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Quality of Service (QoS)

Quality of Service (QoS) 7
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Dr.NeerajMittal,India,Teacher
Published Date:19-07-2017
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Quality of Service (QoS) Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 1Overview  Why better-than-best-effort (QoS-enabled) Internet ?  Quality of Service (QoS) building blocks  End-to-end protocols: RTP, H.323  Network protocols:  Integrated Services(IntServ), RSVP.  Scalable differentiated services: DiffServ  Control plane: QoS routing, traffic engineering, policy management, pricing models Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 2Why Better-than-Best-Effort (QoS)?  To support a wider range of applications Real-time, Multimedia, etc  To develop sustainable economic models and new private networking services Current flat priced models, and best-effort services do not cut it for businesses Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 3Quality of Service: What is it? Multimedia applications: network audio and video QoS network provides application with level of performance needed for application to function. Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 4What is QoS?  “Better performance” as described by a set of parameters or measured by a set of metrics.  Generic parameters: Bandwidth Delay, Delay-jitter Packet loss rate (or loss probability)  Transport/Application-specific parameters: Timeouts Percentage of “important” packets lost Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 5What is QoS (contd) ?  These parameters can be measured at several granularities: “micro” flow, aggregate flow, population.  QoS considered “better” if a) more parameters can be specified b) QoS can be specified at a fine-granularity.  QoS spectrum: Best Effort Leased Line Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 6Fundamental Problems Scheduling Discipline FIFO B B  In a FIFO service discipline, the performance assigned to one flow is convoluted with the arrivals of packets from all other flows  Cant get QoS with a “free-for-all”  Need to use new scheduling disciplines which provide “isolation” of performance from arrival rates of background traffic Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 7Fundamental Problems  Conservation Law (Kleinrock): (i)W (i) = K q  Irrespective of scheduling discipline chosen:  Average backlog (delay) is constant  Average bandwidth is constant  Zero-sum game = need to “set-aside” resources for premium services Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 8QoS Big Picture: Control/Data Planes Control Plane: Signaling + Admission Control or SLA (Contracting) + Provisioning/Traffic Engineering Router Workstation Router Router Workstation Internetwork or WAN Data Plane: Traffic conditioning (shaping, policing, marking etc) + Traffic Classification + Scheduling, Buffer management Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 9QoS Components  QoS = set aside resources for premium services  QoS components: a) Specification of premium services: (service/service level agreement design) b) How much resources to set aside? (admission control/provisioning) c) How to ensure network resource utilization, do load balancing, flexibly manage traffic aggregates and paths ? (QoS routing, traffic engineering) Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 10QoS Components (Continued) d) How to actually set aside these resources in a distributed manner ? (signaling, provisioning, policy) e) How to deliver the service when the traffic actually comes in (claim/police resources)? (traffic shaping, classification, scheduling) f) How to monitor quality, account and price these services? (network mgmt, accounting, billing, pricing) Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 11How to upgrade the Internet for QoS?  Approach: de-couple end-system evolution from network evolution  End-to-end protocols: RTP, H.323 etc to spur the growth of adaptive multimedia applications Assume best-effort or better-than-best-effort clouds  Network protocols: IntServ, DiffServ, RSVP, MPLS, COPS … To support better-than-best-effort capabilities at the network (IP) level Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 12QOS SPECIFICATION, TRAFFIC, SERVICE CHARACTERIZATION, BASIC MECHANISMS Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 13Service Specification  Loss: probability that a flow‟s packet is lost  Delay: time it takes a packet‟s flow to get from source to destination  Delay jitter: maximum difference between the delays experienced by two packets of the flow  Bandwidth: maximum rate at which the soource can send traffic  QoS spectrum: Best Effort Leased Line Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 14Hard Real Time: Guaranteed Services  Service contract Network to client: guarantee a deterministic upper bound on delay for each packet in a session Client to network: the session does not send more than it specifies  Algorithm support Admission control based on worst-case analysis Per flow classification/scheduling at routers Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 15Soft Real Time: Controlled Load Service  Service contract: Network to client: similar performance as an unloaded best-effort network Client to network: the session does not send more than it specifies  Algorithm Support Admission control based on measurement of aggregates Scheduling for aggregate possible Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 16Traffic and Service Characterization  To quantify a service one has two know Flow‟s traffic arrival Service provided by the router, i.e., resources reserved at each router  Examples: Traffic characterization: token bucket Service provided by router: fix rate and fix buffer space  Characterized by a service model (service curve framework) Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 17Token Bucket  Characterized by three parameters (b, r, R) b – token depth r – average arrival rate R – maximum arrival rate (e.g., R link capacity)  A bit is transmitted only when there is an available token When a bit is transmitted exactly one token is consumed r tokens per second bits slope r bR/(R-r) b tokens slope R = R bps time Shivkumar Kalyanaraman Rensselaer Polytechnic Institute regulator 18Characterizing a Source by Token Bucket  Arrival curve – maximum amount of bits transmitted by time t  Use token bucket to bound the arrival curve bps bits Arrival curve time time Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 19Example  Arrival curve – maximum amount of bits transmitted by time t  Use token bucket to bound the arrival curve (b=1,r=1,R=2) Arrival curve bits 4 bps 3 2 2 1 1 0 1 2 3 4 5 1 2 3 4 5 time size of time interval Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 20