On Failure Recoverability of Client-Server Applications in Mobile Wireless Environments

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On Failure Recoverability of Client-ServerApplica
tions in Mobile Wireless Environments

• Ing-Ray Chen, Baoshan Gu, Sapna E. George and
  Sheng-Tzong Cheng
• Present by Heng Zhang Ying Jin

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Agenda

• Introduction
• System Model
• Analysis of Failure Recovery Probability
• Numerical Results
• Failure Recoverability vs. Cost Tradeoff Analysis
• Conclusion and Future Research

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Introduction

• Failure in mobile host
• Checkpoint strategies
• Logging strategies
• Mobility handoff strategies on the Failure
  Recoverability
• Mobile Host in a client-server applications can
  easily fail due to
• Low battery power
• Memory exhaustion
• Lack of resource (e.g. bandwidth)

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Introduction (cont)

• Checkpoint
• Application takes a snapshot of its state to save
  the values of state variables in a persistent
  storage. So when a failure occurs, MH can roll
  back to the sate saved at the checkpoint.
• Checkpoint protocols
• Coordinated multiple MH consistent global
  checkpoint
• Uncoordinated one MH MH can independently
  checkpoint its local state

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Introduction (cont)

• Write-event
• MH receives a message or a user input which
  modifies the state of the application.
• No-logging
• A new checkpoint is created whenever a
  write-event happens.
• High checkpoint cost.
• Logging
• Create checkpoints periodically
• Logs write-events which occur in between two
  consecutive checkpoints.
• Decrease checkpoint cost
• More failure recovery time

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Introduction (cont)

• Mobility Handoff strategies on the Failure
  Recoverability
• Eager
• Always keep the logging and checkpoint
  information in the base station MH currently
  resides.
• Fast failure recovery
• Lazy
• Do not move the checkpoint and logging as the MH
  moves. A forwarding pointer is established from
  the current base station to the last base station.

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System Model (1)

• Consider a MH, in a client-server distributed
  application in a mobile wireless environment
• Periodically checkpoint
• The write events between 2 consecutive
  checkpoints recorded by creating log entries
• Assume the checkpoint and log information will be
  kept at the base stations
• Two mobility hand off strategies are considered
• Eager strategy
• lazy strategy

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System Model (2)

• Eager Strategy
• When the MH fails, the persistent information
  (the last checkpoint and message logs afterward)
  can be found at the current base station.
• Lazy Strategy
• When MH moves from cell n to cell 1, a linked
  list is formed with the length of n-1. If the MH
  fails, there will be n cell involved in failure
  recovery and the persistent information will be
  scattered in the base stations on the forwarding
  chain.

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Analysis of Failure Recovery Probability

• Notations

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Analysis of Failure Recovery Probability
Eager Mobility Handoff Strategy

• When checkpoint operation is performed, all log
  entries before the checkpoint will be purged and
  No. of the log entries N(t) will be reset to 0.
• The MH will only re-execute those log entries
  accumulated past the last checkpoint.

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Cdf of the Recovery Time
Analysis of Failure Recovery Probability Eager
Strategy
TR
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Let tt - MTc
Analysis of Failure Recovery Probability Eager
Strategy
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Consider the Special Case Logs
arrivePoisson process with arrival rate ? MH
failure timeExponentially distributed with
failure rate d
Analysis of Failure Recovery Probability Eager
Strategy
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Analysis of Failure Recovery Probability Eager
Strategy
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Analysis of Failure Recovery Probability

• Lazy Mobility Handoff Strategy
• Suppose that before the failure occur, the No.
  of cells visited by a MH is k since the last
  checkpoint. The recovery process
• Transferring the last checkpoint and log entries
  distributed among the k base stations to the
  current base station via the wired network
• Transfer the last checkpoint with log entries
  from the current base station to the MH (via the
  wireless network)
• The re-execution of the log entries

