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Scheduling Heterogeneous Real- Time Traffic over Fading Wireless Channels I-Hong Hou P.R. Kumar University of Illinois, Urbana-Champaign 1/24
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Background: Wireless Networks There will be increasing use of wireless networks for serving traffic with QoS constraints: Example: VoIP, Video Streaming, Real-time Monitoring, Networked Control, etc. Client requirements include Specified traffic patterns Delay bounds Timely throughput bounds 2 /24
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Previous Work and Challenges Prior work [Hou et al] [Hou and Kumar]: Clients have hard throughput requirements Static but unreliable wireless channels All clients require the same delay bounds Optimal packet scheduling policies are proposed Q: How to deal with more complicated scenarios? Rate adaptation may be applied Channel qualities can be time-varying Clients may require different delay bounds This work extends the model in prior work and proposes a guideline for these scenarios 3 /24
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Client-Server Model A system with N wireless clients and one AP Time is slotted AP schedules all transmissions AP 1 2 3 4 /24
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More General Traffic Model Group time slots into periods with T time slots Clients may generate packets at the beginning of each period AP 1 2 3 {1,.,3} {.,2,.}{1,2,3} {1,.,3} {.,2,.} {1,2,3} T 5 /24
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Different Delay Bounds Deadline for client n = τ n AP 1 2 3 τ 1 =4 arrival deadline τ 3 =3 deadlinearrival τ 2 =5 deadlinearrival 6 /24
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Without Rate Adaptation Transmission takes 1 time slot Transmissions succeeds with probability p c,n Channel Model Channel changes from period to period Channels are static within a period System may or may not support rate adaptation 7 /24 With Rate Adaptation Transmission takes s c,n time slots under channel c Transmissions are error-free
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Timely Throughput Requirements Timely throughput = Client n requires timely throughput q n Q: How to design a scheduling policy to fulfill requirements of all feasible sets of clients? Feasibility optimal scheduling policy 8 /24
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Pseudo-debt Delivery debt: deficiency of timely throughput Time debt: deficiency of time spent on a client Pseudo-debt r n (t) quantifies the behavior of client n up to time t The set of clients is fulfilled converges to 0 in probability 9 /24
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Sufficient Condition for Optimality Let μ n be the reduction on debt for client n Theorem: A policy that maximizes for each period is feasibility optimal. Analogous to Max-Weight scheduling in wireline networks 10 /24
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Rate Adaptation with Different Delay Bounds Scenario: Rate adaptation used Clients may have different per packet delay bounds, τ n Modified Knapsack Policy: Find an ordered set S={m 1,m 2, … } to maximize total debt A variation of knapsack problem and can be solved by DP 11 /24 τ 1 =4τ 2 =7τ 3 =10 S 1 = 3 S 2 = 5 S 3 = 4 S 1 = 3S 3 = 4
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Rate Adaptation with Different Delay Bounds Scenario: Rate adaptation used Clients may have different per packet delay bounds, τ n Modified Knapsack Policy: Find an ordered set S={m 1,m 2, … } to maximize total debt A variation of knapsack problem and can be solved by DP 12 /24 S 3 = 4S 2 = 5 τ 1 =4τ 2 =7τ 3 =10 S 1 = 3 S 2 = 5 S 3 = 4
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Rate Adaptation with Different Delay Bounds Scenario: Rate adaptation used Clients may have different per packet delay bounds, τ n Modified Knapsack Policy: Find an ordered set S={m 1,m 2, … } to maximize total debt A variation of knapsack problem and can be solved by DP 13 /24 S 2 = 5S 1 = 3 τ 1 =4τ 2 =7τ 3 =10 S 1 = 3 S 2 = 5 S 3 = 4
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Time-Varying Channels Scenario: Same delay bounds for all clients, τ≡τ n Time-varying channels, p n (t) Applicable to Gilbert-Elliot fading Model Joint Debt-Channel Policy: Let r n (t) be delivery debt Clients with larger r n (t) p n (t) get higher priorities Theorem: The Joint Debt-Channel policy is feasibility optimal 14 /24
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Heterogeneous Delay Bounds Scenario: Static channels, p n ≡p n (t) Different delay bounds for all clients, τ n Adaptive-Allocation Policy: Let r n (t) be time debt Estimate the # of slots needed by client n for a successful transmission, η n Dynamically allocate slots to maximize 15 /24
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Evaluation Methodology Evaluate four policies: Proposed policies for each scenario PCF with randomly assigned priorities (random) Two policies proposed by [Hou, Borkar, and Kumar] Time debt first policy Weighted-delivery debt first policy Metric: Total delivery debt 16 /24
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Rate Adaptation: VoIP Setup Period length = 20 ms Two groups of clients: 66 Group A clients and 44 Group B clients Group AGroup B One packet every 60 msOne packet every 40 ms 21.3 kb/s traffic32 kb/s traffic require 19.2 kb/s timely throughput require 22.4 kb/s timely throughput Starting times evenly spaced Data rates alternate between 11 Mb/s and 5.5 Mb/s 17 /24
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Rate Adaptation: VoIP Results 18 /24
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Time-Varying Channels: VoIP Setup Period length = 20 ms Two groups of clients: 57 Group A clients and 38 Group B clients Group AGroup B One packet every 60 msOne packet every 40 ms 21.3 kb/s traffic32 kb/s traffic require 19.2 kb/s timely throughput require 22.4 kb/s timely throughput Starting times evenly spaced Channel evolves based on Gilbert-Elliot model 19 /24
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Time-Varying Channels: VoIP Result 20 /24
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Heterogeneous Delay Bounds: VoIP Setup Two groups of clients: 57 Group A clients and 38 Group B clients Group AGroup B One packet every 60 msOne packet every 40 ms 21.3 kb/s traffic32 kb/s traffic require 19.2 kb/s timely throughput require 22.4 kb/s timely throughput Delay bound = 20 msDelay bound = 13 ms Starting times evenly spaced Average channel reliabilities between 80% and 96% 21 /24
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Heterogeneous Delay Bounds: VoIP Result 22 /24
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Conclusion Extend previous model for more complicated scenarios With or without rate adaptation Time-varying channels Heterogeneous delay bounds Identify a sufficient condition for optimal scheduling policies Design policies for several cases Time-varying channels, heterogeneous delay bounds with rate adaptation Time-varying channels without rate adaptation Heterogeneous delay bounds without rate adaptation 23 /24
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Rate Adaptation: MPEG Setup Period length = 6 ms Two groups of clients: 6 Group A clients and 6 Group B clients Group AGroup B 1700 kb/s traffic1360 kb/s traffic require 1530 kb/s timely throughput require 816 kb/s timely throughput Data rates alternate between 54 Mb/s and 24 Mb/s 25
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Rate Adaptation: MPEG Results 26
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Time-Varying Channels: MPEG Setup Period length = 6 ms Two groups of clients: 4 Group A clients and 4 Group B clients Group AGroup B 1700 kb/s traffic1360 kb/s traffic require 1530 kb/s timely throughput require 816 kb/s timely throughput Average channel reliabilities between 80% and 89% 27
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Time-Varying Channels: MPEG Setup 28
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