1. On Impact of Non-Conformant Flows on a Network of Drop-Tail Gateways Kartikeya Chandrayana Shivkumar Kalyanaraman ECSE Dept., R.P.I. chandk@rpi.edu (http://www.rpi.edu/~chandk)

2. Problem Definition Users can choose their rate control schemes.  Rate Control Scheme  rate allocation.  Network may want to bound outcome  Conformance ( e.g. TCP)  Non-Conformant – e.g. TCP un-Friendly Possible rate control schemes ?  Un-Responsive e.g. CBR, UDP etc  Responsive, e.g. TCP, small tweaks to TCP Implications:  Selfish flows grab most of the bandwidth.  One form of traffic volume based denial of service attack.  Congestion Collapse  Network has no control over equilibrium rate distributions.  Unfair Sharing aggravated on a network of Drop-Tail queues

3. Effect of Non-Conformant Flow Long Flow: Conformant (TCP Reno, U=-1/x), Short Flows: Mis-Behaving (U=- 1/x 0.5 ) RED Drop Tail Queue TCP Flows shut out Present Internet is a network of Drop Tail queues

4. Possible Solutions Some Buffer Mgmt. Scheme Users End System Based Solution: Use same congestion control algorithm Network Routers Network Based Solution: Use AQM/Scheduler in the network Limitation Constrains the choice of congestion control algorithms AQM Placement Required at every router. Limitations May require exchange of control information between all AQMs/Schedulers in the network. Generally only provides Min-Max Fairness. Most Solutions do not work with a Drop Tail queue Network No clean method to manage non-conformant flows What is the right architectural response ?

5. Detour: Congestion Control-Optimization Frameworks Users choose congestion control algorithm.  Choose a Utility Function.  TCP : U(x) = -1/x CC Scheme  Utility function Every user maximizes his own utility function. Distributed optimization. Network communicates price (loss, mark, delay) to users. Users use this price to update their rate.

6. Idea: Managing Non-Conformance: Work in the Utility Function Space Key Design Objectives: Deployment Ease Retain existing link price update rules.  No changes in the core. Retain existing user’s rate updation rules.  Allows users to chose rate control protocol. Should work with either drop or marking based network. Should work on a network of Drop Tail queues. U1U1 U2U2 UsUs Conformant Non Conformant U 1,U 2 define the conformance space U x ( Rate ) Map user’s Utility Function to Conformant Space

7. User s is described by: –x s : Rate, U s : Utility function, q: end-to-end price –x s = U s ' -1 (q) Communicate to user the price q new : q new = U s ' (U obj ' -1 (q)) Now user’s update algorithm looks like x s = U s ' -1 (q new )  x s = U obj ' -1 (q)  Appears as if user is maximizing U obj ! Map user’s utility function to some (or range of) objective utility function U s  U obj, U obj  [U 1, U 2 ] How? By Penalty Function Transformation

8. Core Network (No Changes) Any queue mgmt algorithm  Drop Tail/RED etc. Core Routers Edge Routers Edge Based Re-Marking Agent Maps utility function Manages Selfish Flows. ( Decouple it from AQM design ) Provides Service differentiation ( Map users to different utility functions ). Users Free to choose their congestion control algorithm Either marking or dropping Idea: Remap @ the Edge, Not in AQM Decouple Management of Non-Conformant Flows from AQM Design

9. What do we need to make it work ? Need to identify mis-behaving flows. –Smart Sampling in Netflow, Sample & Hold etc Estimate loss/mark rate –Currently using EWMA, WALI methods of TFRC Estimate utility function –Currently using Least Squares, Recursive LS –Needs only estimates of sending and loss rates Scalability –Keep state about only mis-behaving flows CBR/UDP flows –Need to drop (Marking does not work)

10. Results: Single Bottleneck Conformance: TCP-Friendliness 2 Flows: Conformant (TCP Reno, U=-1/x), Mis-Behaving (U=-1/x 0.5 ) Packet Drop Based Network. Drop packets from mis-behaving flows at the edge of the network. Marking Based Network. Re-mark packets from mis-behaving flows at the edge of the network. Drop Tail RED ECN Enabled

11. Results: Multi-Bottleneck (Drop Tail) Conformance: TCP-Friendliness Long Flow: Conformant (TCP Reno, U=-1/x), Short Flows: Mis-Behaving (U=- 1/x 0.5 ) TCP Flows shut out Framework prevents volume based denial of service attack. Without Re-Mapping With Re-Mapping

12. Results: Multi-Bottleneck (RED) Conformance: TCP-Friendliness Long Flow: Conformant (TCP Reno, U=-1/x), Short Flows: Mis-Behaving (U=- 1/x 0.5 ) Framework improves fair sharing of network Without Re-Mapping With Re-Mapping

13. More Results Background Traffic –Web (http) Traffic –Single/Multi Bottleneck scenarios Cross Traffic –Reverse path congestion –Especially important with RED –Multi-Bottleneck scenarios

14. Conclusions On a network of Drop Tail queues Mis-Behaving flows can force Traffic Volume based denial of service attack. –RED can prevent it though not unfair sharing. Edge-based transformation of price can handle misbehaving flows –No changes in the core No need to add penalty box functions in the context of AQM schemes (eg: CHoKe …) –Decouple mgmt of non-conformant flows from AQM Design. Works with packet drop or packet marking (ECN) Independent of buffer management algorithm. Limitation : Path Asymmetry –Different Exit and Entry routers

15. Done more work.. Utility function estimation Handling unresponsive flows Comparison with other AQM proposals Service Differentiation For more details see  http://networks.ecse.rpi.edu/~kartikc/nccc.ps  Or email chandk@rpi.edu