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ACACIA – Context-aware Edge Computing for Continuous Interactive Applications over Mobile Networks ACACIA Design Overview NSF award: #1305384 #1343713 Motivation Continuous Interactive (CI) mobile apps emerging, e.g., AR, VR, and face recognition Many use cases Retail, stadiums, tourism, museums etc Characteristics of CI apps Highly responsive Compute intensive Junguk Cho, Karthikeyan Sundaresan, Rajesh Mahindra, Sampath Rangarajan and Jacobus Van der Merwe Open Question: How should the three entities (user, network, and application) be jointly orchestrated and combined in a service abstraction to deliver low latencies and enable CI application in mobile network? ACACIA Demo Scenario LTE Connection to Internet Open a CI app (User context) Bind the CI app to ACACIA Device Manager Send user context to MRS from ACACIA Device Manager Create policy rules for the user’s CI app Setup a dedicated bearer in network for the user’s CI App through GW-Cs, MME, eNodeb and LTE modem in mobile device Setup flow rules in local S&PGW-U for the dedicated bearer Running the CI app with a CI server MEC Registration Server (MRS) CI Server PCEF SGW& PGW-C LTE Modem Dedicated Bearer (MEC) Default Bearer (Internet) MEC ACACIA Device Manager EPC CI App UE Open vSwitch (Local S&PGW-U) UL TFT for MEC UL TFT for Internet MME PCRF Open vSwitch (S&PGW-U) eNodeBs Ryu SDN Controller OpenFlow 3GPP Control Plane 3 4 5 6 7 1 2 0 0.5 1 1.5 2 2.5 0 10 20 30 40 50 60 70 80 90 100 Network latency (sec) Background traffic (Mpbs) Conventional EPC EPC with MEC ACACIA MEC Isolation of CI Traffic Control Overhead RTT Reduction Always-on for an extra bearer LTE Radio Promotion Event (Release and re-establish) - One event requires 15 control msgs (SCTP (7), GTPv2 (4), OF(4)) Per day Average Worst # of times 929 7200 Data (MB) 2.58 20 0 0.2 0.4 0.6 0.8 1 13 14 15 16 17 18 CDF RTT (ms) QCI 5 QCI 6 QCI 7 QCI 8 QCI 9 App Optimization Matching time 0 0.5 1 1.5 2 2.5 1 2 4 8 Matching time (sec) The number of clients ACACIA rxPower Naive DB size :105 objects Image resolution : 920x720 Current Solutions Computation offloading to cloud servers No consideration for mobile network complexities Mobile Edge Computing (MEC) over mobile network Need to modify current mobile network infrastructure and establish new specifications Context discovery & user’s localization Significantly help optimize CI application ACACIA - Service abstraction framework - Adapts a holistic end-to-end approach to enabling low latency CI services over existing mobile networks - Leverage client context information through LTE-direct to optimize both network and application processing ACACIA Design (i) User context discovery - LTE-direct : Pub-sub mechanism - Publish “service” availability - Subscribe to “interests” (ii) Context-aware traffic redirection - Request a connectivity between a CI app and closest CI server (on demand) (iii) ACACIA Mobile Edge Network - Use LTE/EPC QoS bearer framework with SDN and NFV GW-Us (standards-compliant MEC) (iv) Context-aware application optimization - ACACIA device manager provides location information to the CI server ACACIA Use Case LTE RTT (~70 ms) Retail Shop AR Server Computer Sec,on Food Sec,on Salesman Salesman “Interest” in laptop Retail App (AR) “Service” Match “Service” Non-Match 1 1 Customer 2 3 4 Send: User context info & screen view Recv: Info relevant to the scene ( e.g., price, reviews) 4 ACACIA Architecture eNodeB ACACIA device manager ACACIA device manager EPC functions SDN/NFV EPC functions Sub/CI App CI Server Mobile device Mobile device Mobile Edge Clouds Core Mobile Network User context discovery Context-aware traffic redirection and NFV-enabled offloading Context-aware application optimization LTE-direct communication Network Control Network Data Location information i ii iii iv Radio Access Network Pub App Solutions proposed and studied in standalone manner

Overviejmanbal/paper/acacia-poster.pdf · 2018. 3. 29. · LTE Connection to Internet ① Open a CI app (User context) ② Bind the CI app to ACACIA Device Manager ③ Send user context

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Page 1: Overviejmanbal/paper/acacia-poster.pdf · 2018. 3. 29. · LTE Connection to Internet ① Open a CI app (User context) ② Bind the CI app to ACACIA Device Manager ③ Send user context

ACACIA – Context-aware Edge Computing for Continuous Interactive Applications over Mobile Networks

ACACIA Design

Overview NSF award: #1305384 #1343713

Motivation •  Continuous Interactive (CI) mobile apps

emerging, e.g., AR, VR, and face recognition

•  Many use cases –  Retail, stadiums, tourism, museums etc

•  Characteristics of CI apps

–  Highly responsive –  Compute intensive

Junguk Cho, Karthikeyan Sundaresan, Rajesh Mahindra, Sampath Rangarajan and Jacobus Van der Merwe

Open Question: How should the three entities (user, network, and application) be jointly orchestrated and combined in a service abstraction to deliver low latencies and enable CI application in mobile network?

