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QoS I

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QoS I

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  1. QoS I Do Hyeong Im 2002. 04. 30

  2. Outline • Controlling high-bandwidth flows at the congested router • Providing quality of service guarantees without per-flow state

  3. Controlling high-bandwidth flows at the congested router

  4. Contents • Introduction • Related work • RED-PD • Identifying high bandwidth flows • Preferential dropping • Evaluation • Conclusions

  5. Introduction • FIFO queuing at the router • Simple to implement and well-suited to the heterogeneity of the Internet • It does not protect other flows from high-bandwidth flows • Per-flow scheduling mechanisms • Providing max-min fairness • But keeping state for all the flows

  6. Related work (1) • RED • To control the average queue length • Poor performance under changing traffic load • CSFQ (Core-Stateless Fair Queuing) • To achieve fair queuing without per-flow state in the core routers • To require an extra field in the packet headers • FRED (Flow Random Early Detection) • The dropping probability of a flow depend on the number of buffered packets from that flows • SRED (Stabilized RED) • Cache of recently seen flows to determine the high bandwidth flows

  7. Related work (2) • SFB (Stochastic Fair Blue) • Multiple levels of hashing to identify high-bandwidth flows • CHOKe • An incoming packet is matched against a random packet in the queue • When the number of flows is large and the high-bandwidth flows have only a few packets in the queue

  8. RED-PD (1) • Identifying high bandwidth flows • Preferential dropping

  9. RED-PD (2) • Difference from other schemes • To improve the performance of low-bandwidth flow using a small amount of state • Predictable effect on the traffic going through the router

  10. Identifying high bandwidth flows (1) • Using the RED drop history • To identify flows that are sending more than ƒ(r,p) , the reference TCP flow’s rate( RTT r and packet drop rate p)

  11. Identifying high bandwidth flows (2) • Congestion epoch length • Maintaining the packet drop history over K x CL(r,p) seconds • Partitioning the history into M lists • RED-PD identifies flows with losses in at least K of M lists • K = 3, M = 5, r = 40ms and p = 1%

  12. Preferential dropping (1) • Pseudo code for reducing a flow’s dropping probability

  13. Preferential dropping (2) • Pseudo code for increasing a flow’s dropping probability

  14. Evaluation (1) • Probability of identification

  15. Evaluation (2) • Fairness Multiple CBR flows flow 1 : 0.1Mbps, flow 2 : 0.5 Mbps, every subsequent flow : 0.5 Mbps more than the previous flow Mix of TCP and CBR flows flow 1-9 : TCP flows with RTTs of 30,50,70 ms flow 10-12 : CBR flows with 5,3,1 Mbps respectively

  16. Evaluation (3) • Response time • The speed of RED-PD’s reaction depends on the ambient drop rate and the arrival rate of the monitored flow 1 CBR flow and 9 TCP flows The CBR flow starts with a rate of 0.25 Mbps, increases it to 4 Mbps at t=50s, and decreases it back to 0.25 Mbps at t=250s. The RTT of the TCP flows ranged from 30 to 70 ms.

  17. Evaluation (4) • Effect of R, the target RTT • Increasing R • More flows are monitored • Decreasing the ambient drop rate • Increasing the bandwidth available to the unmonitored flow

  18. Conclusions • RED-PD • Using drop history to identify high-bandwidth flows and controlling their throughput in times of congestion • Applicable to the current Internet

  19. Providing quality of service guarantees without per-flow state

  20. Contents • Introduction • Related work • Quality of service model • Signaling protocol • Fault tolerance • Dynamic packet scheduling • Region aggregation • Conclusions

  21. Introduction • Improving the QoS provided by Internet • Integrated service (Intserv) • QoS is based on scheduling protocol • Each router maintains per-flow state • Scalability problem • Difficult to maintain in a distributed environment • Differentiated service(Diffserv) • A few bits are reserved in each packet to indicate its per-hop behavior(PHB) • At each router packets are classified and forwarded according to their PHB • High levels of QoS and network utilization cannot be accomplished

  22. Related work (1) • Some attempts to provide the QoS level of Intserv without any per-flow state at the core routers • The signaling protocol and the packet scheduling protocol must function without per-flow state • Dynamic packet state • Each packet carries enough information to reproduce its deadline at each router • Unable to compute the deadline accurately if a channel has a variable delay • Flow aggregation • Cannot be used across multiple domains

  23. Related work (2) • Signaling methods without per-flow state • Observation methods • To estimate the resource requirement by observing the traffic through the router • Inaccurate estimation • Bandwidth broker methods • Resource reservation is managed by a bandwidth broker • Centralized brokers are vulnerable to faults • Distributed brokers have the difficulty of maintaining their state synchronized

  24. Quality of service model (1) • Some notations bandwidth reserved for flow f ith packet of f, i≥1 length of packet pf,i maximum of Lf,j ,where 1≤j ≤i maximum packet length at s arrival time of pf,i at scheduler s exit time of pf,i from s bandwidth of the output channel of s upper delay bound of the output channel of s

