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Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
Profiling And Optimization Of Software Base Network Analysis Applications
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Profiling And Optimization Of Software Base Network Analysis Applications

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  • 1. Profiling and Optimization of Software-Base Network-Analysis Applications Loris Degioanni, Mario Baldi, Fulvio Risso, and Gianluca Varenni Presented by: Hargyo T. Nugroho Computer Network & System Research Laboratory
  • 2. Introduction
    • The needs of high-speeds networking grows very fast
    • Hardware solutions
      • Usually expensive
      • Difficult to deploy
      • Low degree of flexibility
      • Performs better
    • Real-time software solutions (usually implemented as libraries libpcap, winpcap)
  • 3. Motivation
    • Improving the overall performance of network analysis tool is still open issue
    • The biggest problem : only focus on some specific components of traffic analysis
    • This work identifies the components involved in network analysis and measures their relative weight
  • 4. Related Work
    • Packet Filtering
      • CSPF (CMU/Stanford Packet Filter) : filtering virtual machine (virtual cpu, register,etc)
      • BPF : improves CSPF by limiting the number of copies packets undergo and by defining better virtual processor
      • MPF, PathFinder, DPF, BPF+
    • Packet classification
    • Buffering and copying  only few 
  • 5. Packet Capture Architecture
  • 6. Unoptimized Packet Processing Cost
    • To increase performance we need:
    • Reduce timestamp costs
    • Reduce tap processing costs
    • Reduce 1 st copy cost
    • Improve filtering
    Current Winpcap 3.0 overhead in clock cycles Total overhead: 5680 clock cycles
  • 7. Optimized Packet Processing Costs
    • To increase performance we need:
    • Hardware-based timestamp
    • Avoid NIC driver and OS-related costs
    • Shared buffer (memcopy overhead)
    Current Winpcap 3.0 overhead in clock cycles Total overhead: 3164 clock cycles
  • 8. Packet capture performance and high speed networks (Single CPU) Notes: - min packet size: 84 bytes (64 bytes + 8 Preambol + 1 Start Frame Delimiter + 12 Inter Packet Gap) - “real” traffic: 2500 packets for each 10Mbps of bandwidth (the table takes into account 3750 packets (i.e. +50%) for each 10Mbps )
  • 9. For doing “simple elaboration”...
    • Software-only packet capture is OK at GE with real traffic
      • > 5000 clock cycles available
    • Simple acceleration may be OK at 10GE with real traffic
      • > 500 clock cycles
    • More accurate software-based elaboration may be obtained through SMP machines
      • One CPU captures packets
      • The other processes them
    • Warning
      • At high speed we must find a way to aggregate results
  • 10. Conclusions
    • Software optimizations are still possible, despite these technologies are considered mature
      • Most important improvement due to the optimization of the whole architecture
      • Very limited improvement due when doing “academic” optimization
        • Filtering, shared buffer
    • Results
      • Gigabit speed is feasible with standard hardware
      • Some simple hardware-based speedtup may ba enough for 10G speed

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