Transitive Grouping for Internet of Things Support IEEE 802.11ah using Integrated Approach

Abstract

With the adoption of IEEE 802.11ah standard, Internet of Things (IoT) and its performance has improved. However, registration time reduction, hidden node problem and efficient channel utilization are issues that have effect on the performance of the IEEE 802.11ah network standard. These issues can be attributed to the failure to allocate appropriate threshold for authentication control and to adjust Restricted Access Window (RAW). These are occasioned by inefficient clustering and station grouping schemes employed. In attempt to address these identified problems, Transitive Grouping (TG) scheme is proposed for the IoT support IEEE 802.11ah network. The TG scheme is a better way of clustering, grouping of stations, and allocation of RAW slot adaptively for an IoT support IEEE 802.11ah network. The TG scheme performance is evaluated in NS-3 environment on the basis of network delay, probability of successful transmission, throughput, channel utilization and registration time metrics. The proposed TG scheme is validated with four popular RAW slot allocation algorithms implemented in 802.11ah namely: RAW Association Identifier (RAd), Traffic Demand-based Stations Grouping (TSG), Hybrid Slotted CSMA/TDMA (HSCT), and M/G/I RAW Slot Allocation (MRA). Simulation results demonstrated that the proposed TG scheme achieved a substantial improvement over the other schemes.