Xin Wang and Henning Schulzrinne

1
Resource Negotiation and Pricing in DiffServ
for Adaptive Multimedia Applications

• Xin Wang and Henning Schulzrinne
• Internet Real -Time Laboratory
• Columbia University
• http//www.cs.columbia.edu/xinwang

2
Outline

• Introduction
• A Resource Negotiation And Pricing
  protocol RNAP
• Pricing models
• User adaptation
• Test-bed demonstration of Resource Negotiation
  Framework
• Simulation and discussion of Resource Negotiation
  Framework
• Conclusion and future work

Resource Negotiation Framework
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Is Simple Over-Provisioning Enough?

• Current Internet
• Growth of new IP services and applications with
  different bandwidth and quality of service
  requirements
• Revenue from the traditional connectivity
  services is declining
• New services present opportunities and challenges
  
• Even though average bandwidth utilization is low,
  congestion can happen access links get congested
  frequently
• Wireless bandwidth is even more scarce
• Bandwidth prices are not dropping rapidly
• No intrinsic upper limit on bandwidth use

Option - manage the existing bandwidth better,
with a service model which uses bandwidth
efficiently.
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A More Efficient Service Model

• Quality of Service (QoS)
• Condition the network to provide predictability
  to an application even during high user demand
• Provide multiple levels of services
• Problems signaling to facilitate service
  negotiation differential charging
• Application adaptation
• Source rate adaptation based on network
  conditions - congestion control and efficient
  bandwidth utilization
• Problems
• How adaptive applications work with QoS-assured
  services? How to motivate an application to
  adapt?

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Design Goals

• Develop an efficient service model which
  combines QoS assurance with user rate adaptation
• Increase service value to the users through
  greater choices over price and quality, improved
  connectivity, and expected QoS
• Reduce network provision complexity, improve
  network efficiency and increase revenue to the
  providers allows network operator to create
  different trade-offs between blocking admissions
  and raising congestion prices

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Our Work

• Propose a Resource Negotiation And Pricing
  protocol RNAP
• Allows for service predictability, multi-party
  negotiation
• Designed to be scalable and reliable
• Can be embedded in other protocols, or
  implemented independently
• Enables differential charging for supporting
  differentiated services, reflecting the service
  cost and long-term user demand
• Support short-term resource commitment for better
  response to user demand and network conditions,
  and more efficient resource usage congestion
  pricing to motivate user adaptation
• Develop reference user adaptation model
• Demonstrate negotiation framework on test-bed
  network
• Show significant advantages relative to static
  resource allocation and fixed pricing using
  simulations

7
Outline

• Introduction
• A Resource Negotiation And Pricing
  protocol RNAP
• Pricing models
• User adaptation
• Test-bed demonstration of Resource Negotiation
  Framework
• Simulation and discussion of Resource Negotiation
  Framework
• Conclusion and future work

Resource Negotiation Framework
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Protocol Architectures Centralized(RNAP-C)
Host Resource Negotiator
RNAP Messages
Network Resource Negotiator
NRN
NRN
NRN
HRN
HRN
Access Domain - A
Edge Router
Access Domain - B
Internal Router
Intra-domain messages
Transit Domain
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Protocol Architectures Distributed (RNAP-D)
Local Resource Negotiator
RNAP Messages
HRN
LRN
LRN
LRN
LRN
LRN
LRN
LRN
LRN
HRN
LRN
LRN
LRN
Access Domain - A
LRN
LRN
Edge Router
Access Domain - B
Internal Router
Transit Domain
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RNAP Messages
Query Inquires about available services, prices
Query
Quotation
Quotation Specifies service availability,
accumulates service statistics,
prices
Reserve
Commit
Reserve Requests services and resources,
Modifies earlier requests
Periodic negotiation
Quotation
Commit Confirms the service request at a
specific price or denies it.
Reserve
Commit
Close Tears down negotiation session
Close
Release Releases the resources
Release
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Message Aggregation (RNAP-D)
Turn on router alert
Edge Routers
Sink-tree-based aggregation
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Message Aggregation (RNAP-D)
Turn off router alert
Sink-tree-based aggregation
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Block Negotiation (Network-Network)
Aggregated resources are added/removed in large
blocks to minimize negotiation overhead and
reduce network dynamics
Bandwidth
time
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Outline

• Introduction
• A Resource Negotiation And Pricing
  protocol RNAP
• Pricing models
• User adaptation
• Test-bed demonstration of Resource Negotiation
  Framework
• Simulation and discussion of Resource Negotiation
  Framework
• Conclusion and future work

Resource Negotiation Framework
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Two Volume-based Pricing Strategies

• Fixed-Price (FP) fixed unit volume price
• During congestion higher blocking rate OR higher
  dropping rate and delay
• Congestion-dependent-Price (CP) FP
  congestion-sensitive price component
• During congestion users have options to maintain
  service by paying more OR reducing sending rate
  OR switching to lower service class
• Overall reduced rate of service blocking, packet
  dropping and delay

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Proposed Pricing Strategies

• Holding price and charge based on cost of
  blocking other users by holding bandwidth even
  without sending data
• phj ? j (pu j - pu j-1) , chij (n) ph j r
  ij (n)? j
• Usage price and charge maximize the providers
  profit, constrained by resource availability
• max Sl x j (pu1 , pu2 , , puJ ) puj - f(C),
  s.t. r (x (pu2 , pu2 , , puJ )) ? R
  
  
• cuij (n) pu j v ij (n)
• Congestion price and charge drive demand to
  supply level
• pc j (n) min pcj (n-1) ? j (Dj, Sj) x
  (Dj-Sj)/Sj,0 , pmaxj
  
• ccij (n) pc j v ij (n)
  

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Usage Price for Differentiated Service

