Towards a Transparent and ProactivelyManaged Internet

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Towards a Transparent and Proactively-Managed
Internet

• Ehab Al-Shaer
• School of Computer Science
• DePaul University

Yan Chen EECS Department Northwestern University
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Motivations

• The Internet has evolved to become a
  un-cooperative ossificated network of networks
• Network has to be treated as a blackbox
• Performance of even neighboring networks are
  opaque
• Inter-domain routing based on policies but not
  performance
• Have to resort to overlay networks which are
  suboptimal
• Diagnosis and fault location extremely hard
• Network config management reactive and expensive
• Reactive configurations tune after deployment
• Vulnerable manually handled and subject to
  conflicts
• Imperative fragmented need to access several
  specific devices in order to implement a service
  goal

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Proposed Solution I Transparent Internet

• Every network shares its measurement and
  management information with other networks when
  necessary (glass box)
• Link-level performance delay, loss rate,
  available bandwidth, etc.
• Management info
• Configuration QoS setting, traffic policing
• Middle box settings firewalls, etc.
• The information sharing
• As part of the inter-domain protocols
  Transparent Gateway Protocols (TGP)
• Other applications leverage DHT

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Analogy to the Airline Alliance

• When airlines compose multi-lag flights, they
  need more than just route info.
• Type of aircraft, of vacancies, probability of
  punctuation, etc.
• Such open model is mutual beneficial
• Provide the best flight composition for clients
• Similarly, open network model can provide best
  communications for applications

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Proposed Solution II Proactive Configuration
Management

• Proactive verification configuration verified
  and translated to different vendor specific
  devices
• Proactive validation Test the configuration
  changes on the real archived network traffic
  without interrupting the main operation network
• Autonomic configuration configurations are
  auto-tuned dynamically to achieve the objectives

Dynamic Validation auto-tuning
Deploying
Optimizing
defining
Verifying
Evaluating
Validation
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Objectives

• Provides a completely transparent view of the
  Internet to networks and applications
• Diagnosis trouble shooting becomes extremely
  easy
• No more Internet tomography needed
• Flexible inter-domain routing
• Not just based on policy or of AS/hops
• Flexible metrics based on bandwidth, latency,
  etc.
• Global traffic engineering
• Each AS performs its own local traffic
  engineering
• Provide AS path-level routing guide
• Unified framework that applications query
  (push/pull) info as needed
• Streaming media, content distribution
• Anomaly/security applications

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Flexible Inter-domain Routing

• Multiple routing paths with TGP
• Incorporate measurement info into AS paths
• Bandwidth-intensive and latency-intensive
  applications can take different AS paths.
• Challenge inter-domain routing based on
  bandwidth without making reservation
• Solution Discretize the bandwidth for better
  stability
• Though stability is a classical problem, not
  unique to TGP

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Global Traffic Engineering

• For the current Internet, only local optimum is
  achieved in each AS
• Allowing the network to handle all traffic
  patterns possible, within the networks
  ingress-egress capacity constraints (e.g. two
  phase routing)
• With global information, we can potentially
  achieve global optimum (or Nash equilibrium)
• Each AS is a selfish individual
• A center (or each AS) infers the Nash equilibrium
  
• Each AS can try the Nash equilibrium, or attempt
  to benefit itself based on the inferred Nash
  equilibrium

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Example of Benefit of Global TE
1G traffic to AS 1
AS 4
AS 2
1G
AS 5
AS 1
1G traffic to AS 1
AS 3
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Example of Benefit of Global TE

• Without Global TE

1G traffic to AS 1
AS 4
AS 2
1G
AS 5
AS 1
1G traffic to AS 1
AS 3
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Example of Benefit of Global TE

• With Global TE

1G traffic to AS 1
AS 4
AS 2
1G
AS 5
AS 1
1G traffic to AS 1
AS 3
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Unified Transparency Framework for Various
Functionality

• Sharing of anomaly/security-related measurement
• Various characteristics of traffic heavy hitter,
  heavy changes, histogram, etc.
• Self-diagnosis to survivability
• Adaptations
• Routing adaptations at router level or
  application level

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Practical Issues and Solutions

• Incentives for information sharing
• Mandatory for next-generation Internet ?
• Alliance model for incremental growth
• Security/cheating Trust but verify
• Trust most of the info shared but periodically
  verify
• Much easier than the current Internet tomography
  unless many ASes collude
• Verification part of the protocol
• Some fields in the packet headers designed for
  that purpose

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Backup Materials
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Measurement Info to Share

• Basic metrics
• Delay, loss rate, capacity, available bandwidth
• Demand (or traffic volume) and application types
• Intra-AS Measurement Info
• Link-level info
• Queried only when necessary
• Aggregated Info
• OD flow level info
• Path segment b/t entry and exit points in each AS
• Inter-AS Measurement Info
• General AS relationship
• AS-level topology
• Inter-AS link metrics

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Transparent Internet Architecture
Combined w/ routing info and export to
neighboring ASes through TGP protocol
Provide global retrievable Management Information
Base (MIB) with DHT
Network link-level monitoring
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Methodology
Analytical evaluation
PlanetLab tests

• Network topology
• Web workload
• Network end-to-end latency measurement

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TGP MIB Dissemination Architecture

• Leverage Distributed Hash Table - Tapestry for
• Distributed, scalable location with guaranteed
  success
• Search with locality

data plane
data source
Dynamic Replication/Update and Replica Management
Replica Location
Web server
SCAN server
Overlay Network Monitoring
network plane
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Adaptive Overlay Streaming Media
Stanford
UC San Diego
UC Berkeley
X
HP Labs

• Implemented with Winamp client and SHOUTcast
  server
• Congestion introduced with a Packet Shaper
• Skip-free playback server buffering and
  rewinding
• Total adaptation time

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Summary

• A tomography-based overlay network monitoring
  system
• Selectively monitor a basis set of O(n logn)
  paths to infer the loss rates of O(n2) paths
• Works in real-time, adaptive to topology changes,
  has good load balancing and tolerates topology
  errors
• Both simulation and real Internet experiments
  promising
• Built adaptive overlay streaming media system on
  top of TOM
• Bypass congestion/failures for smooth playback
  within seconds

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Tie Back to SCAN
Provision Dynamic Replication Update
Multicast Tree Building
Replica Management (Incremental) Content
Clustering
Network DoS Resilient Replica Location Tapestry
Network End-to-End Distance Monitoring Internet
Iso-bar latency TOM loss rate
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Contribution of My Thesis

• Replica location
• Proposed the first simulation-based network DoS
  resilience benchmark and quantify three types of
  directory services
• Dynamically place close to optimal of replicas
• Self-organize replicas into a scalable app-level
  multicast tree for disseminating updates
• Cluster objects to significantly reduce the
  management overhead with little performance
  sacrifice
• Online incremental clustering and replication to
  adapt to users access pattern changes
• Scalable overlay network monitoring

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Existing CDNs Fail to Address these Challenges
No coherence for dynamic content
X
Unscalable network monitoring - O(M N) M of
client groups, N of server farms
Non-cooperative replication inefficient
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Problem Formulation

• Subject to certain total replication cost (e.g.,
  of URL replicas)
• Find a scalable, adaptive replication strategy to
  reduce avg access cost

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SCAN Scalable Content Access Network
CDN Applications (e.g. streaming media)
Provision Cooperative Clustering-based
Replication
Coherence Update Multicast Tree Construction
Network Distance/ Congestion/ Failure Estimation
User Behavior/ Workload Monitoring
Network Performance Monitoring
red my work, black out of scope
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Comparison of Content Delivery Systems (contd)