A Semanticbased Cache Replacement Algorithm for Mobile File Access

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A Semantic-based Cache Replacement Algorithm for
Mobile File Access

• Sharun Santhosh and Weisong Shi
• Department of Computer Science
• Wayne State University
• weisong_at_wayne.edu
• http//mist.cs.wayne.edu

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Motivation

• The Future
• Staying connected anywhere, anytime will become a
  reality
• How ?
• Cable modem or DSL connection at home
• High speed Ethernet network at work or school
• Satellite network in the car
• WiFi network at the airport or the neighborhood
  coffee shop
• Challenges
• Effectiveness - Adapt to the various underlying
  connectivity
• Convenience - Adaptation should be transparent to
  the user
• Security secure access in resource constraint
  devices

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Heterogeneous Environment
802.11a,b,g
Local Area Network wLAN
Bluetooth
Personal Area Network (PAN)
Wide Area Network (WAN)
WirelessBridge
GPS
LAN
lt1Mbs

• Access
• Synchronization
• 10 Meters

WorkgroupSwitches
GSM/CDMA
lt100Mbs
9.6 Kbit/s lt2Mbs

• Access
• hot spots
• LAN equivalent

• Voice
• SMS
• e-Mail
• Web browsing

• mCommerce
• Internet access
• Document transfer
• Low/high quality video

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Our Solution
CEGOR ClosE and Go, Open and Resume
Connection View based Secure and Transparent
Reconnection
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Roadmap

• Motivation
• Caching
• Semantic-based Caching
• Simulation Results
• Conclusion

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Caching

• Three basic steps involved in accessing data
  anywhere and anytime.
• Retrieve the files from the server
• Work on them locally
• Write the changes back to the server
• A Cache optimizes this process
• Reduce frequency of disk operations performed
• Reduce frequency of requests to the fileservers
• Reducing network load
• Problem being addressed
• Minimization of Communication

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Why Study Caching?

• It has been studied extensively yet LRU is the
  most commonly used algorithm
• Used in NFS, AFS, Sprite, CODA and most operating
  systems buffer caches
• Why ?
• Its simple to implement.
• Cache misses are acceptable in existing systems.
• Number of files replaced do not matter
• high hit ratio vs. of replacement
• But in a heterogeneous environment
• Each miss implies additional communication
• Storage of work (when in a weakly connected or
  disconnected state)
• Cannot assume a reliable link exists with the
  server

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Usage Scenario
Imagine a field engineer is accessing layout
diagrams for a faulty electricity sub-station,
half way through communications go down. A cache
MISS may cause several minutes delay, perhaps
longer, e.g.,
Which was the 10,000 volt cable?
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Is simple caching (LRU) enough??
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Goals

• Caches for distributed file systems, that operate
  across heterogeneous networks must
• Provide the hit rates of conventional caches that
  operate over homogenous networks
• Minimize communication overhead, i.e., minimize
  replacements which mean increased file
  availability and

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Our Approach to Caching

• File access patterns arent random
• A semantic relationship exists between two files
  in a file access sequence
• User behavior
• Program execution
• We define and investigate two kinds of such
  relations
• Inter-file relations
• Intra-file relations
• We introduce the notion of eviction index for
  each cached item

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Outline

• Motivation
• Caching
• Semantic-based Caching
• Simulation Results
• Conclusion

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Inter-file relations
Analysis of DFS traces
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Inter-file relations
An inter-file relationship exits between two
files i and j, if i is the next file opened
following j being closed. File j is called file
is precursor. Xi - represents the number of
times file i is accessed. Ti - represents the
time since the last access to file i. Yj -
represents the number of times file j precedes
file i.
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Intra-file relations

• An intra-file relationship is said to exist
  between two files i and j if they are both open
  before they are closed.
• Intra-file relations are based on shared time
  Si,j defined below
• Where O(i) and C(i) are the time at which file i
  was opened or closed respectively

C
O
i
C
O
j
Sij
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Intra-file relations
Ti - represents the time since the last access to
file i. Tj - represents the time since the last
access to file j where j is open before i is
closed. Si,j - represents the shared time of file
i with respect to file j where i is closed before
j. Stotal - represents the total shared time with
all files that are open before i is closed
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Inter Intra
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Workload
DFS Traces from CMU were utilized during the
simulation
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Implementation

• Seven replacement algorithms
• RR Round Robin
• LRU Least recently used
• LFU Least frequently used
• GDS Greedy dual size
• INTER based only on inter-file relations
• INTRA based on intra-file relations
• Both based on both intra and inter file
  relations
• Varying cache sizes
• 10KB, 25KB, 50KB, 100KB, 500KB
• Seven traces
• Simulator maintains a cache (hashlist), open list
  (list of currently open files), close list (list
  of files that are closed).

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Structure of simulator
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Simulator pseudocode
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Outline

• Motivation
• Caching
• Semantic-based Caching
• Simulation Results
• Conclusion

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Hit rates of all algorithms
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Replace attempts of all algorithms
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Performance DFS Traces
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Performance DFS Traces
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Performance
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The Need For File System Tracing

• Traces havent been collected periodically enough
  to reflect present day usage activity
• Publicly available traces such as traces
  collected at the disk driver level or web proxy
  traces do not give us relevant information on
  file system workload.

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System Call Interception
USER SPACE
KERNEL SPACE
int fopen(char name,char mode)
Standard Library
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Analysis Summary

• Most files were opened for less than a hundredth
  of a second
• Majority of files are accessed only a few times.
  There is a small percentage of very popular files
• Majority of files are less than 100KB in size.
  Large file can be very large (heavy tail)
• Almost half the accesses repeat within a short
  period of initially occurring
• File throughput has greatly increased due to
  presence of large files
• Majority of files accessed have a unique
  predecessor

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MIST traces Hit Rates
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MIST Traces Files Replaced
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MIST Traces Byte Hit Rate
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Summary

• We have presented a semantic-based caching
  algorithm and shown that it performs better than
  conventional caching approaches in terms of hit
  ratio and byte hit ratio
• We have also shown that it does this performing
  far fewer replacements
• Compared to prevalent replacement strategies that
  ignore file relations and communication overhead,
  this approach would seem to better suit
  distributed file systems that operate across
  heterogeneous environments

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Future Work

• Collecting more state-of-the-art distributed file
  systems traces
• Applying the cache replacement algorithm into a
  real wireless file system in computer-assisted
  surgery application
• Investigating the idea into more general
  applications, such as mobile database access,
  etc.

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Questions Comments?
weisong_at_wayne.edu http//mist.cs.wayne.edu