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Bandwidth-driven Flow Allocation Policy
for RINA
Michal Koutenskรฝ / Vladimรญr Veselรฝ / Vincenzo Maf๏ฌone
2020
Motivation
Two related problems:
Guaranteeing bandwidth for flows during their lifetime
โ†’ Reserving part of available bandwidth
Proactive congestion prevention
โ†’ Reject flow allocation requests that could congest the
network
rlite
A light RINA implementation
GPL/LGPL licensed RINA stack for Linux
Logically decoupled into several components
Behavior of components extendable through policies
Bandwidth reservation
Utilizing already available information
Flow requests can specify desired bandwidth
Routing component already keeps a graph of the DIF
We need to extend the graph with capacity information
Keeping our view of the DIF up to date
Bandwidth reservation
Logically centralized, fault-tolerant
Based on Raft consensus algorithm
โ€œMan-in-the-middleโ€ for the flow allocation process
Raft leader intercepts every flow allocation negotiation
Searches the DIF graph to ๏ฌnd a viable path
Reserves bandwidth along the path
Raft replication ensures fault-tolerance
Bandwidth reservation
Tied to a speci๏ฌc path
Requires cooperation from the routing component
Raft leader distributes static route updates for each flow
Multi-path routing, better bandwidth utilization
Less predictable paths and connection parameters
Congestion prevention
Utilizing knowledge of bandwidth state
Assume every flow will use all requested bandwidth
No flow may use more than it requested
Reject requests which we cannot satisfy
Centrally managed flow allocation
Congestion prevention
Handling unbounded flows
Two approaches:
โ— Reject them
โ— Apply a pre-de๏ฌned bandwidth limit
Con๏ฌgurable parameter
Congestion prevention
Enforcing rules
The assumption that no flow uses more than requested
is critical
Achieved by rate-limiting every flow
Experiments
Experiments
Questions?

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Rina2020 michal

  • 1. Bandwidth-driven Flow Allocation Policy for RINA Michal Koutenskรฝ / Vladimรญr Veselรฝ / Vincenzo Maf๏ฌone 2020
  • 2. Motivation Two related problems: Guaranteeing bandwidth for flows during their lifetime โ†’ Reserving part of available bandwidth Proactive congestion prevention โ†’ Reject flow allocation requests that could congest the network
  • 3. rlite A light RINA implementation GPL/LGPL licensed RINA stack for Linux Logically decoupled into several components Behavior of components extendable through policies
  • 4. Bandwidth reservation Utilizing already available information Flow requests can specify desired bandwidth Routing component already keeps a graph of the DIF We need to extend the graph with capacity information Keeping our view of the DIF up to date
  • 5. Bandwidth reservation Logically centralized, fault-tolerant Based on Raft consensus algorithm โ€œMan-in-the-middleโ€ for the flow allocation process Raft leader intercepts every flow allocation negotiation Searches the DIF graph to ๏ฌnd a viable path Reserves bandwidth along the path Raft replication ensures fault-tolerance
  • 6. Bandwidth reservation Tied to a speci๏ฌc path Requires cooperation from the routing component Raft leader distributes static route updates for each flow Multi-path routing, better bandwidth utilization Less predictable paths and connection parameters
  • 7. Congestion prevention Utilizing knowledge of bandwidth state Assume every flow will use all requested bandwidth No flow may use more than it requested Reject requests which we cannot satisfy Centrally managed flow allocation
  • 8. Congestion prevention Handling unbounded flows Two approaches: โ— Reject them โ— Apply a pre-de๏ฌned bandwidth limit Con๏ฌgurable parameter
  • 9. Congestion prevention Enforcing rules The assumption that no flow uses more than requested is critical Achieved by rate-limiting every flow