15-744: Computer Networking L-7 QoS QoS IntServ DiffServ Assigned reading [She95] Fundamental Design Issues for the Future Internet Optional [CSZ92] Supporting Real-Time Applications in an Integrated Services Packet Network: Architecture and Mechanisms [CF98] Explicit Allocation of Best-Effort Packet Delivery Service 2
Overview Why QOS? Integrated services Internet video Differentiated services 3 Motivation Internet currently provides one single class of best-effort service No assurances about delivery
Existing applications are elastic Tolerate delays and losses Can adapt to congestion Future real-time applications may be inelastic 4 Inelastic Applications Continuous media applications Lower and upper limit on acceptable performance. BW below which video and audio are not intelligible Internet telephones, teleconferencing with high delay (200 - 300ms) impair human interaction Hard real-time applications Require hard limits on performance
E.g. control applications 5 Why a New Service Model? What is the basic objective of network design? Maximize total bandwidth? Minimize latency? Maximize user satisfaction the total utility given to users What does utility vs. bandwidth look like? Must be non-decreasing function Shape depends on application 6 Utility Curve Shapes
U Elastic BW U U Hard real-time BW Delay-adaptive Stay to the right and you are fine for all curves BW
7 Utility curve Elastic traffic U Elastic Bandwidth Does equal allocation of bandwidth maximize total utility? 8 Admission Control If U(bandwidth) is concave elastic applications U
Incremental utility is decreasing with increasing bandwidth Is always advantageous to have more flows with lower bandwidth Elastic BW No need of admission control; This is why the Internet works! 9 Utility Curves Inelastic traffic U
Delay-adaptive BW U Hard real-time BW Does equal allocation of bandwidth maximize total utility? 10 Admission Control If U is convex inelastic applications
U(number of flows) is no longer monotonically increasing Need admission control to maximize total utility U Delay-adaptive BW Admission control deciding when the addition of new people would result in reduction of utility Basically avoids overload 11
Overview Why QOS? Integrated services Internet video Differentiated services 12 Components of Integrated Services 1. Type of commitment What does the network promise? 2. Packet scheduling
How does the network meet promises? 3. Service interface How does the application describe what it wants? 4. Establishing the guarantee How is the promise communicated to/from the network How is admission of new applications controlled? 13 1. Type of commitment What kind of promises/services should network offer? Depends on the characteristics of the applications that will use the network . 14
Playback Applications Sample signal packetize transmit buffer playback Fits most multimedia applications Performance concern: Jitter variation in end-to-end delay Delay = fixed + variable = (propagation + packetization) + queuing Solution: Playback point delay introduced by buffer to hide network jitter 15 Characteristics of Playback Applications In general lower delay is preferable. Doesnt matter when packet arrives as long
as it is before playback point Network guarantees (e.g. bound on jitter) would make it easier to set playback point Applications can tolerate some loss 16 Applications Variations Rigid & adaptive applications Rigid set fixed playback point Adaptive adapt playback point Gamble that network conditions will be the same as in the past Are prepared to deal with errors in their estimate Will have an earlier playback point than rigid applications Tolerant & intolerant applications
Tolerance to brief interruptions in service 4 combinations 17 Applications Variations Really only two classes of applications 1) Intolerant and rigid 2) Tolerant and adaptive Other combinations make little sense 3) Intolerant and adaptive - Cannot adapt without interruption 4) Tolerant and rigid - Missed opportunity to improve delay
