1. Chapter 12. Traffic and Congestion Control In ATM Networks

2. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Related Standards l ITU-T’s I.371 l ATM Forum’s Traffic Management Spec. Version 4.0

3. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Requirements for ATM Traffic and Congestion Control l no flow control-based congestion control l no feedback based congestion control implicit congestion control = no explicit congestion notification = source deduces the presence of congestion by the loss of data = too late reaction in high-speed ATM (Latency/Speed Effect)  inadequate for ATM

4. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Requirements (cont’d) l CBR support related to cell delay variation (CDV) V(0) = an estimate of the amount of CDV that an application can tolerate V(I) = V(I-1) - [t(I) - (t(I-1) +  )] If V(I) is negative, then that cell is discarded CDV can be reduced by increasing the data rate at the UNI relative to the load and by increasing resources within the network Sources of CDV –queuing delay due to congestion –segmentation, interleaving, OAM cells, SDH overhead...

5. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ATM Traffic-Related Attributes l Traffic Descriptors describe the traffic characteristics of a source and of a connection network establishes a connection only if sufficient resources are available l QoS Parameters characterize the performance of an ATM connection in terms of QoS that it provides l Other feedback attribute for ABR

6. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Traffic Descriptors l Source Traffic Descriptor source characteristics of an ATM flow peak cell rate (PCR) sustainable cell rate (SCR) maximum burst size (MBS) minimum cell rate (MCR) l Connection Traffic Descriptor characteristics of an ATM flow over an ATM connection source traffic descriptor cell delay variation tolerance (CDVT) conformance definition

7. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Source Traffic Descriptor l PCR an upper bound on the traffic that can be submitted by a source on an ATM connection PCR = 1/T, where T: min spacing between cells for CBR and VBR l SCR an upper bound on the average rate of an ATM connection calculated over a time scale that is large relative to T for VBR only SCR < PCR

8. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Source Traffic Descriptor (cont’d) l MBS max number of cells that can be sent continuously at PCR for VBR only l MCR min commitment requested of the network for ABR only

9. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Connection Traffic Descriptor l CDVT a measure of the amount of variation in cell delay that is introduced by network interface (e.g., SDH) and at UNI l Conformance Definition used to specify unambiguously the conforming cells of a connection at UNI net may enforce conformance by dropping or marking cells that exceed the conformance definition GCRA (Generic Cell Rate Algorithm)

10. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul QoS Parameters l Peak-to-peak Cell Delay Variation maxCTD - fixed delay CDV is negotiated during connection establishment whereas CDVT is normally explicitly set at UNI and is not negotiated CDVT is the variation introduced by the source traffic itself (= an upper bound on CDV at UNI) CDV is the difference between the best- and worst- case expected end-to-end CTD

11. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul QoS Parameters (cont’d) l Maximum Cell Transfer Delay (maxCTD) CTD –time between transmission of the last bit of a cell at source UNI and the receipt of the first bit of a cell at the destination UNI –variable due to buffering and cell scheduling maxCTD –max requested delay l Cell Loss Ratio (CLR) ratio of lost cells to total transmitted cells

12. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Traffic Management Framework l Cell Insertion Time react immediately to cells as they are transmitted l Round-Trip Propagation Time respond within the lifetime of a cell in net and may provide a feedback info to source l Connection Duration determine whether a new connection at a given QoS can be accommodated and what performance level will be agreed to l Long Term affect more than one ATM connection and established for long-term use

13. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Traffic Control §ATM Traffic Control Functions l set of actions taken by the network to avoid congestion conditions or to minimize congestion effects l Resource management using VPs l Connection Admission Control (CAC) l Usage Parameter Control (UPC) l Traffic shaping

14. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Resource Management using VPs l Net provides aggregate capacity and performance characteristics on VP and these are shared by VCs in the VP l QoS of a VPC = max QoS of VCCs in the VPC l statistical multiplexing capacity of VPC  average data rates of all VCCs capacity of VPC < aggregate peak demand efficient utilization of capacity difficult to provide fair access preferable to group VCCs into VPCs on the basis of similar traffic characteristics and similar QoS requirements

15. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Connection Admission Control l Net accepts a connection only if it can commit the resources necessary to support that traffic level while at the same time maintaining the agreed QoS of existing connections l if accepted, traffic contract between net & user l net continues provide the agreed QoS as long as the user complies with the traffic contract l traffic contract parameters (table 12.3)

16. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Usage Parameter Control (UPC) l Monitors a connection to determine whether the traffic conforms to the traffic contract once it has been accepted by CAC l Protect net resources from an overload on one connection by detecting violations of assigned parameters and taking appropriate actions

17. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul UPC: Two Separate Functions l Control of PCR & CDVT a traffic flow is compliant if the peak rate of cell transmission does not exceed the agreed peak cell rate, subject to the possibility of cell delay variation within the agreed bound l Control of SCR & burst tolerance

18. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul UPC: Generic Cell Rate Algorithm l Used both for PCR & SCR controls l GCRA(I, L), where I: Increment, L: Limit l peak cell rate algorithm l sustainable cell rate algorithm

19. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul UPC: Peak Cell Rate Algorithm l GCRA(T,  ) T: average interarrival time between cells at PCR if there is no CDVT  : CDVT limit l Virtual Scheduling Algorithm fig. 12.6 (a), 12.7 (a) max # of conforming back-to-back cells =  1 +  / (T -  )  l Leaky Bucket Algorithm fig. 12.6 (b), 12.7 (b)

20. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul UPC: Sustainable Cell Rate Algorithm l GCRA(T s,  s ) T s : interarrival time between cells at SCR if there is no burstiness  s : burst tolerance l MBS =  1 +  s / (T s - T)    s = (MBS - 1)(T s - T)

21. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul UPC: Actions l compliant cells are passed along and noncompliant cells are discarded or tagged (CLP = 1) l fig. 12.10

22. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Selective Cell Discard l at some point beyond the UPC function, net discards (CLP = 1) cells in case of congestion l discard lower-priority cells to protect the performance for higher-priority cells

23. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul Traffic Shaping l smooth out a traffic flow and reduce cell clumping l result in a fairer allocation of resources and a reduced average delay time l Token Bucket token generator produces tokens at a rate of  tokens per sec and places these in token bucket to transmit a cell through the server, one token must be removed from the bucket if bucket is empty, cell is queued waiting for the next token if there is a backlog of cells and an empty bucket, cells are emitted at a smooth flow of  cells per second with no cell delay variation until the backlog is cleared

24. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ATM Traffic Control Approaches l Open-Loop Control for CBR, rt-VBR, nrt-VBR based on traffic contract and UPC no feedback to source concerning congestion l Best-Effort for UBR share the unused capacity in a relatively uncontrolled fashion inefficient: dropped cells cause retransmissions

25. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ATM Traffic Control Approaches (cont’d) l Closed-Loop Control for ABR provide feedback to sources to adjust the load dynamically and avoid cell loss and share the capacity fairly

26. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Characteristics of ABR Service l ABR connections share available capacity l The share of available capacity used by a single ABR connection is dynamic and varies between MCR and PCR l The net provides feedback to ABR sources so that ABR flow is limited to available capacity l For ABR sources that adapt their transmission rate to the provided feedback, a low cell loss ratio is guaranteed

27. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: ABR Connection Characterization Parameters l ACR (Allowed Cell Rate) current rate at which source is permitted to transmit cells l MCR (Minimum Cell Rate) min value that ACR may take (I.e., net will not restrict a source’s flow less than MCR) l PCR (Peak Cell Rate) max value that ACR may take l ICR (Initial Cell Rate) initial value assigned to ACR

28. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Feedback Mechanism l Feedback is provided periodically in the form of a sequence of RM (Resource Management) cells l RM cell contains CI (Congestion Indication) bit, NI (No Increase) bit, ER (Explicit cell Rate) field source transmits one FRM (Forward RM) cell for every (Nrm - 1) data cells for each received FRM, destination transmits it back to source as a BRM (Backward RM) cell

29. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Feedback Mechanism l ACR Control Initially, ACR = ICR linear increase, exponential decrease NI=0, CI=0: ACR  max[MCR,min[ER,PCR,ACR+RIF  PCR]] NI=0, CI=1: ACR  max[MCR,min[ER,ACR(1-RDF)]] NI=1, CI=0: ACR  max[MCR,min[ER,ACR]] NI=1, CI=1: ACR  max[MCR,min[ER,ACR(1-RDF)]]

30. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Feedback Mechanism (cont’d) l Source set CI = 0, NI = 0 or 1 set ER equal to some desired transmission rate l Intermediate ATM switch EFCI marking: cause dest to set CI = 1 in BRM relative rate marking: set CI or NI explicit rate marking: reduce ER value l Destination under normal: if EFCI is marked in the previous data cell, set CI under congestion: set CI or NI, or reduce ER

31. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: RM Cell Format l Header PT = 110 for VC rate control: VCI = 6 l Protocol ID = 1 l Message Type FRM (DIR = 0), BRM (DIR = 1) BECN cell –initially generated by source (BN = 0) –generated by a switch or dest (BN =1)

32. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation l Binary Feedback Scheme use EFCI, CI, NI bits l Explicit Rate Feedback Scheme use ER field

33. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Binary Feedback Scheme l when congestion occurs, switch performs a binary notification either by setting the EFCI on a forward data cell or by setting CI or NI on a FRM or BRM

34. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Binary Feedback Scheme (cont’d) l FIFO Queue dedicate the buffer at each output port to a single FIFO queue if buffer occupancy exceeds a threshold, switch issues binary notifications until buffer occupancy falls below the threshold may use two threshold may unfairly penalize connections passing through a number of switches

35. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Binary Feedback Scheme (cont’d) l Multiple Queues allocate a separate queue to each VC or to each group of VCs a separate threshold for each queue Adv: –a misbehaving source will not affect other VCs –delay and loss behavior of individual VCs are decoupled

36. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Binary Feedback Scheme (cont’d) l Fair Share Notification selective feedback or intelligent marking allocate a fair share of capacity dynamically Fairshare = Target rate / Number of connections when congested, switch marks cells on any VC which satisfies CCR > Fairshare

37. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Explicit Rate Feedback Scheme l General Functions compute the fair share of the capacity for each VC that can be supported determine the current load, or degree of congestion compute an ER for each connection and send that ER to source

38. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Explicit Rate Feedback Scheme (cont’d) l Example Schemes EPRCA (Enhanced Proportional Rate Control Algorithm) ERICA (Explicit Rate Indication for Congestion Avoidance) CAPC (Congestion Avoidance using Proportional Control)

39. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Explicit Rate Feedback Scheme (cont’d) l EPRCA switch keeps track of MACR (Mean ACR) MACR(I) = (1-  )  MACR(I-1) +  CCR(I) if congested, ER  min[ER, DPF  MACR] react to congestion by lowering ERs of VCs that are consuming more than their fair share of capacity

40. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Explicit Rate Feedback Scheme (cont’d) l ERICA selectively adjust VC rates so that the total ER allocated to connections equals the target rate and is allocated fairly Load Factor –LF = Input rate / Target rate Fairshare = Target rate / Number of connections VCshare = CCR / LF ER = min[oldER, max[Fairshare, VCshare] improve fairness under overload conditions

41. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Explicit Rate Feedback Scheme (cont’d) l CAPC if LF > 1, Fairshare = Fairshare  min[ERU, 1+(1-LF)  Rup] if LF < 1, Fairshare = Fairshare  min[ERF, 1-(LF-1)  Rdp] –ERU determines the max increased allowed in the allotment of fair share; ERU > 1 –Rup = a slop parameter between 0.025 and 0.1 –ERF determines the max decrease allowed in the allotment of fair share; ERF = 0.5 –Rdn = a slope parameter between 0.2 and 0.8

42. By Sanghyun Ahn, Dept. of Computer Science and Statistics, University of Seoul ABR: Capacity Allocation (cont’d) §Explicit Rate Feedback Scheme (cont’d) l CAPC (cont’d) if the calculated Fiarshare is lower than ER in RM cell, then set ER to Fairshare simpler to implement than ERICA, very large rate oscillations if RIF is set too high, sometimes lead to unfairness