Admission Control and Scheduling for QoS Guarantees for Variable-Bit-Rate Applications on Wireless Channels I-Hong Hou P.R. Kumar University of Illinois, Urbana-Champaign

Background: Wireless Networks  There will be increasing use of wireless networks for serving traffic with QoS constraints: VoIP Video Streaming Real-time Monitoring Networked Control 1/30

Challenges  Wireless Network limitation Non-homogeneous, unreliable wireless links  Client QoS requirements Specified traffic pattern Delay bound Delivery ratio bound Throughput bound  System perspective Fulfill clients with different QoS requirements 2/30

Goal of the Paper  Prior work [Hou, Borkar, and Kumar]: All clients generate traffic with the same rate Admission control and packet scheduling policies  Q: How to deal with more complicated traffic patterns? Applications with variable-bit-rate (VBR) traffic  MPEG streaming Clients generate traffic with different rates  This work extends results to arbitrary traffic patterns 3/30

Client-Server Model  A system with N wireless clients and one AP  Time is slotted  One packet transmission in each slot  AP schedules all transmissions 4/30 AP 1 2 slot length = transmission duration 3

Channel Model  Unreliable, non-homogeneous wireless channels successful with probability p n failed with probability 1-p n p 1,p 2, …,p N may be different 5/30 AP 1 2 p1p1 p2p2 3 p3p3

Uplink Protocol  Poll (ex. CF-POLL in PCF)  Data  No need for ACK  p n = Prob( both Poll/Data are delivered) 6/30 AP 1 2 p1p1 p2p2 POLL Data 3 p3p3

Downlink Protocol  Data  ACK  p n = Prob( both Data/ACK are delivered) 7/30 AP 1 2 p1p1 p2p2 Data ACK 3 p3p3

Traffic Model  Group time slots into intervals with τ time slots  Clients may generate packets at the beginning of each interval 8/30 AP p1p1 p2p2 p3p3 τ {1,.,3} {.,2,.} {1,2,3}

Delay Bound  Deadline = Interval  Packets are dropped if not delivered by the deadline  Delay of successful delivered packet is at most τ 9/30 AP p1p1 p2p2 p3p3 {1,.,3} {.,2,.} {1,2,3} τ arrival deadline

SI Packet Scheduling 10/30 AP p1p1 p2p2 p3p3 SF F I forced idleness {1,.,3} {.,2,.} {1,2,3} dropped

SI Timely Throughput  Timely throughput = avg. # of delivered packets per interval 11/30 AP p1p1 p2p2 p3p3 SF F I Client #Throughput {1,.,3} {.,2,.} {1,2,3}

SI Packet Arrivals  Distribution of packet arrivals is specified 12/30 AP p1p1 p2p2 p3p3 SF F I {1,.,3} {.,2,.} {1,2,3} ArrivalProportion of Occurrences {1,3}1/3 {2}1/3 {1,2,3}1/3

SI QoS Requirements  Client n requires timely throughput q n  Delivery ratio requirement of client n = q n /{arrival prob. of client n} 13/30 AP p1p1 p2p2 p3p3 SF F I {1,.,3} {.,2,.} {1,2,3} Client #Delivery ratio

Problem Formulation  Admission control Given τ, packet arrivals, p n, q n, decide whether a set of clients is feasible  Scheduling policy Design a policy that fulfills every feasible set of clients 14/30

 The proportion of time slots needed for client n is Work Load 15/30

 The proportion of time slots needed for client n is Work Load 15/ 30 expected number of time slots needed for a successful transmission

 The proportion of time slots needed for client n is Work Load 15/ 30 number of required successful transmissions in an interval

 The proportion of time slots needed for client n is Work Load 15/ 30 normalize by interval length

 The proportion of time slots needed for client n is  We call w n the “ work load ” Work Load 15/ 30

SI Necessary Condition for Feasibility  Necessary condition from classical queuing theory:  But the condition is not sufficient  Packet drops by deadline misses cause more idleness than in queuing theory 16/ 30 AP p1p1 p2p2 p3p3 SF F I {1,.,3} {.,2,.} {1,2,3}

