/
RT-OPEX: Flexible Scheduling for Cloud-RAN Processing RT-OPEX: Flexible Scheduling for Cloud-RAN Processing

RT-OPEX: Flexible Scheduling for Cloud-RAN Processing - PowerPoint Presentation

debby-jeon
debby-jeon . @debby-jeon
Follow
412 views
Uploaded On 2017-06-05

RT-OPEX: Flexible Scheduling for Cloud-RAN Processing - PPT Presentation

Krishna C Garikipati Kassem Fawaz Kang G Shin University Of Michigan 1 fronthaulnetwork What is CloudRAN Virtualization in Radio Access Network RAN Benefits Lower energy consumption compute HVAC ID: 555952

opex core scheduling processing core opex processing scheduling rtt gaps deadline time fft performance load ran latency real migrate

Share:

Link:

Embed:

Download Presentation from below link

Download Presentation The PPT/PDF document "RT-OPEX: Flexible Scheduling for Cloud-R..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.


Presentation Transcript

Slide1

RT-OPEX: Flexible Scheduling for Cloud-RAN Processing

Krishna C. Garikipati, Kassem Fawaz, Kang G. ShinUniversity Of Michigan

1Slide2

fronthaulnetwork

What is Cloud-RAN*?

Virtualization in Radio Access Network (RAN)

Benefits

Lower energy consumption (compute, HVAC)

Less site visitsfaster upgrade and replacement cyclesAdvanced signal processing

* C-RAN

2Slide3

C-RAN in Practice

3Slide4

Deadlines

Periodic (sub)frames every 1 msHard deadline of 3msTransport, decode and respond to LTE uplink frameRequires real-time scheduling

ACK

ACK

ACK

4

fronthaulnetworkSlide5

C-RAN Scheduling

5

Core network

Assign

basestations

to computing nodes

scheduler

Assign

subframes

to cores

BS 0 –

subframe

0

BS 1 –

subframe

0

BS 0 –

subframe

1

BS 1 –

subframe

1

Per-node scheduler

.

.

.

core 0

core 1

core 2

core

N

BS 0

BS 1

BS 0

BS 1Slide6

6

State-of-the-Art

Scheduling

ArchitectureSlide7

7

Two scheduling options:

Design for WCET

overprovision resources

Design for average case

 deadline misses

Real-world Traffic

Band 17

Band 13

Max loadSlide8

RT-OPEX

Offers flexible scheduling for C-RANCombines offline partitioned scheduling with runtime parallelism (work stealing)

Achieves

resource pooling at finer time scale

Avoids

over-provisioning of resources8Slide9

9Slide10

End to End Model

10Slide11

Uplink Processing

ModelLTE processing in software

N

= # antennas

K

= modulation orderD = bits per carrier (load)L = decoding iterationsDominating termsFFT, Equalization, Turbo decodingError term

Platform variations

(kernel tasks/interrupt handling)

Comparable to benchmark stress test

11

GPP (

)

31.4

169.1

49.7

93.0

0.992

31.4

169.1

49.7

93.0

0.992

FFT, Equalization

De-mapping, De-matching

Turbo-decoding

Error Slide12

Parallelism

Decoder Block

Independent w.r.t code blocks

FFT

Independent w.r.t antenna and OFDM symbols

12Slide13

Parallelism

Task ModelDivide tasks into parallel and independent subtasks

13

Parallel processing

Precedence constraintsSlide14

End-to-End Model

Assuming Tx processing starts 1ms before deadline

 

14

RTT/2

RTT/2

RTT/2

 

Tx

processing startsSlide15

Scheduling

15Slide16

Conventional Approaches

StaticDeterministic, offline

Offers real-time guarantees

Deadline miss:

 

GlobalSingle-queue of subframesFIFO (or EDF) de-queuingNon-deterministic, flexibleNo real-time guarantees16Slide17

Scheduling Gaps

WCET design + non-optimal design  gaps in execution

17Slide18

RT-OPEX

Exploit the gaps dynamically at runtime18

core is idle

core is idleSlide19

Local FFT

decode

RT-OPEX Migration

Subtasks migrated to cores with enough slack time

Local processing does not wait for migrated task

Ensures no performance degradation

Otherwise perform recovery

19

Core 0

Core 4

Core 1

Core 3

Core 2

Start migration

Local FFTSlide20

Implementation

& evaluation20Slide21

RT-OPEX Implementation

OpenAirInterface (LTE Rel 10)Modularize the tasksAbstraction of FFT, Demod

, Decode

Utilize

pthread

libraryMigration Data references from shared memoryOpen-sourceEnables different configurationshttps://github.com/gkchai/RT-OPEX21Slide22

Evaluation Platform

GPP32-core Intel Xeon E5, 128 GB RAM, 15 MB L3 cacheUbuntu 14.0.4 low latency kernelLTE data collectionUSRP to collect load of 4 cellular towers30000

subframes

Replay load from each BS trace

4 BS, 2 Antennas, 10MHz LTE FDD1 UE per BS, 100% PRB utilizationSimulated transport delay (RTT/2)22Slide23

Performance Evaluation

Performance Comparison23

Large gaps

Narrower gapsSlide24

Migration Overhead

FFT median overhead is 26

 

Decoding

overhead is 20

 24

Overhead = cost of transfer OAI variables from shared memory to core

Account for overhead at migrationSlide25

Partitioned Scheduler

25

RTT/2 > 400

 Budget<1.6

ms  subframes with MCS > 20 miss deadlinesPartitioned scheduler cannot exploit gaps  Slide26

Global Scheduler

Fails to deliver performance gains26

Cache thrashing causes deadline performance to saturate beyond 8 cores

At MCS 27, processing time increases with more coresSlide27

Conclusion

RT-OPEX: Real-Time Opportunistic ExecutionLow overheadMigration on top of partitionedFlexible to resources

Exploits added resources for migration

Flexible to load

Leverages load variations to improve deadline miss rate

27Slide28

Thank You!

Questions?28Slide29

RT-OPEX Performance

Lower RTT  larger gaps

Larger RTT

 narrower gaps

29

migrate decode tasks of high MCS  deadline miss goes to zeromigrate only FFT subtasks  deadline miss reducedSlide30

Transport Latency

Latency between and RadioFronthaul (

):

Fixed latency (~20us/Km)

Cloud network latency (

):Switch, Ethernet and driver delay 30Latency per packetAverage 0.15ms1Gbps Ethernet to switch1/10

Gbps Ethernet to GPPSlide31

Uplink Processing

Dynamic and depends on:MCS selection

Number of antennas

SNR of channel

31

2.8x increase w.r.t MCS0.5ms increase w.r.t L50% increase w.r.t SNR

 

per antenna

 Slide32

RT-OPEX Performance

At miss rate threshold ≤ 0.01, RT-OPEX supports 4 Mbps of extra load

32

RTT/2 = 500

 Slide33

RT-OPEX

Challenges33

When to migrate?

What to migrate?

How to migrate?Slide34

RT-OPEX

34