the sahara four-layer model; case-studies in composition bhaskaran raman, jimmy shih, randy h. katz,...

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The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

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Page 1: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

The SAHARA Four-Layer Model;Case-studies in Composition

Bhaskaran Raman, Jimmy Shih, Randy H. Katz,

SAHARA, EECS, U.C.Berkeley

Page 2: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Layered Reference Model for Service Composition

IP Network

Enhanced Links

Enhanced Paths

End-to-End NetworkWith Desirable Properties

Middleware Services

Applications Services

End-User Applications

Connect

ivit

yPla

ne

Applic

ati

on

Pla

ne

Serv

ice

Com

posi

tion

Page 3: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Work in Progress

• Enhanced Links– Congestion Pricing for Access Links– Auction-based Resource (Bandwidth) Allocation– Traffic Policing/Verification of Bandwidth Allocation

Page 4: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Congestion Pricing at Access Links

• Setup– 10 users– 3 QoS (Slow-going, Moderate, & Responsive)

differ on degree of traffic smoothing– 24 tokens/day, 15 minutes of usage per charge

• Acceptable– Users make purchasing decision at most once every 15 minutes

• Feasible– Changing prices cause users to select different QoS

• Effective– If entice half of users to choose lower QoS during congestion,

then reduce burstiness at access links by 25%

Internet

Local Area

Network

Computer Acces

s Route

rQoSCompute

r$

Page 5: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Auction-based Resource Allocation

• Capabilities– Bidders can place bids based on application requirements and

contention level.– Bidders can place bids for near future resource requirements based on

recent history.– Bidders can express both utility and priority to auctioneer.– Auctioneer can dynamically change application’s priority by changing

the token allocation rate.• Status

– On-going work– First application: bandwidth allocation in ad hoc wireless networks

• Problem– Efficiently and effectively allocate

resources according to application’s dynamic requirements

• Approach– Leveraging auction schemes and

work-load predictionsResource

AuctioneerBidder

Application

Page 6: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Mobile Virtual Network Operator:Composition and Cooperation

one2one

one2one

1-to-1 Relationship

InterCall

M-to-N Relationships

Competition

Page 7: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Bandwidth Allocation

• Problem: scalable (stateless) and robust bandwidth allocation

• Control Plane: – Soft state– Per-router per-period

certificates for robustness without per-flow state

– Random sampling to prevent duplicate refreshes

• Data Plane: – Monitor aggregate flows – Recursively split

misbehaving aggregates

misbehavingaggregate – split it

R1 attaches new certificateto the refresh message

Page 8: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Work in Progress

• Enhanced Paths– BGP Route Flap Dampening– BGP Policy Agents– Backup Path Allocation in Overlay Networks– Host Mobility– Multicast Interoperation

Page 9: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

BGP: Stability vs. Convergence• Problem:

– Stability achieved through flap damping[RFC2439]– Unexpected:flap damping delays convergence!

Solution: selective flap damping [sigcomm02]

Duplicate suppression: Ignore flaps caused by transient convergence instability Still contains stability

Eliminates undesired interaction!

Topology: clique of routers

Page 10: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

8898 AS’s

971 AS’s

897 AS’s

129 AS’s

20 AS’s

Policy Management for BGP

• 3-15 minute failover time• Slow response to congestion• Unacceptable for Internet service

composition

• Lack of distributed route control• Need distributed policy management• Explicit route policy negotiation

• Identified current routing behavior• Inferred AS relationships, topology• Next : gather traffic data, finish code, emulate

Page 11: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Backup Path Allocation in Overlay Networks

• Challenge– Disjoint primary and backup path in the overlay network may share underlying

links because the overlay network cannot control underlying links used by a path

• Problem– Find a primary and backup path pair with minimal failure probability based on

correlated overlay link failures• Approach

– Decouple backup path routing from primary path routing– Route backup paths based on failure probability cost which measures the

incremental path failure probability caused by using a link in the path• Main Result

– Can be 20-30% more robust compared to shortest disjoint path allocation• Status

– Finished work, submitted to ICNP’02

The Underlying Network

The Overlay Network

Page 12: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Host Mobility Using an Internet Indirection Infrastructure

• The Problem– Internet hosts increasingly mobile;

need to remain reachable– Flows should not be interrupted– IP address represents unique host ID & net location

• ROAM (Robust Overlay Architecture for Mobility)– Leverages i3: overlay network triggers & forward packets– Efficiency, robustness, location privacy, simultaneous mobility– No changes to end-host kernel or applications– Cost: i3 infrastructure, and proxies on end-hosts

• Simulation & Experimental Results– Stretch lower than MIP-bi able to choose nearby triggers– 50-66% of MIP-tri when 5-28% domains deploy i3 servers– Even 4 handoffs in 10 seconds have little impact on TCP performance

(ID, R)

(ID, data)

(ID, data)

(ID, R)

Receiver (R)

Sender (S)

Page 13: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Multicast Broadcast Federation

• Goal : compose different non-interoperable multicast domains to provide an end-to-end multicast service.

