So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more demanding application requirements could not be met and legacy Internet technologies such as Transmission Control Protocol/Internet Protocol (TCP/IP) could not be used. This has changed with the advent of the new IEEE 802.11ah Wi-Fi standard, which is much more suitable for reliable bidirectional communication and high-throughput applications over a wide area (up to 1 km). The standard offers great possibilities for network performance optimization through a number of physical- and link-layer configurable features. However, given that the optimal configuration parameters depend on traffic patterns, the standard does not dictate how to determine them. Such a large number of configuration options can lead to sub-optimal or even incorrect configurations. Therefore, we investigated how two key mechanisms, Restricted Access Window (RAW) grouping and Traffic Indication Map (TIM) segmentation, influence scalability, throughput, latency and energy efficiency in the presence of bidirectional TCP/IP traffic. We considered both high-throughput video streaming traffic and large-scale reliable sensing traffic and investigated TCP behavior in both scenarios when the link layer introduces long delays. This article presents the relations between attainable throughput per station and attainable number of stations, as well as the influence of RAW, TIM and TCP parameters on both. We found that up to 20 continuously streaming IP-cameras can be reliably connected via IEEE 802.11ah with a maximum average data rate of 160 kbps, whereas 10 IP-cameras can achieve average data rates of up to 255 kbps over 200 m. Up to 6960 stations transmitting every 60 s can be connected over 1 km with no lost packets. The presented results enable the fine tuning of RAW and TIM parameters for throughput-demanding reliable applications (i.e., video streaming, firmware updates) on one hand, and very dense low-throughput reliable networks with bidirectional traffic on the other hand.
The main purpose of running ns-3 simulations is to generate relevant data sets for further study. There are two strategies to generate output from ns-3, either using generic predefined bulk output mechanisms or using the ns-3's Tracing system. Both require parsing the raw output data to extract and process the data of interest to obtain meaningful information. However, parsing such output is in most cases time consuming and prone to mistakes. Post-processing is even harder when a large number of simulations needs to be analyzed and even the tracing system cannot simplify this task. Moreover, results obtained this way are only available once the simulation is finished.Therefore, we developed a user-friendly interactive visualization and post-processing tool for IEEE 802.11ah called ahVisualizer. Beside the topology and MAC configuration, ahVisualizer also plots our traces for each node over time during the simulation, as well as averages and standard deviations for each traced parameter. It can compare all the measured values across different simulations. Users can easily download figures and data in various formats. Moreover, it includes a post-processing tool which plots desired series, with desired fixed parameters, from a large set of simulations. This paper presents the ahVisualizer, its services and its architecture and shows how this tool enables much faster and easier data analysis and monitoring of ns-3 simulations with 802.11ah.
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