Stronger Necessary Condition  Let I S = Expected proportion of the idle time when the server only works on S I S decreases as S increases  Theorem: the condition is both necessary and sufficient  Admission control checks the condition 17/ 30

Largest Debt First Scheduling Policies  Give higher priority to client with higher “ debt ” 18/ 30 AP p1p1 p2p2 p3p3 {1,2,3} FFS FS F

Two Definitions of Debt  The time debt of client n time debt = w n – actual proportion of transmission time given to client n  The weighted delivery debt of client n weighted delivery debt = (q n – actual timely throughput)/p n  Theorem: Both largest debt first policies fulfill every feasible set of clients Feasibility Optimal Policies 19/ 30

Evaluation Methodology  Evaluate five policies: DCF Enhanced DCF (EDCF) by e PCF with randomly assigned priorities (random) Time debt first policy Weighted-delivery debt first policy  Metric: Shortfall in Timely Throughput 20/ 30

Evaluated Applications  VoIP Generate packets periodically Duplex traffic Clients may generate packets by different period  MPEG Generate packets probabilistically Only downstream traffic Clients may generate packets by different probability 21/ 30

VoIP Traffic  ITU-T G Bit rates between 8 kb/s to 32 kb/s Different bit rates correspond to different periods 8kb/s – 32 kb/s bit rates 20 ms interval length 160 Byte packet11 Mb/s transmission rate 610 μs time slot32 time slots in an interval 22/ 30

VoIP Clients  Two groups of clients:  Feasible set: 6 group A clients, 5 group B clients  Infeasible set: 6 group A clients, 6 group B clients Group AGroup B 60 ms (3 intervals) period40 ms (2 intervals) period 21.3 kb/s traffic32 kb/s traffic require 99% delivery ratiorequire 80% delivery ratio Starting times evenly spaced Channel reliabilities range from 61% to 67% 23/ 30

VoIP Results: A Feasible Set 24/ 30

VoIP Results: A Feasible Set fulfilled 24/ 30

VoIP Results: A Feasible Set 24/ 30

VoIP Results: A Feasible Set 24/ 30

VoIP Results: A Feasible Set 24/ 30

VoIP Results: An Infeasible Set 25/ 30

VoIP Results: An Infeasible Set small shortfall 25/ 30

VoIP Results: An Infeasible Set 25/ 30

VoIP Results: An Infeasible Set 25/ 30

VoIP Results: An Infeasible Set 25/ 30

MPEG Traffic  Model MPEG VBR traffic by a Markov chain consisting of three activity states (Martin et al)  MAC: a 6 ms interval length1500 Bytes packet 54 Mb/s transmission rate9 time slots in an interval ActivityGreatHighRegular Arrival probability / 30

MPEG Clients  Two groups of clients Group A generates traffic according to Martin et al and requires 90% delivery ratio Group B generates traffic half as often as A and requires 80% delivery ratio The n th client in each group has (60+n)% channel reliability  Feasible set: 4 group A clients, 4 group B clients  Infeasible set: 5 group A clients, 4 group B clients 27/ 30

MPEG Results: A Feasible Set 28/ 30

MPEG Results: A Feasible Set fulfilled 28/ 30

MPEG Results: A Feasible Set 28/ 30

MPEG Results: A Feasible Set 28/ 30

MPEG Results: A Feasible Set 28/ 30

MPEG Results: An Infeasible Set 29/ 30

MPEG Results: An Infeasible Set small shortfall 29/ 30

MPEG Results: An Infeasible Set 29/ 30

MPEG Results: An Infeasible Set 29/ 30

MPEG Results: An Infeasible Set 29/ 30

Conclusion  Extend a framework for QoS to deal with traffic patterns, deadlines, throughputs, delivery ratios, and channel unreliabilities  Characterize when QoS is feasible  Provide efficient scheduling policies  Address implementation issues 30/ 30

Backup Slides  An example: Two clients, τ = 3 p 1 =p 2 =0.5 q 1 =0.876, q 2 =0.45 w 1 =1.76/3, w 2 =0.3 I {1} =I {2} =1.25/3, I {1,2} =0.25/3  w 1 +I {1} =3.01/3 > 1  However, w 1 +w 2 +I {1,2} =2.91/3 < 1