Double Middleware-based Mobile Data Service Jinsuo Zhang CISE Department University of Florida April 2002

Double Middleware-based Mobile Data Service

Jinsuo Zhang

CISE DepartmentUniversity of Florida

April 2002

Outline

• Introduction

• Double Middleware-based Architecture

• Automatic Data Hoarding

• Data Management & Consistency Control

• Heterogeneity Support

• Mobile Network Adaptation

• Summary & Future Work

History of Data Management

Monitor File System Network

File SystemMobile File

Service

Location Transparency

Name Transparency

Hierarchy

Name Transparency ?

Current Computation Model

InterNet

Challenges

Data AvailabilityAutomatic Hoarding

What, When, Where, Who, Why, How

Data ConsistencyHeterogeneous

CommunicationData Content

Mobile Network Adaptation

Motivation• Data Access From Anywhere at Any Time

– Data access in disconnection, weak connection and strong connection mode

• Device Independence– laptop, PDA,…

• Heterogeneity Support– Communication– Data content

Contribution• A New Architecture & Implementation• Filtering Mechanism & a New Hybrid Priority-

based Algorithm• XML-based Protocol• Asynchronous Consistency Model• Network Log Optimization• Incremental-based Weak Connection Adaptation• Simulation-based & Live Experiment Validation

Trace Collecting Period Footprint (Number of Files)

Trace 1 63 days 8k

Trace 2 62 days 8k

Trace 3 232 days 37k

Trace 4 132 days 100k

Trace 5 61 days 4k

Trace Information

Outline

• Introduction• Double Middleware-based Architecture• Automatic Data Hoarding• Data Management & Consistency Control• Heterogeneity Support• Mobile Network Adaptation• Summary & Future Work

Double Middleware-based Architecture

Inter-Net

F-MEM

r

r

Meta-Data

Server

Data Server

AbiWord vi

Operating System (Linux)

MS Word Visual Studio

Operating System (Windows)

M-MEM

M-MEM

Mobile Data Normal Data

Managed by both Host FS and MFS Managed only by Host FS

Retire

Role of Data

Publish/Import

Data Propagation

MH 1 MH 3 MH 4

MDSS

…… ……

Publish

MH 2

Import

Synchronization

Mobile Client Model

Logic Layer of File System

Physical Layer of File System

Application

User Space

Kernel Space

M-MEM

MFS Extension

MFS Utility

AnalyzerCache

ManagerData

Synchronizer…

M-MEM Responsibility

• Observe File Access Pattern• Decide Active Files On-the-Fly• Publish/Import files• Cache Management• Data Synchronization• Heterogeneity Support• Mobile Network Adaptation

M-MEM Workflow

Analyzer

MD Agent

File Event

Cache Manager

Filtering

Event Queue

Piggybacked Message

Write

Synchronizer

Non-WriteEvent

Optimizer

HTTP/SMTP/POP3

Scheduler

AdaptorNetwork Adaptor

Messenger

Input Event Queue

XML Protocol Parser

Output Event Queue

Request Interpreter

Authentication

Input Decoder

F-MEM

Data Server

Meta-Data Server

F-MEM Architecture

Output Packager

Request

Reply

System Summary

Dimension Our solution

Mobile Data Spectrum Any File in Supported OS

Data Selection Automatic

Application Transparency Transparent

Conservative/Optimistic Optimistic

Client/Server or Peer-to-Peer Hybrid

Immediate/delayed propagation Delayed

Push/Pull Model Hybrid Push/Pull

Replication Granularity Per-File

Replacement Policy Hybrid Priority

Updated Data Shipping Incremental Update

Outline

• Introduction







File Selection Workflow

Hooks in OS Kernel

User’s Profile in Server

Hoarding List

FilterFile access event AnalyzerFiltered event

Mobile Computer

Hoard Instruction

Hooks on Operating System

• Linux– Modified Linux Kernel– Introduce a Pseudo char-Driver as Bridge between

Kernel & Analyzer.

• Windows (95,98,ME,NT & 2000)– Introduce a Filter Device Driver to Intercept File

Access Event (DDK)– Forward Event to User-space Analyzer

• CE.Net by Ajay• Real World Problem

– Translation– Kernel-Application Communication


Hooks in OS Kernel


Hoarding List


Mobile Computer

Hoard Instruction

Location Distribution

0%

20%

40%

60%

80%

100%

System/Software Package Files Other Files

Trace 1 Trace 2 Trace 3 Trace 4 Trace 5 Average

Program Access Distribution

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

Number of Program (ordered by number of accesses)

Per

cent

age

of F

ile A

cces

s (%

)


Filtering Mechanism• Filter Types:

– Path Based Filter• /tmp,/etc,/usr/bin,/usr/lib,/dev,$HOME/.pine, …• /WinNT, /Program files

