Adaptive medium access control protocol of Wifi-Halow for home machine-to-machine network

IEEE 802.11ah is a Wi-Fi standard designed to support the Internet of Things (IoT) and Machine-to-machine (M2M) concept. While showing positive promises, the lack of clarity on the implementation is hindering the network from reaching its full potential. Contention window (CW) has been studied intensively for conventional Wi-Fi but remain unexplored for Wi-Fi HaLow. Besides, the parameters of new mechanism are not defined optimally even though the procedure is detailed. The increasing exibility of wireless network card used also raises the concern of resources availability due to selfish attack. Therefore, work can be done on these aspects to improve its performance and introduce a new dimension of adaptation. Firstly, this work proposed a novel algorithm known as probability-based opportunity dynamic adaptation (PODA) of CW for home M2M network. The relationship between channel winning opportunity and CW of the nodes is detailed and the CW of the station can be adapted to achieve target resource share. In the scenario considered, the network saturation throughput is improved by 23 percent compared to the existing model. Next, the fundamental of RAW mechanism is analysed. The performance fluctuation due to non-optimal RAW duration is avoided through determine the optimal RAW slot duration for RAW group of different traffic intensity. Scaling the RAW slot duration according to the group's traffic allows better channel utilisation and improve the network throughput by 14 percent in dense IoT network (n > 2000). Lastly, a novel punishment scheme is suggested based on the replicator dynamic of Evolutionary Game Theory. The results show that the proposed algorithm is capable of determining the suitable degree of punishment to handle the selfish attack effectively and prevent the performance degradation of at least 8 percent, 300 percent and 75 percent in terms of throughput, delay, and energy efficiency respectively.

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