Achieving proportional fairness in WiFi networks via bandit convex optimization

In this paper, we revisit proportional fair channel allocation in IEEE 802.11 networks. Traditional approaches are either based on the explicit solution of the optimization problem or use iterative solvers to converge to the optimum. Instead, we propose an algorithm able to learn the optimal slot transmission probability only by monitoring the throughput of the network. We have evaluated this algorithm both (i) using the true value of the function to optimize and (ii) considering estimation errors. We provide a comprehensive performance evaluation that includes assessing the sensitivity of the algorithm to different learning and network parameters as well as its reaction to network dynamics. We also evaluate the effect of noisy estimates on the convergence rate and propose a method to alleviate them. We believe our approach is a practical solution to improve the performance of wireless networks as it does not require knowing the network parameters in advance. Yet, we conclude that the setting of the parameters of the algorithm is crucial to guarantee fast convergence.

StegoFrameOrder—MAC Layer Covert Network Channel for Wireless IEEE 802.11 Networks

The proposed StegoFrameOrder (SFO) method enables the transmission of covert data in wireless computer networks exploiting non-deterministic algorithms of medium access (such as the distributed coordination function), especially in IEEE 802.11 networks. Such a covert channel enables the possibility of leaking crucial information outside secured network in a manner that is difficult to detect. The SFO method embeds hidden bits of information in the relative order of frames transmitted by wireless terminals operating on the same radio channel. The paper presents an idea of this covert channel, its implementation, and possible variants. The paper also discusses implementing the SFO method in a real environment and the experiments performed in the real-world scenario.

Experience in measuring Wi-Fi to ZigBee interference using open-source hardware

Considering the growing appliance of wireless technologies in the Internet of Things and Wireless Sensor Networks the question of their coexistence and interoperability becomes extremely important. Wi-Fi and ZigBee technologies already have a long-lasting presence in the market as well as deployment in many systems. Because of their numerous appliances, it is extremely important to measure the impact of one technology on another. This paper has presented the approach of using open-source hardware and software for measuring the interference effects of Wi-Fi to ZigBee. The testing platform is built on Arduino microcontroller boards. This paper describes the experiment, the experimental platform, methodology, and tools used for collecting and analyzing data, as well as the experience gained during the experiments, and its influence on future work. The results presented in this paper give a clear insight into how the IEEE 802.11 networks influence the throughput of IEEE 802.15.4 networks when operating in similar frequencies. According to presented test results, Wi-Fi at distances of about 12m can affect the ZigBee throughput when the central frequency difference is 7 MHz or lower.

Throughput of an IEEE 802.11 Wireless Network in the Presence of Wireless Audio Transmission: A Laboratory Analysis

Wireless networks, including IEEE 802.11-based or Wi-Fi networks, are inexpensive and easy to install and therefore serve as useful connectivity alternatives in areas lacking wired-network infrastructure. However, IEEE 802.11 networks may not always provide the seamless connectivity and minimal throughput required for Industry 4.0 communications because of their susceptibility to interference from other devices operating in the unlicensed “Industrial, Scientific, and Medical” frequency band. Here we analyzed how a wireless audio transmitter operating on this band influences the throughput of an IEEE 802.11 b/g/n network under laboratory conditions. Wireless audio transmission reduced mean throughput by 85%, rendering the IEEE 802.11 b/g/n network nearly unusable. Our analysis suggests that in order for IEEE 802.11 wireless networks to support Industrial 4.0 applications, attention should be paid to the physical layer as well as the data or upper layers, and critical services should not transmit on the 2.4 GHz band. These findings may contribute to understanding and managing IEEE 802.11 wireless networks in various Industry 4.0 contexts.

Research of authentication failure and ARP inject attacks and methods of their detection in IEEE 802.11 networks

Nowadays, Wi-Fi technology is used everywhere in the world: in the offices of large companies, public places and in simple home premises. However, the use of a public transmission medium leads to the possibility of various attacks. This article discusses attacks such as authentication failure and Address Resolution Protocol inject. The considered attacks have shown high efficiency and danger for wireless networks. In this connection, methods of detection and protection against them were proposed. Methods. At the first stage, the concept of how attacks work, their main idea and purpose, were analyzed. At the subsequent stages, for testing, a laboratory stand was created, on which they were simulated. In the course of the experiments, the effectiveness of attacks was found out, and the main phases of attacks and the elements that contribute to their detection were graphically reflected in the article. Main results. As a result of the work done, it was possible to isolate attack vectors and identify their accompanying anomalies. Based on the research materials, mechanisms for detecting and preventing the attacks under consideration were developed. The practical part. All theoretical and experimental materials collected in the article can be used in detecting and preventing attacks on wireless networks by network administra-tors and information security specialists.