A Measurement Based Admission Control Algorithm for Integrated Services Packet Networks ( extended version)

1. A Measurement Based Admission Control Algorithm for Integrated Services Packet Networks ( extended version) S. Jamin, P. Danzig, S. Shenker, L. Zhang

2. Types of Services • Guaranteed service • a absolute bound on delay of every packet is provided • Predictive service • a fair but not absolute bound on delay of every packet is provided

3. Guaranteed service • Provides hard or absolute bound on delay of every packet • Sources are described by either peak or average rates or filter like token bucket • Descriptions provide upper bounds on traffic generated by source • Admission control algorithms use these a priori characterizations to calculate worst case behavior of flows • Network utilization low when flows are bursty • Network utilization acceptable when flows are smooth

4. Predictive Service • Does not provide absolute bound on delay • service commitment is somewhat less reliable • sources characterized by token bucket filters at admission time • behavior of existing flows determined by measurement rather than a priori characterizations • when only few flows present, unpredictability of individual flows causes measurement based approach to be conservative • delivers significant gain in utilization only when there is high degree of statistical multiplexing

5. Objective of paper • Describes a measurement based admission control algorithm for predictive service • To answer the following questions • can reliable delay bounds be provided for measurement based admission control algorithm • does predictive service increase network utilization

6. Measurement Based Admission Control • Set of criteria controlling whether to admit a new flow • based on approximate model of traffic flows • uses measured quantities as inputs • Measurement process to measure the inputs • set of criteria used in this case • delay bound as a result of admitting the new flow • link utilization as a result of admitting the new flow

7. Measurement Based Admission Control • Sources requesting services characterize worst case behavior • to guarantee hard bound on delay • worst case behavior considered • conservative estimate of bound obtained • new flow may not be admitted due to conservative estimate • results in low utilization • to achieve fairly reliable bound for predictive service • approximate maximal delay by replacing worst case parameters with measured quantities • results in higher utilization

8. Worst case delay • Theorem by Parekh says the delay bound for a class j is the one time delay burst that accrues if the aggregate bucket of all classes 1 through j flows are simultaneously dumped into the switch and all classes 1 through j-1 sources continue to send at their reserved rates with j having lowest priority • this worst case delay can change • when flow of same class is admitted • when flow of higher priority class is admitted • when guaranteed flow is admitted • classes classified according to the delay bounds tolerated by that class

9. Computation of new delay bound • The delay bounds as a result of admitting the new flow is computed • for e.g., • When new predictive flow a of same class is admitted • new delay bound = old delay bound + k( bucket size of a) • similarly new delay bounds are calculated for the case • When new predictive flow a of lower class is admitted • When new guaranteed flow a is admitted

10. Equivalent Token bucket filter • In equations replace worst case values by measured values • substitute the reserved rates by the measured rates • substitute the worst case delays by the measured delays • this results in describing the existing aggregate traffic by an equivalent token bucket filter with parameters determined from traffic measurement

11. Admission control algorithm • New predictive flow: if incoming flow a requests predictive service in a particular class • request denied if sum of flow’s requested rate and current usage exceeds link utilization level • request denied if admitting new flow violates delay bound of the same priority level • request denied if admitting new flow violates delay bound of the lower priority level

12. Admission control algorithm • New guaranteed flow: if incoming flow a requests guaranteed service • request denied if total bandwidth of the flows including new flow exceeds link utilization level • request denied if admitting new guaranteed flow violates delay bound of predictive services • this is due to the decrease in the bandwidth available for predictive flows due to admission of a guaranteed flow

13. Measurement mechanism: Time window • Two measurements • experienced delay • utilization • to estimate delays measure the queuing delays d of every packet • to estimate utilization sample the usage rate of the guaranteed service and the predictive class over sampling period of S packet transmission units

14. Measuring delay • Measurement variable to estimate queuing delay is D • Measurement window of T packet transmission units used as basic measurement block • value of D updated on three occasions • at end of measurement block D updated to reflect maximal packet delay seen in previous block • when individual delay measurement exceeds estimated maximum queuing delay D is updated to times the sampled delay • whenever a new flow is admitted D is updated to the value of projected delay from equation

15. Measuring rate • Measurement variable to estimate queuing delay is V • Measurement window of T packet transmission units used as basic measurement block • value of V updated on three occasions • at end of measurement block V updated to reflect maximal sampled utilization seen in previous block • when individual utilization measurement exceeds estimated V, V is updated to the sampled value • whenever a new flow is admitted V is updated

16. Performance Tuning • Parameters , S, T can be varied for better performance • smaller S, more sensitive to bursts , larger S smoother traffic • smaller T means more adaptability to changes in traffic load, larger T results in more stability • larger T results in fewer delay violations and lower link utilization

17. COPS • A simple client/server model for supporting policy control over QoS signaling protocols and provisioned QoS resource management • used to exchange policy information between a policy server (PDP) and its clients (PEP) • for e.g., a policy client maybe RSVP routers that must exercise policy based admission control over RSVP usage

18. COPS • A simple client/server model for supporting policy control over QoS signaling protocols and provisioned QoS resource management • used to exchange policy information between a policy server (PDP) and its clients (PEP) • for e.g., a policy client maybe RSVP routers that must exercise policy based admission control over RSVP usage