Telematics 2. Chapter 3 Quality of Service in the Internet. (Acknowledgement: These slides have been compiled from Kurose & Ross, and other sources)

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1 Telematics 2 Chapter 3 Quality of Service in the Internet (Acknowledgement: These slides have been compiled from Kurose & Ross, and other sources) Telematics 2 (WS 14/15): 03 Internet QoS 1 Improving QOS in IP Networks Thus far: making the best of best effort Future: next generation Internet with QoS guarantees RSVP: signaling for resource reservations Differentiated Services: differential guarantees Integrated Services: firm guarantees Simple model for sharing and congestion studies: Telematics 2 (WS 14/15): 03 Internet QoS 2

2 Principles for QOS Guarantees (1) Example: 1Mbps IP phone, FTP share 1.5 Mbps link. Bursts of FTP can congest router, cause audio loss Want to give priority to audio over FTP Principle 1 Packet marking needed for router to distinguish between different classes; and new router policy to treat packets accordingly Telematics 2 (WS 14/15): 03 Internet QoS 3 Principles for QOS Guarantees (2) What if applications misbehave (audio sends higher than declared rate) Policing: force source adherence to bandwidth allocations Marking and policing at network edge: Similar to ATM UNI (User Network Interface) Principle 2 Provide protection (isolation) for one class from others Telematics 2 (WS 14/15): 03 Internet QoS 4

3 Principles for QOS Guarantees (3) Allocating fixed (non-sharable) bandwidth to flow: inefficient use of bandwidth if flows doesn t use its allocation Principle 3 While providing isolation, it is desirable to use resources as efficiently as possible Telematics 2 (WS 14/15): 03 Internet QoS 5 Principles for QOS Guarantees (4) Basic fact of life: can not support traffic demands beyond link capacity Principle 4 Call Admission: flow declares its needs, network may block call (e.g., busy signal) if it cannot meet needs Telematics 2 (WS 14/15): 03 Internet QoS 6

4 Summary of QoS Principles Let s next look at mechanisms for achieving this. Telematics 2 (WS 14/15): 03 Internet QoS 7 Scheduling And Policing Mechanisms Scheduling: choose next packet to send on link FIFO (first in first out) scheduling: send in order of arrival to queue Real-world example? Discard policy: if packet arrives to full queue: which one to discard? Tail drop: drop arriving packet Priority: drop/remove on priority basis Random: drop/remove randomly Telematics 2 (WS 14/15): 03 Internet QoS 8

5 Scheduling Policies (1) Priority scheduling: transmit highest priority queued packet Multiple classes, with different priorities Class may depend on marking or other header info, e.g. IP source/dest, port numbers, etc.. Real world example? Telematics 2 (WS 14/15): 03 Internet QoS 9 Scheduling Policies (2) Round robin scheduling: Multiple classes Cyclically scan class queues, serving one from each class (if available) Real world example? Telematics 2 (WS 14/15): 03 Internet QoS 10

6 Scheduling Policies (3) Weighted Fair Queuing: Generalized Round Robin Each class gets weighted amount of service in each cycle Real-world example? Telematics 2 (WS 14/15): 03 Internet QoS 11 Policing Mechanisms (2) Goal: limit traffic to not exceed declared parameters Three commonly used criteria: (Long term) Average Rate: how many packets can be sent per unit time (in the long run) Crucial question: what is the interval length: 100 packets per sec or 6000 packets per min have same average! Peak Rate: e.g., 6000 packets per min. (ppm) average 1500 packets per second peak rate (Max.) Burst Size: max. number of pkts sent consecutively (with no intervening idle) Telematics 2 (WS 14/15): 03 Internet QoS 12

7 Policing Mechanisms (2) Token Bucket: limit input to specified Burst Size and Average Rate. Bucket can hold b tokens Tokens generated at rate r token/sec unless bucket full Over interval of length t: number of packets admitted less than or equal to (r t + b). Telematics 2 (WS 14/15): 03 Internet QoS 13 Policing Mechanisms (3) Token bucket, WFQ combine to provide guaranteed upper bound on delay, i.e., QoS guarantee arriving traffic token rate, r bucket size, b WFQ D = b/r max per-flow rate, R Telematics 2 (WS 14/15): 03 Internet QoS 14