ACACIA Demo Scenario LTE Connection to Internet ①  Open a CI app (User context) ②  Bind the CI app to ACACIA Device Manager ③  Send user context to MRS from ACACIA Device Manager ④  Create policy rules for the user’s CI app ⑤  Setup a dedicated bearer in network for the user’s CI App through

GW-Cs, MME, eNodeb and LTE modem in mobile device ⑥  Setup flow rules in local S&PGW-U for the dedicated bearer ⑦  Running the CI app with a CI server

MEC RegistrationServer (MRS)

CI Server PCEF

SGW&PGW-C

LTE Modem

Dedicated Bearer (MEC)

Default Bearer (Internet)

MEC

ACACIA Device

Manager

EPC

CI App

UE

Open vSwitch(Local S&PGW-U)

UL TF

Tfo

r MEC

UL TF

T for

In

terne

t

MME PCRF

Open vSwitch(S&PGW-U)

eNodeBs

Ryu SDN ControllerOpenFlow

3GPP Control Plane

3

4

5

6

71

2

0

0.5

1

1.5

2

2.5

0 10 20 30 40 50 60 70 80 90 100

Netw

ork

late

ncy

(se

c)

Background traffic (Mpbs)

Conventional EPC

EPC with MEC

ACACIA

MEC Isolation of CI Traffic Control Overhead RTT Reduction

Always-on for an extra bearer LTE Radio Promotion Event (Release and re-establish) - One event requires 15 control msgs (SCTP (7), GTPv2 (4), OF(4))

Per day Average Worst # of times 929 7200 Data (MB) 2.58 20

0

0.2

0.4

0.6

0.8

1

13 14 15 16 17 18

CD

F

RTT (ms)

QCI 5QCI 6QCI 7QCI 8QCI 9

App Optimization Matching time

0 0.5

1 1.5

2 2.5

1 2 4 8

Matc

hing t

ime (

sec)

The number of clients

ACACIArxPowerNaive

DB size :105 objects Image resolution : 920x720

Current Solutions •  Computation offloading to cloud servers

–  No consideration for mobile network complexities

•  Mobile Edge Computing (MEC) over mobile network

–  Need to modify current mobile network infrastructure and establish new specifications

•  Context discovery & user’s localization –  Significantly help optimize CI application

ACACIA -  Service abstraction framework -  Adapts a holistic end-to-end approach to

enabling low latency CI services over existing mobile networks

-  Leverage client context information through LTE-direct to optimize both network and application processing

ACACIA Design (i)   User context discovery

-  LTE-direct : Pub-sub mechanism -  Publish “service” availability -  Subscribe to “interests”

(ii)   Context-aware traffic redirection -  Request a connectivity between a CI app and closest CI server (on demand)

(iii)   ACACIA Mobile Edge Network -  Use LTE/EPC QoS bearer framework with

SDN and NFV GW-Us (standards-compliant MEC) (iv)  Context-aware application

optimization -  ACACIA device manager provides

location information to the CI server

ACACIA Use Case

LTE RTT (~70 ms)

Retail Shop

AR Server

Computer)Sec,on)

Food)Sec,on)

Salesman

Salesman

“Interest” in laptop

Retail)App)(AR))

“Service” Match

“Service” Non-Match

1"

1"

Customer

2"3"4"

Send: User context info & screen view Recv: Info relevant to the scene ( e.g., price, reviews)

4"

ACACIA Architecture

eNodeB

ACACIAdevice

manager

ACACIAdevice

manager

EPCfunctions

SDN/NFV EPCfunctions

Sub/CIApp

CI Server

Mobile device

Mobile device

Mobile Edge Clouds

Core Mobile Network

User context discovery

Context-aware traffic redirection andNFV-enabled offloading

Context-aware application optimization

LTE-direct communicationNetwork Control

Network Data

Location information

i

ii

iii

iv

Radio Access Network

Pub App

Solutions proposed and studied in standalone manner