– Should work for both IP and App-layer protocols.

• Approach : overlay of Broadcast Gateways (BGs)

– BGs establish peering between domains.

– Inside a domain, local multicast capability is used.

– Clustered gateways for scalability.

– Independent data flows and control flow.

• Implementation :– Linux/C++ event-driven

program– Easily customizable interface

to local multicast capability (~700 lines)

– Upto 1 Gbps BG thruput with 6 nodes.

– Upto 2500 sessions with 6 nodes.

Source

Clients

BG

Broadcast Domains

PeeringData

CDN

IP Mul

SSM

Page 14: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Work in Progress

• Middleware Services– Measurement and Monitoring Infrastructure– Robust Service Composition– Authorization Interworking

Page 15: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Internet Distance Monitoring Infrastructure

• Problem: N end hosts in different administrative domains, how to select a subset to be probes, and build an overlay distance monitoring service without knowing the underlying topology?

Cluster A

End Host

Cluster B

Monitor Distance from monitor to its hosts

Distance measurements among monitors

Cluster C• Solution: Internet Iso-bar

– Clustering of hosts perceiving similar performance

• Good scalability• Good accuracy & stability

– Tested with NLANR AMP & Keynote data

• Small overhead• Incrementally deployable• [SIGMETRICS PAPA 02] & [CMG journal 02]

Page 16: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

TextTexttoto

audioaudio

TextTexttoto

audioaudio

Text Source

Text Source

WA setup: UCB, Berk. (Cable), SF (DSL), Stan., CMU, UCSD, UNSW (Aus), TU-Berlin

(Germany)

• >15sec outage• Note: BGP recovery could take

several minutes [Labovitz’00]

• End-to-end recovery in about 3.6sec: 2sec detection, ~600ms signaling, ~1sec state restoration

• Fix: detect and recover from failures using service replicas

• Highlight of results:– Quick detection (~2sec)

possible– Scalable messaging for

recovery (can handle simultaneous failure recovery of 1000s of clients)

– See SPECTS’02 paper• More recent results on load

balancing across service replicas…

• Issue: Multi-provider WA composition

• Poor availability of Internet path Poor service availability for client

Availability in Wide-Area

Service Composition

Page 17: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Authorization Control Across Administrative Domains

• Authorization authority– Provides authorization decision service.– Manages different verification methods and credentials.

• Trust peering agreement– Credential transformation rule– Acceptable verification method

Trusted third party

Domain 2

Domain 1

Service

User

AuthorizationAuthorizationAuthorityAuthority

Request - certificates - credentials

Should grant access?

Decision

Trust peering agreementTrust peering agreement - credential transformation ruleTrust peering agreementTrust peering agreement - credential transformation rule

VerificationPolicy compliance

check

Credentialtransformation

CertificatesCredentials

Page 18: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Work in Progress

• Applications Services– Voice Over IP – Adaptive Content Distribution– (Universal In-Box)

Page 19: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

IP Telephony Gateway Selection

ITG

Load Advertisement

Call Session

LS

Gateway (ITG)IP TerminalLocation Server (LS)

ITG

LS

ITG LS

ITG LSCall Blocking Probability

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Relative Weight of Congestion Sensitivity

Blo

ckin

g P

roba

bilit

y

Random RedirectionCongestion and QoS Redirection

Results: Congestion sensitive pricing decreases unnecessary call blocking, increases revenue, and improves economic efficiency Hybrid redirection achieves good QoS and low blocking probability

Goal: High quality, economically efficient telephony over the Internet Questions: How to

Perform call admission control? Route calls thru converged net?

Page 20: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

SCAN: Scalable Content Access Network

• Problem: Provide content distribution to clients with small latency, small # of replicas and efficient update dissemination

• Solution: SCAN– Leverage P2P location services to improve scalability and

locality– Simultaneous dynamic replica placement & app-level multicast

tree construction• Close to optimal #

of replicas wrt latency guarantee

• Small latency & bandwidth for sending updates

• [IPTPS 02] & [Pervasive 02]

data plane

network plane

datasource

Web server

SCAN server

client

replica

always update

adaptivecoherence

cache

Tapestry mesh

Page 21: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Layered Reference Modelfor Service Composition

Services at Layer i-1Services at Layer i-1Services at Layer i-1

Services at Layer i-1Other Servicesat Layer iComponent Services

Composed Service at Layer i

PolicyManagement

Dynamic ResourceAllocation

InteroperabiltyMeasurement-based

Adaptation

Trust Management/Verification

UnderlyingCompositionTechniques

Page 22: The SAHARA Four-Layer Model; Case-studies in Composition Bhaskaran Raman, Jimmy Shih, Randy H. Katz, SAHARA, EECS, U.C.Berkeley

Evaluation: Emulation Testbed

• Idea: Use real implementation, emulate the wide-area network behavior (NistNET)

• Opportunity: Millennium cluster

App

LibNode 1

Node 2

Node 3

Node 4

Rule for 12

Rule for 13

Rule for 34

Rule for 43

Emulator

Also have limited (8-node) wide-area testbed