Scheduling CS 215 W 2001- Keshav Chpt 9 Problem: given N packet streams contending for the same channel, how to schedule pkt transmissions?

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Presentation transcript:

Scheduling CS 215 W Keshav Chpt 9 Problem: given N packet streams contending for the same channel, how to schedule pkt transmissions?

Why and where scheduling?

Scheduling Requirements Easy to implement Fair (for best effort sources) Protected against abusive sources (for best effort) Peformance bounds (for guaranteed service) Admission control (for guaranteed service)

Control Parameters/Measures Controls Perf. Measures priority ranking avg delay/resource share polling frequency bandwidth buffer allocation/drop loss rate polling frq/buffer alloc fairness

Performance Bounds Deterministic bounds: satisfied by ALL packets Statistic bounds:satisfied by fraction R of packets (a) Bandwidth: important for real time applications (b) Delay: avg., worst case, 99% (important for interactive) (c ) Delay jitter: important for interactive appl. (reconstruction buffer for playback) (d) Loss

Max-Min Fairness The min of the flows should be as large as possible Max-Min fairness for single resource: Bottlenecked (unsatisfied) connections share the residual bandwidth equally Their share is > = the share held by the connections not constrained by this bottleneck C=10 F1 = 25 F2 = 6 F1’= 5 F2”= 5

Max-Min Fairness (cont) Extension to multiple resource sharing Iterative construction approach (given the routing): at each iteration increase the flow of non saturated connections by Df C=2 C= 8 F1=8 F2=8 F3=8 F4=8 F1=? F4= ? C=4

More Scheduling Issues (Keshav) Work conserving vs not work conserving schedule (the issue arises only for jitter control) Per flow vs per class (a la DiffServ) queueing: “per flow” does not scale, has bad reputation.. Per-flow service tag implementation using two Heaps (for smallest tag and largest tag) Schedulable region (in space C1xC2): set of pairs of connections C1 and C2 that can be supported simultaneously, meeting the respective QoS

Schedule review (1): Best Effort Traffic FIFO: in order of arrival to the queue; packets that arrive to a full buffer are either discarded, or a discard policy is used to determine which packet to discard among the arrival and those already queued

Scheduling Best Effort Traffic (cont) Priority Queuing: classes have different priorities; class may depend on explicit marking or other header info, eg IP source or destination, TCP Port numbers, etc. Transmit a packet from the highest priority class with a non-empty queue Preemptive and non-preemptive versions

Scheduling (Cont.) Round Robin: scan class queues serving one from each class that has a non-empty queue Weighted Round Robin: is a generalized Round Robin in which an attempt is made to provide a class with a differentiated amount of service over a given period of time

Scheduling Best Effort Traffic (cont) Deficit RR: achieves same effect as WRR, but does not require avg pkt size knowledge a quantum size, say Q is defined a Deficit Counter DC is initialized to Q queues are served RR; if queue empty, DC <- Q if HOL packet is P < DC, it is served; DC <- DC + Q-P else, DC <- DC + Q

Scheduling Best Effort Traffic (cont Weighted Fair Queueing: compute the packet finishing time (ie,the time when the packet would be served by Generalized Proc Sharing) rank packets according to finishing times the resulting sequence number (finishing number) is the packet’s turn to be transmitted.

Scheduling real time traffic Weighted Fair Queueing: a nice delay bound applies Virtual Clock Earliest Due Date (or Earliest Deadline First)