8 An Overview/Comparison of Proposed Approaches Name What is it? Usage Guarantees QoS Complexity Int-Serv Reservation framework Y high RSVP Reservation protocol with Int-Serv high Diff-Serv Priority framework N low MPLS Label-Switching (circuitbuilding) Framework In future?? Telematics 2 (WS 14/15): 03 Internet QoS 15 Integrated Services (IntServ) An architecture for providing QOS guarantees in IP networks for individual application sessions Relies on resource reservation, and routers need to maintain state info (like for a virtual circuit), maintaining records of allocated resources and responding to new call setup requests on that basis Question: Can newly arriving flow be admitted with performance guarantees while not violating QoS guarantees made to already admitted flows? Telematics 2 (WS 14/15): 03 Internet QoS 16

9 IntServ: QoS Guarantee Scenario Resource reservation Call setup, signaling (RSVP) Traffic, QoS declaration Per-element admission control request/ reply QoS-sensitive scheduling (e.g., WFQ) Telematics 2 (WS 14/15): 03 Internet QoS 17 Call Admission Arriving session must : Declare its QOS requirement R-spec: defines the QOS being requested Characterize traffic it will send into network T-spec: defines traffic characteristics Signaling protocol: needed to carry R-spec and T-spec to routers (where reservation is required) RSVP (Resource Reservation Protocol) Telematics 2 (WS 14/15): 03 Internet QoS 18

10 IntServ QoS: Service Models (1) Guaranteed service: Worst case traffic arrival: leakybucket-policed source Simple (mathematically provable) bound on delay [Parekh 1992, Cruz 1988] Controlled load service: A quality of service closely approximating the QoS that same flow would receive from an unloaded network element." arriving traffic token rate, r bucket size, b WFQ per-flow rate, R D = b/r max [RFC 2211, RFC 2212] Telematics 2 (WS 14/15): 03 Internet QoS 19 IntServ QoS: Service Models (2) Guaranteed QOS Provides with firm bounds on queuing delay at a router; Envisioned for hard real-time applications that are highly sensitive to endto-end delay expectation and variance Controlled Load Provides a QOS closely approximating that provided by an unloaded router Envisioned for today s IP network real-time applications which perform well in an unloaded network Telematics 2 (WS 14/15): 03 Internet QoS 20

11 Call Admission Call Admission: routers will admit calls based on their R-spec and T- spec and based on the current resource allocated at the routers to other calls. Telematics 2 (WS 14/15): 03 Internet QoS 21 T-Spec Defines traffic characteristics in terms of Leaky bucket model (r = rate, b = bucket size) Peak rate (p = how fast flow might fill bucket) Maximum segment size (M) Minimum segment size (m) Traffic must remain below M + min(pt, rt+b-m) for all possible times T M instantaneous bits permitted (pkt arrival) M + pt: can t receive more than 1 pkt at rate higher than peak rate Should never go beyond leaky bucket capacity of rt+b Telematics 2 (WS 14/15): 03 Internet QoS 22

12 R-Spec Defines minimum requirements desired by flow(s) R: rate at which packets may be fed to a router S: the slack time allowed (time from entry to destination) Modified by router Let (R in, S in ) be values that come in Let (R out, S out ) be values that go out S in S out = max time spent at router If the router allocates buffer size β to flow and processes flow pkts at rate ρ then R out = min(r in, ρ) S out = S in β/ρ Flow accepted only if all of the following conditions hold ρ r (rate bound) β b (bucket bound) S out > 0 (delay bound) Telematics 2 (WS 14/15): 03 Internet QoS 23 Call Admission for Controlled Load A more flexible paradigm does not guarantee against losses, delays only makes them less likely Only T-Spec is used routers do not admit more than they can handle over long timescales short time-scale behavior unprotected (due to lack of R-Spec) In comparison to QoS-Guaranteed Call Admission more flexible admission policy looser guarantees depends on application s ability to adapt handle low loss rates cope with variable delays / jitter Telematics 2 (WS 14/15): 03 Internet QoS 24

