Understanding Block-level Address Usage in the Visible Internetjimmychad/CN2011/Slides/paper.pdf ·...
Transcript of Understanding Block-level Address Usage in the Visible Internetjimmychad/CN2011/Slides/paper.pdf ·...
Understanding Block-level Address Usage in the Visible InternetXue Cai and John Heidemann, SIGCOMM ’10
B95502017 機械五 Chen-Hsin Ding (丁振新)
Network Issues in Cloud Computing 2011
Final Presentation
Outline
Introduction
Methodology
Applications
Validation
Conclusion
Introduction (1-4)This work provides:
Little insight into the edge of the Internet
The use of the IPv4 address space
Assumptions:
1.Many active addresses will respond to probes
2.Contiguous address are often used similarly
3.Patterns of probe responses and response delay suggest address usage
Introduction (2-4)
Introduction (3-4)Approach and Validation:
Surveyed around 24,000 /24 address blocks
Pinged every 11 minutes for around one week
Applications:
To understand how addresses are managed
How effectively addresses are used
Detect and quantify the use of dynamic address assignment
Applications (cont.):
Distinguish blocks connected mainly by low-bitrate edge links from those with broadband connections
Introduction (4-4)
The contribution of this paper is therefore to develop new approaches to classify Internet address usage and to apply those approaches to answer important questions in network management.
Methodology (1-11)
Data Collection: Surveying the Internet
Representation: Observations of Intrest
Block Identification
Ping-Observable Block Classification
Identifying Low-bitrate Blocks
Ping each address of about 1% of the allocated Internet address space around every 11 minutes for one week longer
Ignore all non-positive (no reply) responses.
Most of the /24 blocks did respond at least once by one IP address
Methodology (2-11)Data Collection: Surveying the Internet
Address Usage Metrics:
1.Availability
• The fraction of time an address is responsive.
2.Volatility
• A normalized representation of how many consecutive periods the address is responsive.
3.Median-up
• The median duration of all up periods.
Methodology (3-11)Representation: Observation of Interest
Availability
Volatility
Median-up
Methodology (4-11)Representation: Observation of Interest
Availability shows how effectively address are used.
High volatility indicates addresses that are intermittently used and often dynamically allocated.
Median uptime suggests how long an address is used.
Methodology (5-11)Representation: Observation of Interest
Edge Bitrate Metrics:
1.Median-RTT
2.Stddev-RTT
Median-RTT tracks typical response bitrate
Stddev-RTT estimates variance
Methodology (6-11)Representation: Observation of Interest
The process of finding a prefix where addresses in the block are used consistently.
The algorithm is based on elbow criterion, not K-means.
Methodology (7-11)Block Identification
Methodology (8-11)Block Identification
4 thresholds:
αH = 0.95 for high availability
αL = 0.10 for low availability
β = 0.0016 for low volatility
γ = 6 hours for a relatively long uptime.
Methodology (9-11)Ping-Observable Block Classification
Categories:
Always-stable
Sometimes-stable
Intermittent
Underutilized
Unclassifiable
Methodology (10-11)Ping-Observable Block Classification
Definition:
Low bitrate: <100Kb/s
eg.: dial-up (56Kb/s) and GPRS (57.6Kb/s)
Round-trip time (RTT) = 2(Dcpu+Dprop+Dt+Dq)
Low-bitrate block:
Goal:
To distinguish addresses with low-bitrate edge links from broadband links.
Methodology (11-11)Identifying Low-bitrate Blocks
(δ=300ms)
Application
Block Sizes
Address Utilization
Intermittent and Dynamic IP Addressing
Understanding Edge Bitrates
ApplicationBlock Sizes
A lower bound of 61% of the responsive Internet is used consistently.This supports the second assumption: the majority of contiguous addresses are used consistently.
ApplicationBlock Sizes
ApplicationAddress Utilization
ApplicationAddress Utilization
ApplicationIntermittent and Dynamic IP Addressing
ApplicationUnderstanding Edge Bitrates
Conclusion
Contiguous addresses are often used similarly
This work provides a new tool to understand Internet use and trends.
Thank You!