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CLayer: Cross-Layer Packet Classification with Explicit Coordination

Implementing a novel cross-layer classification approach, CLayer enhances packet classification performance with explicit coordination between entities. Authored by Mosharaf Chowdhury, Sameer Agarwal, Dilip Joseph, and Ion Stoica.

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CLayer: Cross-Layer Packet Classification with Explicit Coordination

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  1. CLayer Packet classification with explicit coordination Mosharaf Chowdhurywith Sameer Agarwal, Dilip Joseph, and Ion Stoica

  2. Motivation Packet classification is everywhere INTERNET Google GRAD CS Forum @ Mountainview

  3. Problems 1 Existing approaches are point solutions for specific layer/service Packet classification is expensive • Computation and memory requirements • Power hungry Configuration complexity • Lack of coordination between entities involved Semantic gap 3 2 4 5 Google GRAD CS Forum @ Mountainview

  4. Solution CLayer is a cross-layer classification primitive • Generic mechanism to configure and implement capability-driven classification offloading • Explicit coordination between classifiers and helpers Label-based per-flow classification • Labels are verifiable, confidential, and non-transferable “Classify once, verify thereafter” Google GRAD CS Forum @ Mountainview

  5. Outline CLayer classification model Fate-carrying labels (FCLs) Implementation Results Google GRAD CS Forum @ Mountainview

  6. Classification model Google GRAD CS Forum @ Mountainview

  7. QoS:q1 Capability TCPFLow, WebSess ClassReq Control plane ClassReq QoS:q1, WebSess:1 2b ClassRsp QoS:q1, WebSess:1 1 2a Web server 1 QoS enabled router Load balancer End host A Web server 2 3 Google GRAD CS Forum @ Mountainview

  8. Data plane 4b 4a Web server 1 QoS:q1, WebSess:1 QoS:q1, WebSess:1 Payload Payload QoS enabled router Load balancer End host A Web server 2 Google GRAD CS Forum @ Mountainview

  9. Fate-carrying labels Google GRAD CS Forum @ Mountainview

  10. FCL basics A label in CLayer is an opaque bag of bits • Issued by a classifier for a particular flow • Meaningful only to the issuer • ‹label→action› lookup A fate-carrying label carries the action itself • No ‹label→action› lookup • No states in classifiers Google GRAD CS Forum @ Mountainview

  11. Requirements Authenticity and Integrity • Verifiable and non-transferable • Unforgeable and single-use only Confidentiality • Impossible to infer Performance • Not better off without CLayer HMAC Checksum Obfuscation Periodic Invalidation Line-speed hashing Low overhead Google GRAD CS Forum @ Mountainview

  12. Placement Application Layer 4 Bits 8 Bits 32 Bits Transport Layer RESIG CLayer N HANDLE MSG Network Layer INFO 0 … INFO (N – 1) 4 Bits 32 Bits 16 Bits CLayer Header TYPE ID LEN CHECKSUM ACTION HMAC (5-tuple, ACTION, SECRET) FCL Google GRAD CS Forum @ Mountainview

  13. Implementation Google GRAD CS Forum @ Mountainview

  14. Implementation stats C++ Implementation using user level Click software router Core components: • CLayer socket library and daemon (4025 lines) • Layer 4 firewall (308 lines) • Layer 4 load balancer (190 lines) Ported applications: • lighttpd, httperf, wget, nuttcp, elinks (< 50 lines) Google GRAD CS Forum @ Mountainview

  15. Results Google GRAD CS Forum @ Mountainview

  16. Overheads CLayer overheads at helpers: • State: ~10 bytes per connection • Processing: less than 1 μs At classifiers: • No state overheads • Processing: varies in s/w and h/w implementations Per-packet overheads: • Proportional to the number of labels • Potential bottleneck Google GRAD CS Forum @ Mountainview

  17. Performance attractiveness threshold Google GRAD CS Forum @ Mountainview

  18. Multiple classifiers hash overhead software implementation overhead (Each with 7500 rules) Google GRAD CS Forum @ Mountainview

  19. Summary Packet classification requires a dedicated layer CLayer provides significant performance gain • 2-4 times increase in classifier throughput • Additional ~100% increase in throughput in trusted domains or with line-speed h/w hashing CLayer adoption requires minimal change • Most suitable for controlled environments like data center and enterprise networks Google GRAD CS Forum @ Mountainview

  20. Questions ? ? ? Google GRAD CS Forum @ Mountainview

  21. Backup Google GRAD CS Forum @ Mountainview

  22. Router E End host B End host A CLayer handshaking 2 CL_SYN CL_SYN 1 Capability: [A,TCPFlow,Label] Capability: [A,TCPFlow,Label] ClassReq: [E, A, TCPFlow,Label:q1] 3 4 CL_SYNACK CL_SYNACK Control Plane Capability: [B,TCPFlow,Label] Capability: [B,TCPFlow,Label] EchoReq: [E, A, TCPFlow,Label:q1] EchoReq: [E, A, TCPFlow,Label:q1] ClassReq: [E, B, TCPFlow,Label:q2] CL_ACK1 6 5 CL_ACK1 EchoReq: [E, B, TCPFlow,Label:q2] EchoReq: [E, B, TCPFlow,Label:q2] Results: [E, TCPFlow,Label:q1] Results: [E, TCPFlow,Label:q1] 7 8 CL_ACK2 CL_ACK2 Results: [E, TCPFlow,Label:q2] Results: [E, TCPFlow,Label:q2] DATA DATA Results: [E, TCPFlow,Label:q1] Results: [E, TCPFlow,Label:q2] Data Plane Google GRAD CS Forum @ Mountainview

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