13 Scalability: Combining T-Specs Problem: Maintaining state for every flow is very expensive Solution: combine several flows states (i.e., T-Specs) into a single state Must stay conservative (i.e., must meet QoS requirements of the flows) Several models for combining Summing: all flows might be active at the same time Merging: only one of several flows active at a given time (e.g., a teleconference) Telematics 2 (WS 14/15): 03 Internet QoS 25 Combining T-Specs Given two T-Specs (r 1, b 1, p 1, m 1, M 1 ) and (r 2, b 2, p 2, m 2, M 2 ) The summed T-Spec is (r 1 +r 2, b 1 +b 2, p 1 +p 2, min(m 1,m 2 ), max(m 1,M 2 )) The merged T-Spec is (max(r 1,r 2 ), max(b 1,b 2 ), max(p 1,p 2 ), min(m 1,m 2 ), max(m 1,M 2 )) Merging makes better use of resources Less state at router Less buffer and bandwidth reserved But how to police at network edges? And how common? Summing yields a tradeoff Less state at router What to do downstream if flows split directions downstream? Telematics 2 (WS 14/15): 03 Internet QoS 26

14 Resource Reservation Protocol (RSVP) Int-Serv is just the network framework for bandwidth reservations Need a protocol used by routers to pass reservation info around Resource Reservation Protocol Is the protocol used to carry and coordinate setup information (e.g., T- SPEC, R-SPEC) Designed to scale to multicast reservations as well Receiver initiated (easier for multicast) Provides scheduling, but does not help with enforcement Provides support for merging flows to a receiver from multiple sources over a single multicast group Telematics 2 (WS 14/15): 03 Internet QoS 27 RSVP Merge Styles No Filter: any sender can utilize reserved resources E.g., for bandwidth: S 1 S 2 No-Filter Rsv R 1 R 2 S 3 S 4 Telematics 2 (WS 14/15): 03 Internet QoS 28

15 RSVP Merge Styles Fixed-Filter: only specified senders can utilize reserved resources S 1 S 2 Fixed-Filter Rsv: S 1,S 2 R 1 R 2 S 3 S 4 Telematics 2 (WS 14/15): 03 Internet QoS 29 RSVP Merge Styles Dynamic Filter: only specified senders can use resources Can change set of senders specified without having to renegotiate details of reservation S 1 S 2 Dynamic-Filter Change to Rsv S 1,S S1 4,S 2 R 1 R 2 S 3 S 4 Telematics 2 (WS 14/15): 03 Internet QoS 30

16 The Cost of Int-Serv / RSVP Int-Serv / RSVP reserve guaranteed resources for an admitted flow Requires precise specifications of admitted flows If over-specified, resources go unused If under-specified, resources will be insufficient and requirements will not be met Problem: often difficult for apps to precisely specify their requirements May vary with time (leaky-bucket too restrictive) May not know at start of session e.g., interactive session, distributed game Telematics 2 (WS 14/15): 03 Internet QoS 31 Measurement-Based Admission Control (MBAC) Idea: Applications don t need strict bounds on delay, loss can adapt Difficult to precisely estimate resource requirements of some applications Flow provides conservative estimate of resource usage (i.e., upper bound) Router estimates actual traffic load used when deciding whether there is room to admit the new session and meet its QoS requirements Benefit: flows need not provide precisely accurate estimates, upper bounds o.k. Flow can adapt if QoS requirements not exactly met Telematics 2 (WS 14/15): 03 Internet QoS 32

17 MBAC example (1) Traffic is divided into classes, Where class k does not affect class i for k > i Token bucket classification (B i, R i ) Let D k be class k s expected delay Only lower classes affect delay k k-1 D k = Σ B i / (μ - Σ R i ) (this is Little s Law) i=1 i=1 Router takes estimates, d k and r k, of class k s delay and rate Admission decision: Should a new session (β, ρ) be admitted into class k? Telematics 2 (WS 14/15): 03 Internet QoS 33 MBAC example (2) New delay estimate for class j is j-1 d j + β / (μ - Σ r i ) (bucket size increases) i=1 New delay estimate for class k > j is k-1 k-1 k-1 d k (μ - Σ r i ) / (μ - Σ r i - ρ) + β / (μ - Σ r i - ρ) i=1 i=1 i=1 delay shift due to increase in aggregate reserved rate delay shift due to increase in bucket size Telematics 2 (WS 14/15): 03 Internet QoS 34

