2011 IEEE Global Telecommunications Conference - GLOBECOM 2011 2011
DOI: 10.1109/glocom.2011.6133774
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Bandwidth Monitoring in Multi-Rate 802.11 WLANs with Elastic Traffic Awareness

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Cited by 7 publications
(5 citation statements)
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“…Traffic prediction is one of the major issues in measurement-based network control. An accurate prediction of the traffic load in the next time interval helps to provide a high quality of service (QoS) for multimedia applications [ 21 ] to improve resource allocation for cognitive radio systems [ 22 ] and to assist in capacity planning for Wi-Fi networks [ 23 ]. The traffic-related time series prediction problem has been extensively explored in both Ethernet and WiFi networks with different applications [ 23 , 24 ].…”
Section: Related Workmentioning
confidence: 99%
“…Traffic prediction is one of the major issues in measurement-based network control. An accurate prediction of the traffic load in the next time interval helps to provide a high quality of service (QoS) for multimedia applications [ 21 ] to improve resource allocation for cognitive radio systems [ 22 ] and to assist in capacity planning for Wi-Fi networks [ 23 ]. The traffic-related time series prediction problem has been extensively explored in both Ethernet and WiFi networks with different applications [ 23 , 24 ].…”
Section: Related Workmentioning
confidence: 99%
“…Similarly to the mechanism we described in [31], [32], every measurement period, for each active node 1 k the GW computes a running average of the uplink (UL) throughput for all elastic and inelastic flows, denoted by η u k and ν u k , respectively. Likewise, the GW computes a running average of its own downlink (DL) throughput for both the elastic and inelastic traffic it handles for each node k, denoted by η d k and ν d k , respectively.…”
Section: A Preliminariesmentioning
confidence: 99%
“…Again, we consider an IEEE 802.11 BSS managed by an AP capable of monitoring local wireless resources at the MAC layer. As in [17,18] during each measurement period, the AP computes: average size of the frame payload (P ), maximum payload size (P max ), average data rate for data frames and for ACKs, average PER (p e ), and number of active WSs within the BSS (N ). The AP considers a node in the BSS (either itself or a WS) to be active if the node has successfully transmitted at least one data frame within the last measurement period.…”
Section: Computation Of the Saturation Throughputmentioning
confidence: 99%