Distributed Call Admission Control for VoIP over WLANs based on Channel Load Estimation Paolo Dini, Nicola Baldo, Jaume Nin-Guerrero, Josep Mangues-Bafalluy, IP Technologies Area Sateesh Addepalli, Lillian L. Dai, Cisco Research Centre IEEE ICC 2010 proceedings 報告者：李宗穎

2 Outline Introduction CAC algorithm definition Channel Load Estimation Method Test Environment Setup and Performance Conclusion

3 Introduction a distributed CAC solution in which the decision is performed by the mobile station the STA is in charge of deciding whether a particular AP can offer a suitable service quality a user-centric approach is advantageous for the end-user since the choice of the AP can be made also considering user preferences

4 Related Work Time Between Idle Times (TBIT) the method for measuring the TBIT metric does not consider the time consumed by erroneous transmissions (e.g., collisions) the measured number and duration of the idle time periods are not correct [7] K. Yasukawa, A. G. Forte, H. Schulzrinne “Distributed Delay Estimation and Call Admission Control in IEEE WLANs”, in Proc. of IEEE ICC, June 2009

5 CAC algorithm definition The observed channel can be in two different states: busy, when one or more transmissions are being performed or idle when there are no ongoing transmissions

6 Two different channel Busy channel successful or unsuccessful frame transmissions (packet collisions among active stations and/or channel errors) based on stop-and-wait ARQ model Idle channel no frame transmissions

7 CAC equation (1/2) ρ v + ρ f + ρ bg + ρ bo ≦ 1 ρ v : the channel is occupied by successful voice traffic transmissions ρ f : the channel is occupied by failed transmissions ρ bg : the fraction of time dedicated to successful background traffic transmissions ρ bo : the channel is occupied by the back-off procedure

8 CAC equation (2/2) the AP is said to be eligible for the new VoIP session : the forecast channel load ρ v +ρ f expected after the introduction of the new VoIP session is determined as a function of the actual values of ρ v and ρ f

9 Channel Load Estimation Method T w : a STA can monitor the radio link over a time window of duration T i : the index i denote the generic observed frame exchange sequence DIFS(or AIFS) + DATA + SIFS + ACK

10 ρ v and ρ v (voice traffic) λ new is the cumulative number of packets per second of the two new VoIP flows T new is the duration of the frame exchange sequences for these flows

11 ρ f andρ f (collisions or channel errors) these events cannot be observed directly by a monitoring STA counting the number of PHY errors more than one PHY error can be reported for the same frame, and furthermore PHY errors often happen for other causes some analytical models provide methods hypothesis that every station always has a new packet to transmit, which clearly does not hold for the case of VoIP traffic

12 ρ f andρ f (collisions or channel errors) the estimation of ρ f based only on the observation of successful frame exchange sequences n MSDU : the total number of MAC Service Data Units (MSDUs) which have been successfully delivered n s : first transmission attempt was successful n r : retry transmission was successful

13 Failure Probability P f assume that transmissions fail mostly due to collisions, and that consequently all frame transmission attempts in the observation period have the same failure probability P f

14 Some expected value for ρ f paper can use P f to calculate the expected value E[k] of the number k of failed transmission attempts per MSDU (by stop- and-wait ARQ) r max : retransmission limit

15 Estimation ρ f (1/2) E[c] : the average number of stations having a contemporary collision (approximate E[c] with a value of 2) E[k] : the number k of failed transmission attempts per MSDU

16 Estimation ρ f (2/2) Where λ new has been defined in the previous sub-section, and E[k] is calculated as per equation by substituting

17 ρ bo (backoff procedure) Paper focus on the AP since it is well known that the downlink is the bottleneck in a VoIP over WLAN scenario σ : duration of timeslot

18 Test Environment Setup and Performance The scenario is composed of one AP and several mobile nodes sending/receiving traffic to/from an external fixed node (using ns3 simulator) paper conclude with the evaluation of the performance of the proposed CAC algorithm and its comparison with the TBIT algorithm [7] [7] K. Yasukawa, A. G. Forte, H. Schulzrinne “Distributed Delay Estimation and Call Admission Control in IEEE WLANs”, in Proc. of IEEE ICC, June 2009

19 Determination of P f and ρ bg Homogeneous traffic scenario Heterogeneous codec scenario Multi-rate scenario TCP background traffic scenario

20 Expected failure probability (P f )

21 Background traffic channel time ratio (ρ bg ) voice traffic is normally assigned the highest priority in medium contention paper define ρ bg as the minimum fraction of time which is expected that background traffic will occupy as a consequence of its lower medium access priority

22 CAC Algorithm Evaluation the maximum number n real of user which can be accepted with a good quality (i.e. R>70) in a given scenario and the maximum number n alg of users accepted by the algorithm being considered

23 Measurement campaign results for every tested scenario

24 Fraction of blocked users for G711 codec scenario at 12 Mbps TBIT does not consider the channel time spent due to collisions

25 Fraction of blocked users for G711 codec + 1 TCP connection scenario at 2 Mbps First, TBIT recognizes it as congestion and therefore does not admit new voice calls When most of the traffic in the network is voice, then TBIT underestimates the network congestion

26 Conclusion The channel load estimation method accounts for both the fraction of time spent in successful and erroneous frame transmissions the proposed scheme is more robust and accurate in making CAC decisions than the TBIT scheme, which to our knowledge is the best among the CAC solutions for VoIP over WLAN previously appeared in the literature