So what service classes should the network offer? 18 Type of Commitments Guaranteed service For intolerant and rigid applications Fixed guarantee, network meets commitment as long as clients send at match traffic agreement Predicted service For tolerant and adaptive applications Two components If conditions do not change, commit to current service If conditions change, take steps to deliver consistent performance (help apps minimize playback delay) Implicit assumption network does not change much over time
Datagram/best effort service 19 Components of Integrated Services 1. Type of commitment What does the network promise? 2. Packet scheduling How does the network meet promises? 3. Service interface How does the application describe what it wants? 4. Establishing the guarantee How is the promise communicated to/from the network How is admission of new applications controlled? 20
Scheduling for Guaranteed Traffic Use token bucket filter to characterize traffic Described by rate r and bucket depth b Use WFQ at the routers Parekhs bound for worst case queuing delay = b/r 21 Token Bucket Filter Tokens enter bucket at rate r Operation: If bucket fills, tokens are discarded
Sending a packet of size P Bucket depth b: capacity of bucket uses P tokens If bucket has P tokens, packet sent at max rate, else must wait for tokens to accumulate 22 Token Bucket Operation Tokens Tokens Tokens
Overflow Packet Enough tokens packet goes through, tokens removed Packet Not enough tokens wait for tokens to accumulate 23 Token Bucket Characteristics On the long run, rate is limited to r On the short run, a burst of size b can be sent Amount of traffic entering at interval T is
bounded by: Traffic = b + r*T Information useful to admission algorithm 24 Token Bucket Specs BW 2 Flow B Flow A: r = 1 MBps, B=1 byte 1 Flow A
1 2 3 Flow B: r = 1 MBps, B=1MB Time 25 Predicted Service Goals: Isolation Isolates well-behaved from misbehaving sources Sharing
Mixing of different sources in a way beneficial to all Mechanisms: WFQ Great isolation but no sharing FIFO Great sharing but no isolation 26 Predicted Service FIFO jitter increases with the number of hops Use opportunity for sharing across hops FIFO+ At each hop: measure average delay for class at that router For each packet: compute difference of average delay
and delay of that packet in queue Add/subtract difference in packet header Packet inserted into queues expected arrival time instead of actual More complex queue management! Slightly decreases mean delay and significantly decreases jitter 27 Unified Scheduling Assume 3 types of traffic: guaranteed, predictive, best-effort Scheduling: use WFQ in routers Each guaranteed flow gets its own queue All predicted service flows and best effort aggregates in single separate queue Predictive traffic classes
Multiple FIFO+ queues Worst case delay for classes separated by order of magnitude When high priority needs extra bandwidth steals it from lower class Best effort traffic acts as lowest priority class 28 Service Interfaces Guaranteed Traffic Host specifies rate to network Why not bucket size b? If delay not good, ask for higher rate Predicted Traffic
Specifies (r, b) token bucket parameters Specifies delay D and loss rate L Network assigns priority class Policing at edges to drop or tag packets Needed to provide isolation why is this not done for guaranteed traffic? WFQ provides this for guaranteed traffic 29 Overview Why QOS?
Integrated services Internet video Differentiated services 30 Internet Video Today Client-server streaming Skype video conferencing Hulu DVD transfer BitTorrent P2P lecture Synchronized video (IPTV) Overlay multicast multicast lecture 31
Client-Server Streaming: Adaptation Quality to Link Long LongTime TimeScale Scale Short ShortTime TimeScale Scale Content Content Negotiation Negotiation Server Server Selection Selection
California New York Adaptive Adaptive Media Media ? 32 Problems Adapting to Network State f1 f1 ?
