Markov Model of Modified Unslotted CSMA/CA for Wireless Sensor Networks

Mahmoud, Gamal M.; Sadek, Nayera; Rizk, Mohamed R. M.; Ahmed, Magdy A.

doi:10.1109/icm48031.2019.9021836

Cited by 7 publications

(5 citation statements)

References 7 publications

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“…The approach is applicable to any MAC protocol and does not need to make assumptions about the network traffic. A modified backoff procedure that reduces average delay by up to 30% is proposed by Gamal et al in [20] for the unslotted IEEE 802.15.4 CSMA/CA algorithm. Zhu et al [21] worked on the same problem and found optimal IEEE 802.15.4 MAC contention parameters by maximizing a channel contention efficiency metric for a given traffic model.…”

Section: Related Workmentioning

confidence: 99%

Delay Probability Distributions of Acknowledged CSMA/CA With Finite Re-Transmissions Over Fading Channels

Madariaga,

Oberli,

Constanza Estela

2024

IEEE Access

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The delay distribution observed between the data link layer of a pair of neighbouring nodes in wireless mesh networks is studied. Specifically, we model the delay for unslotted carrier sense multiple access with collision avoidance with acknowledgments and multiple transmission retries under given channel access and block-fading statistics. This medium access control mechanism is used, for instance, by the IEEE 802.15.4 Standard. It has three different possible outcomes: frame transfer success (acknowledgement received), channel access failure and frame transfer failure (no acknowledgement received, all transmission attempts used). We model these outcomes in terms of the maximum allowed number of channel access attempts, the maximum number of transmission attempts, the probability of busy channel and the frame-loss probability. All these parameters are local to each node and hence our model allows for modeling link delays from the perspective of each individual node. This lies in contrast with prior work, based mostly on Markov chain approaches, which tend to be computationally intensive, often mathematically intractable and require taking a global view over the network. We validate our results with Monte-Carlo simulations and show that the proposed model for frame transfer success and frame transfer failure are accurate in terms of the delay distribution and mean value. In the case of channel access failure, the model is less precise but can be used as an upper bound for the expected delay.

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Section: Related Workmentioning

confidence: 99%

Delay Probability Distributions of Acknowledged CSMA/CA With Finite Re-Transmissions Over Fading Channels

Madariaga,

Oberli,

Constanza Estela

2024

IEEE Access

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“…If every node has a transmission probability of τ, then the critical path length, Pc = 1 -(1-τ) N -1, where N is the total number of nodes [18][30]. Channel Access Failure Probability: When a node can locate the channel inactive twice in a row while still within its maximum allowable backoff stages (max csma backoff), this is considered a failed attempt to access the channel [19].…”

Section: Probability Of Assessing Channel Busy During Cca1mentioning

confidence: 99%

Cross-Layer Optimization on Different Data Rates for Efficient Performance in Wireless Sensor Network

Anju,

Bindal,

Bhatia

et al. 2023

IJRITCC

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The traditional protocols used in wireless sensor networks adhere to stringent layering approaches, which decreases the performance of the quality of service (Quality of Service) metrics. As per specifications 802.15.4, wireless sensor networks are inexpensive and energy efficient. It is essential for evaluating the performance of WSNs. Researchers have looked into the fundamental aspects of a single physical layer and the medium access control (MAC) layer protocol using methodologies calculated using several mathematical models or experimental approaches, respectively. In this research, we offer an improved cross-layer analytical model that utilises a thorough combining and interacting of a Markov chain model of the MAC layer's propagation with a model of the PHY layer's propagation. This combination and interaction are described in detail. Various Quality of Service (quality of service) statistics are presented and evaluated, and a cross-layer effectiveness degradation study is conducted under different inputs of multi-parameter vectors. Other parameters, such as Average Wait Time, Reliability, Failure Probability, and Throughput, have been estimated from the simulation results and contrasted with standardised models. The cross-layer model provides a more thorough performance study with various cross-layer parameter sets, some of which comprise distance, power transmission, and offered loads, among other things.

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“…Similarly, OPNET 8 simulate (e.g. the literature 11 , 14 , 15 , 23 ) WSN sensors as OPNET node models (implemented in C) interconnected as OPNET network models. Furthermore, OMNet++ 9 simulation environment modeled (e.g.…”

Section: Background and Related Workmentioning

confidence: 99%

“…modeled as OPNET network) where each PAN can contain a few mobile nodes and routers (that were modeled as OPNET nodes). Furthermore, the work in Gamal et al 15 used OPNET to model and simulate the collision in WSN when sensors (modeled as OPNET nodes) wait for restricted backoff periods.…”

Section: Background and Related Workmentioning

confidence: 99%

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A grid-shaped cellular modeling approach for wireless sensor networks

Al-Zoubi

Wainer

2022

SIMULATION

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WSN (Wireless Sensor Network) applications have been widely used in recent years. We introduce a new method for modeling WSN, based on the specification of the WSN using the Cell-Discrete-Event Systems Specification (DEVS) formalism: the space is partitioned into cells where each cell can be considered a sensor, an obstacle, or anything of a behavior with defined rules. This model is then converted automatically into DEVS model at runtime. We present two case studies analyzing the use of energy in WSN member nodes, which have impact on prolonging the overall network lifetime. We study to analyze energy consumption related to routing and data transmission at the node level, and topology residual energy control methods at the cluster level (i.e. group of sensors) level. The goal is to show how these spatial modeling methods can be used for building WSN models in a simple but efficient fashion.

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Markov Model of Modified Unslotted CSMA/CA for Wireless Sensor Networks

Cited by 7 publications

References 7 publications

Delay Probability Distributions of Acknowledged CSMA/CA With Finite Re-Transmissions Over Fading Channels

Delay Probability Distributions of Acknowledged CSMA/CA With Finite Re-Transmissions Over Fading Channels

Cross-Layer Optimization on Different Data Rates for Efficient Performance in Wireless Sensor Network

A grid-shaped cellular modeling approach for wireless sensor networks

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