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Random variable representing the number of base
station crossed by the MH past the last
checkpoint given that the failure time is t
Analysis of Failure Recovery Probability Lazy
Strategy
Cdf of the Recovery Time
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Let tt - MTc
Analysis of Failure Recovery Probability Lazy
Strategy
TR
r transmission ratio between wired and wireless
communication.
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Consider the Special Case Logs arrive
Poisson process with arrival rate ? MH
failure timeExponentially distributed with
failure rate d Residence time-Exponentially
distributed with rate s
Analysis of Failure Recovery Probability Lazy
Strategy
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Analysis of Failure Recovery Probability Lazy
Strategy
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Numerical Results

• Effects of various parameters on failure
  recoverability
• Eager handoff logging
• Lazy handoff logging

Log arrival rate ?
MH failure rate d
Checkpoint interval Tc
Transmission ratio between wired and wireless communication r
MH mobility rate s
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Numerical Results (cont)

• Failure recovery probability for different
  recovery time

Checkpoint interval 1000s
Log arrival rate 0.1
Mobility rate 0.01
Failure rate 0.0001
Transmission ratio 0.1

• Failure recovery probability under the eager
  strategy is always better than that under the
  lazy strategy.

• Given enough recovery time (T gt 0.3)
• in this case, the failure recoverability offered
  by the less costly
• lazy strategy is just as good as the more costly
  eager strategy.

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Numerical Results (cont)

• Effect of log arrival rate and mobility rate

Checkpoint interval 1000s
Recovery time 0.24s
Mobility rate 0.01 0.001
Failure rate 0.0001
Transmission ratio 0.1

• The system recovery probability
• decreases dramatically as the log
• arrival rate increases.

• Recovery probability difference between the two
• handoff strategies is small when the log arrival
• rate is low.

• The effect of mobility rate on the recovery
  probability is marginal.

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Numerical Results (cont)

• Effect of the checkpoint interval

Log arrival rate 0.1
Recovery time 0.24s
Mobility rate 0.01
Failure rate 0.0001
Transmission ratio 0.1

• The system recovery probability
• decreases dramatically as the
• checkpoint interval increases.

• The difference in recovery probability at a
  particular
• recovery time between the Eager and Lazy strategy
  
• becomes more significant as the checkpoint
  interval
• increases.

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Numerical Results (cont)

• Effect of failure rate

Log arrival rate 0.1
Recovery time 0.24s
Mobility rate 0.01
Checkpoint interval 1000s
Transmission ratio 0.1

• The higher the failure rate the
• higher the recovery probability.

• As the failure rate increases the difference
• between the Eager and Lazy mobility handoff
• strategies becomes less significant.

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Failure Recoverability vs. Cost Tradeoff Analysis

• Tradeoff Eager strategy spends less time for a
  failure recovery, but much more time for
  maintaining checkpoint and logs than Lazy
  strategy.
• Objective identify a condition under which the
  recovery probability gained by Eager is most
  effective considering the cost invested for
  maintenance.

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Failure Recoverability vs. Cost Tradeoff Analysis

• Failure Recoverability versus Cost Ratio the
  slope of the recovery probability gained versus
  the cost invested.
• Cost invested by Eager

Number of checkpoints before failure
Number of moves crossing boundary during a
checkpoint period
Number of log entries between two consecutive
moves
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Failure Recoverability vs. Cost Tradeoff Analysis

• Cost invested by Lazy
• Cp communication cost for setting up the link.

• There exists a best checkpoint interval
• under which the Eager strategy is most
• cost-effective over the Lazy strategy.

• The best cost-effective checkpoint
• interval for the eager strategy increases
• as the recovery time increases.

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Conclusion and Future Research

• Conclusion
• Closed-form expressions for the failure recovery
  time distribution for both Eager and Lazy handoff
  strategies.
• Extensive numerical analysis on the effect of
  model parameters like log arrival rate, mobility
  rate, failure rate, checkpoint interval.
• Analysis the tradeoff involved between cost
  requested to maintain the checkpoints and logs
  and the recovery cost.
• Future research
• Using more sophisticated probabilistic model
  (SPN)
• Analysis more other checkpoint strategies

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Thank you