18 Problems with Int-Serv / Admission Control Lots of signalling Routers must communicate reservation needs Reservation done on a per-session basis How to police? Lots of state to maintain Additional processing load / complexity at routers Signaling and policing load increases with increased # of flows Routers in the core of the network handle traffic for thousands of flows Conclusion: Int-Serv approach does not scale! Telematics 2 (WS 14/15): 03 Internet QoS 35 IETF Differentiated Services (DiffServ) Intended to address the following difficulties with Intserv and RSVP; Scalability: maintaining states by routers in high speed networks is difficult due to the very large number of flows Flexible Service Models: Intserv has only two classes, want to provide more qualitative service classes; want to provide relative service distinction (Platinum, Gold, Silver, ) Simpler signaling: (than RSVP) many applications and users may only want to specify a more qualitative notion of service Telematics 2 (WS 14/15): 03 Internet QoS 36

19 Differentiated Services Approach: Only simple functions in the core, and relatively complex functions at edge routers (or hosts) Do not define service classes, instead provides functional components with which service classes can be built End host End host core routers edge routers Telematics 2 (WS 14/15): 03 Internet QoS 37 DiffServ Architecture Edge router: per-flow traffic management marks packets as in-profile and out-profile scheduling. Core router: per class traffic management buffering and scheduling based on marking at edge preference given to in-profile packets Assured Forwarding b r marking Telematics 2 (WS 14/15): 03 Internet QoS 38

20 Edge-Router Packet Marking Profile: pre-negotiated rate A, bucket size B Packet marking at edge based on per-flow profile Rate A B User packets Possible usage of marking: Class-based marking: packets of different classes marked differently Intra-class marking: conforming portion of flow marked differently than non-conforming one Telematics 2 (WS 14/15): 03 Internet QoS 39 Classification and Conditioning May be desirable to limit traffic injection rate of some class: User declares traffic profile (eg, rate, burst size) Traffic metered, shaped if non-conforming Telematics 2 (WS 14/15): 03 Internet QoS 40

21 Classification and Conditioning Packet is marked in the Type of Service (TOS) in IPv4, and Traffic Class in IPv6 6 bits used for Differentiated Service Code Point (DSCP) and determine PHB that the packet will receive 2 bits are currently unused Telematics 2 (WS 14/15): 03 Internet QoS 41 Edge Functions At DS-capable host or first DS-capable router Classification: edge node marks packets according to classification rules to be specified (manually by admin, or by some TBD protocol) Traffic Conditioning: edge node may delay and then forward or may discard Telematics 2 (WS 14/15): 03 Internet QoS 42

22 DiffServ Reservation Step DiffServ s reservations are done at a much coarser granularity than with IntServ Edge-routers reserve one profile for all sessions to a given destination Renegotiate profile on longer timescale (e.g., days) Sessions negotiate only with edge to fit within the profile Compare with IntServ Each session must negotiate profile with each router on path Negotiations are done at the rate in which sessions start Telematics 2 (WS 14/15): 03 Internet QoS 43 Core Functions Forwarding: according to Per-Hop-Behavior or PHB specified for the particular packet class; Strictly based on class marking Core routers need only maintain state per class BIG ADVANTAGE: No per-session state info to be maintained by core routers! I.e., easy to implement policing in the core (if edge-routers can be trusted) BIG DISADVANTAGE: Can t make rigorous guarantees Telematics 2 (WS 14/15): 03 Internet QoS 44

