen-Tsuen Chen']
Load-Balanced Sensor Grouping for IEEE 802.11ah Networks