Internet Server Client TCP hides network state New applications may not use TCP Often do not adapt to congestion Need Needsystem systemthat thathelps helpsapplications applicationslearn learnand and adapt
adaptto tocongestion congestion 33 Congestion Manager Architecture Transmitting Application (TCP, conferencing app, etc) API Congestion Controller Application Protocol Scheduler CM
cm_send(data, length) Request/callback-based send App cm_request( ) send( ) CM IP cmapp_send( ) cm_notify(nsent) 35 Feedback about Network State Monitoring successes and losses Application hints
Probing system Notification API (application hints) Application calls cm_update(nsent, nrecd, congestion indicator, rtt) 37 Overview Why QOS? Integrated services Internet video Differentiated services
38 DiffServ Analogy: Airline service, first class, coach, various restrictions on coach as a function of payment Best-effort expected to make up bulk of traffic, but revenue from first class important to economic base (will pay for more plentiful bandwidth overall) Not motivated by real-time! Motivated by economics and assurances 39 Basic Architecture Agreements/service provided within a domain
Service Level Agreement (SLA) with ISP Edge routers do traffic conditioning Perform per aggregate shaping and policing Mark packets with a small number of bits; each bit encoding represents a class or subclass Core routers Process packets based on packet marking and defined per hop behavior More scalable than IntServ No per flow state or signaling 40 Per-hop Behaviors (PHBs) Define behavior of individual routers rather
than end-to-end services there may be many more services than behaviors Multiple behaviors need more than one bit in the header Six bits from IP TOS field are taken for Diffserv code points (DSCP) 41 Per-hop Behaviors (PHBs) Two PHBs defined so far Expedited forwarding aka premium service (type P) Possible service: providing a virtual wire Admitted based on peak rate Unused premium goes to best effort Assured forwarding (type A) Possible service: strong assurance for traffic within
profile & allow source to exceed profile Based on expected capacity usage profiles Traffic unlikely to be dropped if user maintains profile Out-of-profile traffic marked 42 Expedited Forwarding PHB User sends within profile & network commits to delivery with requested profile Signaling, admission control may get more elaborate in future Rate limiting of EF packets at edges only, using token bucket to shape transmission Simple forwarding: classify packet in one of two queues, use priority EF packets are forwarded with minimal delay
and loss (up to the capacity of the router) 43 Expedited Forwarding Traffic Flow Company A Packets in premium flows have bit set internal router host first hop router Unmarked packet flow Premium packet flow restricted to R bytes/sec
ISP edge router edge router 44 Assured Forwarding PHB User and network agree to some traffic profile Edges mark packets up to allowed rate as in-profile or low drop precedence Other packets are marked with one of 2 higher drop precedence values A congested DS node tries to protect packets with a lower drop precedence value from being lost by
preferably discarding packets with a higher drop precedence value Implemented using RED with In/Out bit 45 Red with In or Out (RIO) Similar to RED, but with two separate probability curves Has two classes, In and Out (of profile) Out class has lower Minthresh, so packets are dropped from this class first Based on queue length of all packets As avg queue length increases, in packets are also dropped Based on queue length of only in packets 46
RIO Drop Probabilities P (drop out) P (drop in) P max_out P max_in min_in max_in avg_in min_out max_out
Conditioner 1 Packet classifier Traffic Conditioner N Best effort Forwarding engine classify packets based on packet header 48 Traffic Conditioning Drop on overflow
Packet input Wait for token Set EF bit Packet output No token Packet input Test if
token token Set AF in bit Packet output 49 Router Output Processing 2 queues: EF packets on higher priority queue Lower priority queue implements RED In or Out scheme (RIO) What DSCP?
EF High-priority Q Packets out AF If in set incr in_cnt Low-priority Q RIO queue management If in set decr in_cnt 50
Edge Router Policing AF in set Arriving packet Is packet marked? Token available? no Clear in bit Forwarding
engine Not marked EF set Token available? no Drop packet 51 Comparison Best-Effort Diffserv
Intserv Service Connectivity No isolation No guarantees Per aggregation isolation Per aggregation guarantee Per flow isolation Per flow guarantee Service Scope
End-to-end Domain End-to-end Complexity No set-up Long term setup Per flow setup Scalability Highly scalable
(nodes maintain only routing state) Scalable (edge Not scalable (each routers maintains router maintains per aggregate state; per flow state) core routers per class state) 52 Possible Token Bucket Uses Shaping, policing, marking Delay pkts from entering net (shaping) Drop pkts that arrive without tokens (policing) Let all pkts pass through, mark ones without
tokens Network drops pkts without tokens in time of congestion 76 Guarantee Proven by Parekh Given: Flow i shaped with token bucket and leaky bucket rate control (depth b and rate r) Network nodes do WFQ Cumulative queuing delay Di suffered by flow i has upper bound Di < b/r, (where r may be much larger than average rate) Assumes that r < link speed at any router All sources limiting themselves to r will result in no
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