A comprehensive simulation study of slotted CSMA/CA for IEEE 802.15.4 wireless sensor networks

Koubâa, Anis; Alves, Mário; Tovar, Eduardo

doi:10.1109/wfcs.2006.1704149

Cited by 158 publications

(100 citation statements)

References 3 publications

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“…In [25,26,27] the performance of slotted CSMA/CA and the impact of various beacon order values on throughput, average delay and successful transmissions has been studied, and in [28] the authors evaluated the performance of the unbeaconed 802.15.4 MAC as the number of sensor networks increases. The impact of the backoff exponent parameters (in particular macMinBE ) and payload size have been studied in [29,30] for IEEE 802.15.4 and Zigbee.…”

Section: Related Workmentioning

confidence: 99%

Mutual interference in large populations of co-located IEEE 802.15.4 body sensor networks—A sensitivity analysis

Moravejosharieh

Willig

2016

Computer Communications

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We consider scenarios where a large number of wireless body sensor networks (WBSN) meets at the same location, as can happen for example at sports events, and assess the impact of their mutual interference on their achievable transmission reliability. In particular, we consider several of MAC-and application parameters for a range of static and dynamic schemes for allocating WBSNs to frequencies, and determine their relative impacts on achievable performance. Our results indicate that parameters related to the MAC backoff scheme have by far the largest impact on performance, and that frequency adaptation can provide substantial performance benefits.

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Section: Related Workmentioning

confidence: 99%

Mutual interference in large populations of co-located IEEE 802.15.4 body sensor networks—A sensitivity analysis

Moravejosharieh

Willig

2016

Computer Communications

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“…The nodes are not allowed to sleep and the entire superframe duration is active and set to be long enough. The reason for this is to accurately approximate the CSMA/CA scheme as non-persistent CSMA, and neglect the effect of finite superframe duration [3]. 3.…”

Section: Model Assumptions and Approximationsmentioning

confidence: 99%

“…Solving Appendix A equations for class-n1 node will give us the long-run proportions of transitions into the states, while using eqn. 3 we can obtain the channel access probability p n1 t = 0.0090 and the conditional probability for a class-n1 node to start a transmission p n1 t|(2)i = 0.0629 (eqn. 7).…”

Section: Solving the Case Of Studymentioning

confidence: 99%

“…(macM inBE n − macM axBE n ). Figures 12 and 13 show the throughput, probability of delivery and latency in case of 2 different types of nodes, 6 nodes with p n1 b obtained from macM inBE n1 = 0, macM axBE n1 = 5, that will be denoted in the figures as p n1 b = [0, 5], and 6 with p n2 b = [3,5] (macM inBE n2 = 3, macM axBE n2 = 5). The throughput differentiation obtained in this scenario is similar to the case of using CW n to differentiate nodes, but with a lesser aggregate value and a significant higher absolute energy consumption for class-n1 in full saturated mode, see Table 2 and Table 4.…”

Section: Impact Of a Single Parameter Modification Cw Nmentioning

confidence: 99%

“…In particular, its beaconenabled mode featuring a novel slotted access protocol in its contention access period (CAP) has spurred most attention 1 . Many preliminary simulation studies [2,3] have been conducted, and several accurate analytical models have been introduced. These analytical models follow two main approaches.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Generic Markov model of the contention access period of IEEE 802.15.4 MAC layer

Recas

Khaled

Barrio

et al. 2014

Digital Signal Processing

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The IEEE-802.15.4 standard is poised to become the global standard for low data rate, low energy consumption Wireless Sensor Networks. By assigning the same sets of contention access parameters for all data frames and nodes, the Contention Access Period (CAP) of the slotted IEEE-802.15.4 currently provides an even channel access functionality and no service differentiation. However, some applications may require service differentiation and traffic prioritization support to accommodate high-priority traffic (e.g., alarms). In order to simulate a scenario in which different sets of access parameters for different node classes can be configured, this paper develops a Markov-chainbased model of the CAP of the IEEE-802.15.4-MAC. Our Markov model can be used to evaluate the impact of mixing node classes in important factors like the throughput, energy consumption, probability of delivery and the packet latency. The model has been used to provide traffic differentiation in a high saturation scenario in which a set of nodes can be configured to increase 76% the probability of sending a packet and reduce 58% latency, with a 69% energy penalty, in comparison with a standard scenario. The accuracy of the Markov model is validated by extensive ns-2 simulations.

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Analysis and Clustering of Sensor Recorded Data to Determine Sensors Consuming the Least Energy

Abbi¹,

Arora²,

Gupta³

et al. 2022

Smart and Sustainable Approaches for Optimizing Performance of Wireless Networks

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A comprehensive simulation study of slotted CSMA/CA for IEEE 802.15.4 wireless sensor networks

Cited by 158 publications

References 3 publications

Mutual interference in large populations of co-located IEEE 802.15.4 body sensor networks—A sensitivity analysis

Mutual interference in large populations of co-located IEEE 802.15.4 body sensor networks—A sensitivity analysis

Generic Markov model of the contention access period of IEEE 802.15.4 MAC layer

Analysis and Clustering of Sensor Recorded Data to Determine Sensors Consuming the Least Energy

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