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Enregistrement W2096054917 · doi:10.1109/ccnc.2007.17

Performance Analysis of IEEE 802.11 DCF with Heterogeneous Traffic

2007· article· en· W2096054917 sur OpenAlex

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Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineComputer Science
ThématiqueWireless Networks and Protocols
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésDistributed coordination functionComputer scienceIEEE 802.11PollingComputer networkNetwork allocation vectorQuality of serviceService setIEEE 802.11e-2005Access controlRandom accessInter-Access Point ProtocolIEEE 802.11sThroughputWi-FiWireless networkWirelessTelecommunicationsWireless mesh networkWi-Fi array

Résumé

récupéré en direct d'OpenAlex

An analytical model is proposed for the perfor- mance study of IEEE 802.11 distributed coordination function (DCF) with finite traffic load. Based on the model, average medium access control (MAC) sublayer service time of a frame and channel throughput are obtained. The model is further extended for the performance analysis of DCF with mixed voice and data traffic. The maximum number of voice connections supported in IEEE 802.11 WLAN under various background data traffic is derived. The results are useful for effective call admission control in IEEE 802.11 WLAN. Extensive simulations are performed to validate our analysis. I. INTRODUCTION The IEEE 802.11 standard (1) has been widely deployed around the world. Its medium access control (MAC) sublayer specifies two modes, the mandatory distributed coordination function (DCF) and the optional point coordination function (PCF). DCF is a distributed random access mechanism that is suitable for ad hoc networks, while PCF is a centralized polling based mechanism that can only work in infrastructure- based wireless LANs (WLANs). Due to its inefficient polling schemes and limited Quality-of-Service (QoS) provisioning, PCF is not widely implemented in practice. Therefore, in this paper, we study the performance of the dominant DCF in various scenarios. To date most research work in the literature (e.g., (2)-(4)) focuses on the study of DCF performance in the saturation case, in which every station in the network always has frames waiting for transmission. However, when there are more than In this paper, we first propose an analytical model to study the DCF throughput and average MAC service time under various load conditions for a single traffic type. It is based on the fundamental relationship between the mean MAC service time and the mean traffic arrival rate, and thus applicable to general traffic arrival processes. The proposed model improves the one in (10) in several aspects such as more accurate calculation of the average backoff time and the average number of transmission trials of a frame. Moreover, by comparing the obtained average MAC service time for a frame with the given average frame inter-arrival time, whether or not a station is in the saturated state can be accurately determined with the proposed model. The maximum number of stations that can be supported in such a network is also obtained. This information is critical to the design of admission control schemes that are usually adopted for QoS support in a network. It is worthy to note that this information cannot be readily obtained from the analysis of a saturation case. As VoIP over WLAN becomes more and more popular, it is instructive to study analytically the performance of DCF in a WLAN with mixed voice and data traffic. However, little work on this thread has been reported. In this paper, we carefully extend the proposed model to study the performance of DCF in such a situation. Using the extended model, the maximum number of voice stations that can be supported in the presence of a certain amount of data traffic can be obtained. On the other hand, the data throughput can also be obtained, given the number of voice stations in the WLAN. The rest of the paper is organized as follows. The IEEE 802.11 DCF is briefly reviewed in Section II. Section III presents the proposed analytical model for a single traffic type. Section IV extends the model to mixed voice and data traffic. Numerical results of both analysis and simulations for the two scenarios are given in Section V. Finally, we conclude the paper in Section VI.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,292
Score d'incertitude au seuil0,301

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,242
Écart entre enseignants0,229 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

En bref

Citations24
Publié2007
Routes d'admission1
Résumé présentoui

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