• Usage price based on cost of class bandwidth
• lower target load (higher QoS) -gt higher per-unit
  bandwidth price
• Parameters
  
• pbasic basic rate for fully used bandwidth
  
• ? j expected load ratio of class j
• xij effective bandwidth consumption of
  application i
• Aj constant elasticity demand parameter
• Price for class j puj pbasic / ? j
• Demand of class j xj ( puj ) Aj / puj
• Effective bandwidth consumption xe j ( puj )
  Aj / ( puj ? j )
• Network maximizes profit
• max Sl (Aj / pu j ) pu j - f (C), puj
  pbasic / ? j , s. t. Sl Aj / ( pu j ? j ) ? C
• Hence pbasic Sl Aj / C , puj Sl Aj /(C? j)

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Outline

• Introduction
• A Resource Negotiation And Pricing
  protocol RNAP
• Pricing models
• User adaptation
• Test-bed demonstration of Resource Negotiation
  Framework
• Simulation and discussion of Resource Negotiation
  Framework
• Conclusion and future work

Resource Negotiation Framework
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Rate Adaptation of Multimedia System

• Gain optimal perceptual value of the system based
  on the network conditions and user profile
• Utility function users preference or
  willingness to pay

Cost
U1
U2
Utility/cost/budget
U3
Budget
Bandwidth
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Example Utility Function

• Utility is a function of bandwidth at fixed QoS
• An example utility function U (x) U0 ? log
  (x / xm)
• U0 perceived (opportunity) value at minimum
  bandwidth
• ? sensitivity of the utility to bandwidth
• Function of both bandwidth and QoS
• U (x) U0 ? log (x / xm) - kd d - kl l , for x
  ? xm
• kd sensitivity to delay
• kl sensitivity to loss

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Rate-Adaptation Models

• Optimize perceived surplus of the multimedia
  system subject to budget and application
  requirements
• User utility optimization
• U Si Ui (xi (Tspec, Rspec)
• max Sl Ui (xi ) - Ci (xi) , s. t. Sl Ci (xi)
  ? b , xmini ? xi ? xmaxi
• Determine optimal Tspec and Rspec
• With the example utility functions, resource
  request of application i
• Without budget constraint x i ?i / pi
• With budget constraint x i bi / pi, with b
  i b (? i / Sl ? k)

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Outline

• Introduction
• A Resource Negotiation And Pricing
  protocol RNAP
• Pricing models
• User adaptation
• Test-bed demonstration of Resource Negotiation
  Framework
• Simulation and discussion of Resource Negotiation
  Framework
• Conclusion and future work

Resource Negotiation Framework
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Testbed Architecture

• Demonstrate functionality and performance
  improvement
• blocking rate, loss, delay, price stability,
  perceived media quality
• Host
• HRN negotiates for a system
• Host processes (HRN, VIC, RAT) communicate
  through Mbus
• Network
• Router FreeBSD 3.4 ALTQ 2.2, CBQ extended for
  DiffServ
• NRN (1) Process RNAP messages (2) Admission
  control, monitor statistics, compute price (3)
  At edge, dynamically configure the conditioners
  and form charge
• Inter-entity signaling RNAP

VIC
RAT
Mbus
HRN
RNAP
NRN
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Outline

• Introduction
• A Resource Negotiation And Pricing
  protocol RNAP
• Pricing models
• User adaptation
• Test-bed demonstration of Resource Negotiation
  Framework
• Simulation and discussion of Resource Negotiation
  Framework
• Conclusion and future work

Resource Negotiation Framework
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Simulation Design

• Performance comparison fixed price policy (FP)
  vs. congestion price based adaptive service (CPA)
  
• loss, delay, blocking rate, user benefit,
  network revenue, stability
• Three groups of experiments effect of traffic
  load, admission control, and load balance between
  classes
• Weighted Round Robin (WRR) scheduler
• Three classes EF, AF, BE
• EF load threshold 40, delay bound 2 ms, loss
  bound 10-6
• AF load threshold 60, delay bound 5 ms, loss
  bound 10-4
• BE load threshold 90,delay bound 100 ms,loss
  bound 10-2
• Sources mix of on-off traffic and Pareto on-off
  traffic

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Simulation Architecture
Topology 1 (60 users)
Topology 2 (360 users)
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Effect of Traffic Load
CPA maintains the traffic load at the targeted
level, meets the expected performance bounds
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Effect of Admission Control
Admission control is important in maintaining the
expected performance of a class.
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Effect of Admission Control
(contd)
With admission control, the dynamics of the
network price can be better controlled. Coupled
with user adaptation, the blocking rate of CPA is
up to 30 times smaller than that of FP.
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Effect of Admission Control
(contd)
CPA allows for higher network revenue and user
benefit.
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Load Balance Between Classes
Even when a small portion of users (15) select
other service classes, the performance of the
over-loaded class is greatly improved.
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Conclusions

• Proposed a dynamic resource negotiation framework
  consisting of A Resource Negotiation And Pricing
  protocol (RNAP) , a rate and QoS adaptation
  model, and a pricing model
• RNAP supports dynamic service negotiation
• Pricing models based on resources consumed by
  service class and long-term user demand
  including congestion-sensitive component to
  motivate user demand adaptation
• Performance
• Effectively restricts load to targeted level and
  meet service assurance
• Provide lower blocking rate, higher user
  satisfaction and network revenue
• Admission control and inter-service class
  adaptation give further improvements in blocking
  rate and price stability

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Further Work

• Interaction of short-term resource negotiation
  with longer-term network provision
• A light-weight resource management protocol
• Cost distribution in QoS-enhanced multicast
  network
• Pricing and service negotiation in the presence
  of alternative data paths or competing networks
• User valuation models for different QoS
• Resource provisioning in wireless environment