23 Forwarding (PHB) PHB result in a different observable (measurable) forwarding performance behavior PHB does not specify what mechanisms to use to ensure required PHB performance behavior Examples: Class A gets x% of outgoing link bandwidth over time intervals of a specified length Class A packets leave first before packets from class B PHBs being developed: Expedited Forwarding: Forwarding treatment for one particular diffserv aggregate where the departure rate of the aggregate's packets from any diffserv node must equal or exceed a configurable rate. The EF traffic SHOULD receive this rate independent of the intensity of any other traffic attempting to transit the node Assured Forwarding: 4 classes of traffic where each AF class is in each DS node allocated a certain amount of forwarding resources (buffer space and bandwidth) each AF class with three drop preference partitions Telematics 2 (WS 14/15): 03 Internet QoS 45 Queuing Model of EF Packets from various classes enter same queue Denied service after queue reaches threshold E.g., 3 classes: green (highest priority), yellow (mid), red (lowest priority) yellow rejection-point red rejection-point Telematics 2 (WS 14/15): 03 Internet QoS 46

24 Queuing model of AF Packets into queue based on AF class Each AF class gets a minimum rate E.g., with 3 AF classes Telematics 2 (WS 14/15): 03 Internet QoS 47 Comparison of AF and EF EF Properties: Higher priority class completely unaffected by lower class traffic AF Properties: Traffic of one AF class cannot use buffer of another AF class, even when this class's buffer has room Telematics 2 (WS 14/15): 03 Internet QoS 48

25 Differentiated Services Issues Impact of crossing multiple ASs and routers that are not DS-capable Diff-Serv is stateless in the core, but does not give very strong guarantees Q: Is there a middle ground (stateless with stronger guarantees) Telematics 2 (WS 14/15): 03 Internet QoS 49 Dynamic Packet State (DPS) Goal: provide Int-Serv-like guarantees with Diff-Serv-like state E.g., fair queueing, delay bounds Routers in the core should not have to keep track of individual flows Approach: Edge routers place state in packet header Core routers make decisions based on state in header Core routers modify state in header to reflect new state of the packet Telematics 2 (WS 14/15): 03 Internet QoS 50

26 DPS Example: fair queuing Fair queuing: if not all flows fit into a pipe, all flows should be bounded by same upper bound, b b should be chosen so that pipe is filled to capacity S 1 r 1 > b S 2 S 3 r 2 > b r 3 < b b b r 3 Telematics 2 (WS 14/15): 03 Internet QoS 51 DPS: Fair Queuing The header of each packet in flow f i indicates the rate, r i of its flow into the pipe r i is put in the packet header The pipe estimates the upper bound, b, that flows should get in the pipe If r i < b, packet passes through unchanged If r i > b: packet is dropped with probability 1 - b / r i r i replaced in packet with b (flow s rate out of pipe) Router continually tries to accurately estimate b buffer overflows: decrease b aggregate rate out less than link capacity: increase b Telematics 2 (WS 14/15): 03 Internet QoS 52

27 Summary Int-Serv: Strong QoS model: reservations Heavy state High complexity reservation process Diff-Serv: Weak QoS model: classification No per-flow state in core Low complexity DPS: Middle ground Requires routers to do per-packet calculations and modify headers What can / should be guaranteed via DPS? No approach seems satisfactory Telematics 2 (WS 14/15): 03 Internet QoS 53 Current State of Discussion IntServ Lost Too much state and signaling made it impractical unable to accurately quantify apps needs in a convenient manner DiffServ is losing Not clear what kind of service a flow gets if it buys into premium class What / how many / when should flows be allowed into premium unclear What happens to flows that don t make it into premium The current winner: over-provisioning Bandwidth is cheap these days ISPs provide enough bandwidth to satisfy needs of all apps Telematics 2 (WS 14/15): 03 Internet QoS 54

28 Reflection: Is over-provisioning the answer? Q: are you happy with your Internet service today? Problem: the peering points between ISPs Some traffic must travel between ISPs Traffic crosses peering points ISPs have no incentive to make other ISPs look good, so they do not overprovision at the peering point Solutions: ISPs duplicate content and buffer within their domain What to do about live / dynamically changing content? Will there always be enough bandwidth out there? What is the next killer app? Q: Are there other alternatives outside of the IP model? Telematics 2 (WS 14/15): 03 Internet QoS 55

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