An Adaptive Contention Window Scheme for 802.11ah WLANs

Gao, Renzheng; Li, Xiaoying; Hu, Qiang

doi:10.1051/itmconf/20181701016

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…However, most STAs operate in sleep mode in IEEE 802.11ah WLAN, and it is projected that the network would have a considerably greater collision probability at the beginning of a BI than at the end. To mitigate these limitations, the authors in [ 130 ] proposed an adaptive contention window technique in which the contention window size is optimized at the beginning of the BI and subsequently decreased after the transmission is successfully completed. Through simulations, it was demonstrated that the suggested method might improve IEEE 802.11ah WLAN performance.…”

Section: Mac Features Of the Ieee 80211ah And Current Resource Alloca...mentioning

confidence: 99%

Resource Management for Massive Internet of Things in IEEE 802.11ah WLAN: Potentials, Current Solutions, and Open Challenges

Farhad

Pyun

2022

Sensors

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IEEE 802.11ah, known as Wi-Fi HaLow, is envisioned for long-range and low-power communication. It is sub-1 GHz technology designed for massive Internet of Things (IoT) and machine-to-machine devices. It aims to overcome the IoT challenges, such as providing connectivity to massive power-constrained devices distributed over a large geographical area. To accomplish this objective, IEEE 802.11ah introduces several unique physical and medium access control layer (MAC) features. In recent years, the MAC features of IEEE 802.11ah, including restricted access window, authentication (e.g., centralized and distributed) and association, relay and sectorization, target wake-up time, and traffic indication map, have been intensively investigated from various aspects to improve resource allocation and enhance the network performance in terms of device association time, throughput, delay, and energy consumption. This survey paper presents an in-depth assessment and analysis of these MAC features along with current solutions, their potentials, and key challenges, exposing how to use these novel features to meet the rigorous IoT standards.

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Section: Mac Features Of the Ieee 80211ah And Current Resource Alloca...mentioning

confidence: 99%

Resource Management for Massive Internet of Things in IEEE 802.11ah WLAN: Potentials, Current Solutions, and Open Challenges

Farhad

Pyun

2022

Sensors

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“…This section presents some recent works that mitigated the drawbacks of the BEB algorithm in IEEE 802.11 standards, including IEEE 802.11ah [28][29][30][31][32][33][34][35][36]. As mentioned earlier, the IEEE 802.11ah MAC protocol of RAW reduces collisions in highly congested network scenarios by using EDCA and DCF access schemes to manage transmission attempts.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, this kind of threat needs to be mitigated. The authors in [32] proposed a combination mechanism of RAW and adaptive scheme used to calculate an optimal value of the CW size at the beginning of the beacon interval, then slowly halving it when the transmission is successful. The performance of the proposed scheme has been evaluated using the OPNET simulator.…”

Section: Related Workmentioning

confidence: 99%

Pseudorandom sequence contention algorithm for IEEE 802.11ah based internet of things network

et al. 2020

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The IEEE 802.11ah standard relies on the conventional distributed coordination function (DCF) as a backoff selection method. The DCF is utilized in the contention-based period of the newly introduced medium access control (MAC) mechanism, namely restricted access window (RAW). Despite various advantages of RAW, DCF still utilizes the legacy binary exponential backoff (BEB) algorithm, which suffers from a crucial disadvantage of being prone to high probability of collisions with high number of contending stations. To mitigate this issue, this paper investigates the possibility of replacing the existing exponential sequence (i.e., as in BEB) with a better pseudorandom sequence of integers. In particular, a new backoff algorithm, namely Pseudorandom Sequence Contention Algorithm (PRSCA) is proposed to update the CW size and minimize the collision probability. In addition, the proposed PRSCA incorporates a different approach of CW freezing mechanism and backoff stage reset process. An analytical model is derived for the proposed PRSCA and presented through a discrete 2-D Markov chain model. Performance evaluation demonstrates the efficiency of the proposed PRSCA in reducing collision probability and improving saturation throughput, network throughput, and access delay performance.

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“…One of the essential approaches is to modify the contention window size to maximize the network performance. The optimal contention window was used in prior studies, but once the window size was set, it did not alter 21 . The communication problems between nodes can be mitigated when the contention window is wide, which reduces the latency.…”

Section: Introductionmentioning

confidence: 99%

“…The optimal contention window was used in prior studies, but once the window size was set, it did not alter. 21 The communication problems between nodes can be mitigated when the contention window is wide, which reduces the latency. At the same time, it will use less energy because there will be less data retransmission, but it will need more ability to keep a large contention window.…”

mentioning

confidence: 99%

An optimized joint medium access control and routing protocol with iterative contention window adjustment mechanism for a guaranteed lifetime in Internet of Things‐based wireless sensor networks

Nizampatnam

Shankar

Yamuna

2022

Int J Communication

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The problem of extending the lifespan of wireless sensor networks (WSN) based on the Internet of Things (IoT) has been widely investigated over the last 20 years. This paper proposes an Optimized J-RMAC (optimized joint routing and media access control protocol) to guarantee the network lifetime in IoT-based WSN. Initially, all sensor nodes report their position and coverage information to the sink, which uses this information to pick a list of active nodes based on energy usage and active time. Then, the k-covered network is formed to execute the routing task by selecting the active nodes with the largest sensing areas. A multi-objective seagull optimization algorithm (MO-SOA) represents routing paths between the source and destination by considering two objective functions: energy consumption cost and end-to-end delay of a routing path. After that, the contention window of the nodes in the routing path is adjusted using a new iterative adaptive adjustment process of the contention window with adjustment parameters (IAACW-AP) to avoid message conflicts. The proposed protocol is simulated in the NS2 simulator. The performance of the proposed protocol will be compared with existing strategies in terms of network lifetime, packet delivery ratio, communication overhead, energy consumption, and delay.

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An Adaptive Contention Window Scheme for 802.11ah WLANs

Cited by 5 publications

References 11 publications

Resource Management for Massive Internet of Things in IEEE 802.11ah WLAN: Potentials, Current Solutions, and Open Challenges

Resource Management for Massive Internet of Things in IEEE 802.11ah WLAN: Potentials, Current Solutions, and Open Challenges

Pseudorandom sequence contention algorithm for IEEE 802.11ah based internet of things network

An optimized joint medium access control and routing protocol with iterative contention window adjustment mechanism for a guaranteed lifetime in Internet of Things‐based wireless sensor networks

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