  25. Quality of service model (2) Ss,f,i the time at which the first bit of pf,i is forwarded by s Fs,f,i the time at which the last bit of pf,i is forwarded by s Rf forwarding rate of s Ss,f,1 = As,f,1 Ss,f,i = max(As,f,i, Fs,f,(i-1)) , for every i, i >1 Fs,f,i = Ss,f,i + Ls,f,i / Rf , for every i, i≥1 • Rate-guaranteed scheduler Es,f,i≤ Ss,f,i + δs,f,i , for every input flow f of s and every i, i >1 δs,f,i the delay of packet pf,i at scheduler s Ss,f,i + δs,f,i deadline of at s

  26. Quality of service model (3) • The delay of a packet across a sequence of schedulers • Let t1, t2,…,tkbe a sequence of k rate-guaranteed schedulers traversed by flow f , for all i where

  27. Quality of service model (4) • Scheduling test • To ensure packets exit by their deadline • Rate-dependent delay (1) • Rate-independent delay • For all t, t > 0, (2) where δs,fis the delay of flowfat schedulers

  28. Signaling protocol (1) • How much information is needed? • In case (1), the total of the reserved rates of flows and the rate of output channel • In case (2), a count of input flows in each (rate, delay) pair • Objective • To maintain the above information current at each node • Soft state • Each flow periodically send Refresh messages along the path to its destination

  29. Signaling protocol (2) • We assume the scheduler uses rate dependent delay and test (1) • Each scheduler s updates its state every T seconds in the following way: SumRatess := ShadowSumRatess; ShadowSumRatess := 0; SwapBitss := ¬ SwapBitss; • Whenever s receives a Refresh message from f, the following is performed ifbf,s≠ SwapBitssthen ShadowSumRatess := ShadowSumRatess + Rf; bf,s := SwapBitss end if forward Reserve towards the destination of f • When the destination receives this message, it returns a RefreshAck message back to the source of f

  30. Signaling protocol (3) • When a new flow f is created • Upon receiving a Reserve message from f at s ifSumRatess + Rf≤ Cs then ShadowSumRatess := ShadowSumRatess + Rf; SumRatess := SumRatess + Rf; bf,s := SwapBitss ; forward Reserve towards the destination of f else Return a Reject message towards the source of f end if • Upon receiving a Reject message for flow f ifSwapBitss= bf,sthen ShadowSumRatess := ShadowSumRatess - Rf ; SumRatess := SumRatess - Rf; else SumRatess := SumRatess - Rf; endif Forward Reject towards the source off

  31. Signaling protocol (4)

  32. Signaling protocol (5) • How often should the source of a flow send a Refresh message? • D : on the time for signaling message to traverse the network • The interval between the successive transmissions of Refresh messages should be at most T - D

  33. Fault tolerance • Delayed or lost signaling messages • If a source does not receive a RefreshAck, then the source terminates the flow • This should occur rarely • Link failure & Process failure • The path from source to destination may change before the flow is terminated • Routing changes • If the path of f changes, its message are dropped where the change occurred,causing the termination of f

  34. Dynamic packet scheduling (1) • Consider two consecutive schedulers, s and t, of flow f At,f,i≤ St,f,i ≤ Ss,f,i + Δs,f,i +πs assume At,f,i = Ss,f,i + Δs,f,i +πs for all pf,i then St,f,i = At,f,i = Ss,f,i + Δs,f,i +πs • Before s forwards pf,i to t, s computes Ss,f,i and store Ss,f,i in pf,i • If pf,i arrives earlier than Ss,f,i, it is kept in a buffer until time Ss,f,i, then it is considered “arrived” and may be scheduled for transmission • But all schedulers must have a common clock

  35. Dynamic packet scheduling (2) • Scheduler s computes the early departure of pf,i, denoted εs,f,i, as follows εs,f,i = Ss,f,i + Δs,f,i – Es,f,I • Disadvantages • If the output channel has variable delay, then is not computed accurately • Assume some schedulers have clocks which run fast, and forward packets to a scheduler with a normal clock => This will cause excessive delays to other flows of the normal scheduler

  36. Region aggregation (1) • Taking advantage of the hierarchical structure of internetworks • The gateways are nodes in the network • The circuits between gateways are output channels with variable delay • Gateways have synchronized clocks using the NTP protocol

  37. Region aggregation (2) • The packets of all the flows sharing the same circuit are aggregated together to become a single flow g • The aggregation should be done in a fair manner • A lower per-hop delay is possible for the aggregated flow than for the individual flows

  38. Conclusions • Approach to provide QoS guarantees without per-flow state at each router • Signaling protocol • Maintaining a constant amount of state per router • Accurate and resilient to process and link failures • Packet scheduling technique • A combination of the dynamic packet state and flow aggregation