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The IEEE 802.11ah standard has been developed to provide Internet access to a large number of devices in the Internet of Things (IoT) and machine-to-machine (M2M) networks. To handle contention from a large number of devices and reduce the collision probability, IEEE 802.11ah partitions nodes into groups by adopting a group- based MAC protocol. The formed groups may consist of nodes with different traffic patterns and hence, the data rate requirements of nodes in a group (and consequently the groups themselves) may not be uniform. To maximize the throughput while minimizing unfairness across groups, this paper formulates fair scheduling in IEEE 802.11ah networks as a multi-objective optimization problem. To maintain fairness among the nodes in a group, contention window size selection of nodes is formulated as an integer programming problem. Since it is difficult to solve these problems in real time, heuristic methods are also proposed. Performance of the proposed methods is evaluated in a dense IoT network and compared with the existing methods. As the number of nodes and groups increase, the proposed method consistently shows a superior performance in terms of fairness, throughput, delay, and power consumption, compared to the existing methods. |
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