Extension of the IEEE 802.11ah ns-3 simulation module

Tian, Le; Šljivo, Amina; Santi, Sintha Soraya; Poorter, Eli De; Hoebeke, Jeroen; Famaey, Jeroen

doi:10.1145/3199902.3199906

Cited by 41 publications

(24 citation statements)

References 8 publications

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“…The performance evaluation was based on simulation. The simulations were performed using NS-3 4 version 3.23 and the 802.11ah module implemented in [Tian et al 2016] and extended in [Tian et al 2018]. The nodes were randomly distributed within a radius of 100 meters around the access point (AP), which runs the application servers.…”

Section: Simulation Setup and Methodologymentioning

confidence: 99%

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Analyzing QoS metrics in IEEE 802.11ah networks with traffic differentiation

Arnosti¹,

Borin²

2019

Anais Do XXXVII Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos (SBRC 2019)

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The IEEE 802.11ah is one of the most recent wireless protocols that has emerged, aiming to improve Internet of Things (IoT) communication devices. Among the 802.11ah related works that evaluate the Restricted Access Window (RAW) and others medium access control mechanisms, only a few consider Quality of Service (QoS) and inherent traffic heterogeneity in IoT. Nevertheless, the purpose of this work is to compare two RAW scenarios, which consider two types of devices with different traffic patterns and QoS requirements. The results suggest that the increase of medium containment within RAW slots in dense networks may be a limiting factor for providing QoS.

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Section: Simulation Setup and Methodologymentioning

confidence: 99%

“…The file may include multiple RPS and its parameters are described in Table 4. The format of the RAW configuration file is based on the extended implementation of [Tian et al 2018].…”

Section: Summary Of the Simulation Parametersmentioning

confidence: 99%

Analyzing QoS metrics in IEEE 802.11ah networks with traffic differentiation

Arnosti¹,

Borin²

2019

Anais Do XXXVII Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos (SBRC 2019)

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“…While in the full design space, there is no such limitation. Our previously developed IEEE 802.11ah ns-3 simulation module [19], [36] is integrated into the Matlab Surrogate Modeling (SUMO) toolbox to train the RAW model. The SUMO Toolbox is a flexible framework for accurate global surrogate modeling [15], and has already been applied successfully to a wide range of applications.…”

Section: • Stopping Criteriamentioning

confidence: 99%

Optimization-Oriented RAW Modeling of IEEE 802.11ah Heterogeneous Networks

Tian

López-Aguilera

García-Villegas

et al. 2019

IEEE Internet Things J.

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The new medium access method of IEEE 802.11ah, called Restricted Access Window (RAW), divides stations into different groups, and only allows stations in the same group to access the channel simultaneously, in order to reduce collisions and thus achieve better performance (e.g., throughput). However, the existing station grouping strategies only support homogeneous scenarios where all stations use the same modulation and coding scheme (MCS) and packet size. A surrogate model is an efficient mathematical model that represents the behavior of a complex system, trained with a limited set of labeled input-output data samples. In this paper, we present a surrogate model that can accurately predict RAW performance under a given Restricted Access Window (RAW) configuration in heterogeneous networks. Different from the homogeneous scenario, heterogeneous networks are defined by a large number of parameters, leading to an enormous design space, i.e., the order of 10 17 possible data points. This is too big to achieve feasible training convergence. In this paper, we present a novel training methodology that leads to a new design space with highly reduced size, i.e., the order of 10 5 data points. The surrogate model converges when less than 6000 labeled data points are used for training, which is only a tiny portion of the whole design space. The results show that, the relative error between model prediction and simulation results is less than 0.1 for 95% of the data points, in the areas of the design space studied. Its low complexity and high precision make the proposed model a valuable tool to develop real-time RAW optimization algorithms for heterogeneous IEEE 802.11ah networks.Index Terms-IEEE 802.11ah, RAW, surrogate model, heterogeneous networks.

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“…sensors) side by side. As the hardware supporting 802.11ah is not available at the market yet, we experimented with the beacon interval in ns-3 network simulator [12] to investigate the feasibility of in-time delivery of fast control loop traffic. We find the setups for which it is possible to serve the needs of control loops with various cycle-times, explore the scalability of such solutions and derive best practices for network configuration depending on loops' dynamics.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Suitability of IEEE 802.11ah for Low-Latency Time-Critical Control Loops

Seferagic

Moerman

Poorter

et al. 2019

IEEE Internet Things J.

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A number of industrial wireless technologies have emerged over the last decade, promising to replace the need for wires in a variety of use cases. Except for customized Time Division Multiple Access (TDMA) based wireless technologies that can achieve ultra-low latency over a very limited area, wireless communication generally has reliability and latency issues when it comes to industrial applications. Closed loop communication requires high reliability (over 99%), limited jitter and latency, which poses a challenge especially over a wide area measuring in hundreds of meters. Extended coverage is promised with the advent of sub-GHz technologies, one of them being IEEE 802.11ah which is the only one that offers sufficient data rate for frequent bidirectional communication. Thus, we evaluated IEEE 802.11ah for low-latency time-critical control loops. We propose the network setup for adjusting the network dynamics to that of control loops, enabling limited jitter and high reliability. We explore the scalability of IEEE 802.11ah network hosting both control loops and monitoring sensors that periodically transmit measurements. Assigning the control loop end-nodes to dedicated Restricted Access Window (RAW) slot results in over 99.99% successful deliveries. Furthermore, inter-packet delay is concentrated around the cycle-time in the following or preceding beacon interval in case the beacon interval is at least half the value of the shortest cycle-time. Adjusting the beacon interval to the fastest control loop in the network ensures latency requirements at the cost of maximum achievable throughput and energy consumption.

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Extension of the IEEE 802.11ah ns-3 simulation module

Cited by 41 publications

References 8 publications

Analyzing QoS metrics in IEEE 802.11ah networks with traffic differentiation

Analyzing QoS metrics in IEEE 802.11ah networks with traffic differentiation

Optimization-Oriented RAW Modeling of IEEE 802.11ah Heterogeneous Networks

Evaluating the Suitability of IEEE 802.11ah for Low-Latency Time-Critical Control Loops

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