IEEE 802.11ba — Extremely Low Power Wi-Fi for Massive Internet of Things — Challenges, Open Issues, Performance Evaluation

Bankov, Dmitry; Khorov, Evgeny; Lyakhov, Andrey; Stepanova, Ekaterina

doi:10.1109/blackseacom.2019.8812785

Cited by 13 publications

(7 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, it can be concluded, WiFi-enabled devices are easy to integrate with networks in the vicinity. Furthermore, in addition to low transmission power and energy optimization capabilities, WiFi is the only technology which provides higher bit rate and can support multimedia application like live audio/video streaming and monitoring, not possible with other wireless protocols mentioned above [11], [12]. All these reasons motivated us to make use of 802.11 WiFi adapters in our experimentation setups for the proof of concept.…”

Section: Wireless Ad Hoc Networkmentioning

confidence: 99%

Ephemeral Secrets: Multi-Party Secret Key Acquisition for Secure IEEE 802.11 Mobile Ad Hoc Communication

Bhatti

Saleem

2020

IEEE Access

View full text Add to dashboard Cite

Mobile ad hoc networks consist of wireless nodes and can be established quickly with minimal configuration and cost, because, they do not require any infrastructure in advance. Civil and military applications are using them extensively in emergency and mission-oriented scenarios respectively as multi-party communication systems. Whereas, the multi-party secret key acquisition is one of the acute issues in these low resource wireless ad hoc networks, especially, which are based on IEEE 802.11ah and IEEE 802.11ba (low power WiFi), IEEE 802.15.4(Zigbee), BLE, IEEE 802.15.6 (body-worn or wearable) devices. In this study, a novel low cost and robust approach has been proposed and tested to establish an identical secret key in a multiuser mobile ad hoc environment. We believe, it is one of the groundbreaking contributions toward establishing a cost-effective secret key acquisition solution with respect to memory, computation, and bandwidth. We have used Bloom-Filters to cope with these resource limitations of such wireless setups. The proposed approach has been tested using IEEE 802.11 adapters in a real environment, and we found it to be highly suitable for wireless resource-limited applications. INDEX TERMS Dynamic secret, ephemeral secrets, shared secret, wireless networks, bloom filter, mobile ad hoc networks.

show abstract

Section: Wireless Ad Hoc Networkmentioning

confidence: 99%

Ephemeral Secrets: Multi-Party Secret Key Acquisition for Secure IEEE 802.11 Mobile Ad Hoc Communication

Bhatti

Saleem

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Another group of studies consider wireless sensor networks using different technologies, including the cellular networks [40,41] such as NB-IoT [42], low power wide area networks such as LoRaWAN [43,44], and wireless personal area networks such as ZigBee [45]. Finally, some papers evaluate the benefits of low-power wake-up radios added to existing technologies to reduce power consumption, e.g., see [46,47] for Wi-Fi and 5G networks. However, since this paper is focused on the peculiarities of channel access in Wi-Fi HaLow, we further review the literature specifically on this technology.…”

Section: Related Papersmentioning

confidence: 99%

Resource Allocation for Machine-Type Communication of Energy-Harvesting Devices in Wi-Fi HaLow Networks

Bankov

Khorov

Lyakhov

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

The recent Wi-Fi HaLow technology focuses on adopting Wi-Fi for the needs of the Internet of Things. A key feature of Wi-Fi HaLow is the Restricted Access Window (RAW) mechanism that allows an access point to divide the sensors into groups and to assign each group to an exclusively reserved time interval where only the stations of a particular group can transmit. In this work, we study how to optimally configure RAW in a scenario with a high number of energy harvesting sensor devices. For such a scenario, we consider a problem of device grouping and develop a model of data transmission, which takes into account the peculiarities of channel access and the fact that the devices can run out of energy within the allocated intervals. We show how to use the developed model in order to determine the optimal duration of RAW intervals and the optimal number of groups that provide the required probability of data delivery and minimize the amount of consumed channel resources. The numerical results show that the optimal RAW configuration can reduce the amount of consumed channel resources by almost 50%.

show abstract

“…In real networks, long time intervals without channel listening and the clock drifting lead to a loss of time synchronization between devices. We have started the investigation of the clock drift effect influence on the efficiency of TWT and WUR power saving mechanisms in [35], and, in this paper, we propose more strong and detailed research on this theme. Specifically, we develop mathematical models of different approaches for data transmission with TWT and WUR, conduct an in-depth analysis This work is licensed under a Creative Commons Attribution 4.0 License.…”

Section: Literature Reviewmentioning

confidence: 99%

On the Joint Usage of Target Wake Time and 802.11ba Wake-Up Radio

et al. 2020

Self Cite

View full text Add to dashboard Cite

Energy efficiency is a significant challenge for modern wireless networking devices. It is crucial for the Internet of Things devices, is required for battery-supplied user devices such as smartphones, and is advisable for high-performance devices such as wireless VR headsets. This paper examines the ability of modern Wi-Fi devices to achieve extremely low power consumption when they rarely send and receive data. Two recently developed mechanisms, namely Target Wake Time (TWT) and Wake-Up Radio (WUR), are studied. The first one allows stations to schedule the frame exchanges in advance, while the second one introduces a low-power radio for control information exchange. Although TWT and WUR differ significantly, they both suffer from the clock drift effect that significantly degrades their performance in the case of rare traffic. The paper describes these mechanisms, focusing on their revolutionary features, and presents mathematical models to evaluate the impact of this effect on TWT and WUR mechanism efficiency in terms of energy and channel time consumption. The paper also proposes and thoroughly examines various approaches to the joint and separate usage of TWT and WUR in Wi-Fi networks.

show abstract

IEEE 802.11ba — Extremely Low Power Wi-Fi for Massive Internet of Things — Challenges, Open Issues, Performance Evaluation

Cited by 13 publications

References 9 publications

Ephemeral Secrets: Multi-Party Secret Key Acquisition for Secure IEEE 802.11 Mobile Ad Hoc Communication

Ephemeral Secrets: Multi-Party Secret Key Acquisition for Secure IEEE 802.11 Mobile Ad Hoc Communication

Resource Allocation for Machine-Type Communication of Energy-Harvesting Devices in Wi-Fi HaLow Networks

On the Joint Usage of Target Wake Time and 802.11ba Wake-Up Radio

Contact Info

Product

Resources

About