– Program Base Filter• Find, daemon, service task, virus tool,……

– Extension Name Based Filter• *.bak, *.tmp, *.old, *.swp, …

– File Type Based Filter• Pipe, device

– Time Based Filter• Backup, scan virus

– Derive Based Filter• *.c-> *.o, *.tex->*.dvi,*.ps

– Meta-info Based Filter• Size, Date, Permission, Ownership……

Trace Interpreter

MFS Extension

Operating System

Kernel Space

M-MEM Utilities

X Disabled

Simulation Methodology

User Space

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Non-Filtered

Filtered Out


Effectiveness of Filters

*Left bar: Unique Files. Right bar: Access

0

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0 10 20 30 40 50 60 70

Day

Num

ber

of U

niqu

e Fi

les

W/o FilterW/ Filter

Daily Working Set for Trace 1

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Day

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ber

of U

niq

ue F

iles

w/o Filterw/ Filter


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of U

niqu

e Fi

les

w/o Filter w/ Filter


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0 20 40 60 80 100 120 140

w/o Filterw/ Filter


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0 10 20 30 40 50 60 70

Day

Num

ber

of U

niqu

e Fi

les

w/o Filterw/ Filter



Hooks in OS Kernel


Hoarding List


Mobile Computer

Hoard Instruction

Observations (1 of 2)

0%

20%

40%

60%

80%

100%

Per

cen

tag

e o

f U

niq

ue

File

s

<= 1min <= 10min <= 1 hour <= 1 day >1day


Left bar: Non-filtered, Right bar: Filtered

0%

10%20%

30%40%

50%

60%70%

80%90%

100%

Pe

rce

nta

ge

of

Un

iqu

e F

iles

Freq=1 Freq=2 Freq=3 Freq=4 Freq>=5


Observations (2 of 2)

Left bar: Non-filtered, Right bar: Filtered

Hybrid Priority-based Algorithm

F (t, f, a) = 1 F1(t) + 2 F2(f) + 3 F3(a)

• F1(<current time>) = H0 – <aging parameter>

* (<current time> – last access time)

• F2(freq) = FA * freq

• F3(<active period>) = AA * <active period>

> H0 ? H0 : AA * <active period>

Algorithm Analysis

• Property 1: If F (t, f1, a1) > F (t, f2, a2), then for >

t, F (, f1, a1) > F (, f2, a2)

Property 1 means if two files are ordered by the hybrid priority and no file is touched since ordering, then the order is always kept.

• Property 2: The file list ordered by the hybrid priority need not be updated between any two file access intervals.

• Property 3: If one file in the file list is accessed, the order after this file in the file list still holds.

Hybrid Priority-based Algorithm

1. Records history information, reset when newly inserted.2. Dynamic just-in-time re-computing3. Binary insertion, complexity O(log(n))

1 2 3 4 5 6 7 8 9 10

Header Tail (existing file) (example) Tail (new file)

Bigger HP Smaller HP

10

20

30

40

50

60

70

80

20 30 40 50 60

Cache Size (number of files)

Hit

Ra

tio

(%

)

OPTHPLRU

Hit Ratio for Trace 1

35

40

45

50

55

60

65

70

20 30 40 50 60


Hit

Rat

io (%

)

OPTHPLRU


20

30

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20 30 40 50 60


Hit R

atio

(%)

OPTHPLRU


Outline

• Introduction







Data Management• Distributed Management

– Naming:URI– Version Control– Timestamp

• Data Spectrum• Role Change• Automatic Selection, Publish, Importing,

Consistency Maintenance

Data Representation in MDSS

Meta-Data Server (Apache Xindice)

Data Server

Mobile User

URI

Mobile Profile

URI1URIVersion

URI2

URI

Version

Replica Descriptor

Data 1

Data 2

Data

……

……

……

2. Update Propagation

1. Update Detection

4. Piggybacked Notification of Data Staleness

5. Refresh Request

6. Delta Data

Consistency Model

3. Buffer Notification

MDSS

Outline• Introduction







Comm. Between M-MEM and F-MEM

Network

Message Transport Agent

HTTP/SMTP/POP3

XML-based Protocol

Mobile Message Adaptor

XML Command

Message Transport Agent

XML-based Protocol

Mobile Message Adaptor

• Message-based,Asynchronous, Durable, Reliable• XML-based• File granularity, incremental based

Optimized XML Command

XML Communication Protocol

• File Management– Publish

– Import

– Retire

– Delete

– Rename

• User Management– PublicKeyReq– Login– Logout– Profile

• Consistency Maintenance– Update– Refresh

A Publish Example<?xml version="1.0"?><MobileDataMessage>

<OPERATOR>PUBLISH

</OPERATOR><FileInfo>

<URI> mfs://mymachine/mypath/myname.dat </URI><MODIFYTIME> 12:34:56 01/02/2000 </MODIFYTIME><SIZE> 12345 </SIZE><ACCESS>

<OWNER> somebody </OWNER><GROUP> somegroup </GROUP><ACCESSATTRIBUTE>rwxrwxrwx</ACCESSATTRIBUTE>

<ACCESS><VERSION> 1 </VERSION>

<FileInfo><AGENTINFO>

<ID>M-MEM 1.0</ID><HOSTOS> Linux </HOSTOS>

</AGENTINFO></MobileDataMessage>

Outline

• Introduction







Mobile Network Adaptation

• Hoarding

• Filtering Mechanism

• Working Set Locality

• Log Optimization

• Incremental Update/Hoarding

0

10

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30

40

50

60

70

80

90

100

0 20 40 60 80 100 120 140 160 180 200 220

Day

Rela

tive D

aily W

ork

ing

Set

Overl

ap

vs. P

revio

us D

ay (

%)

Locality for Trace 3

Locality for Trace 4

0

10

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5060

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100

0 10 20 30 40 50 60 70 80 90 100 110 120 130

Day

Rel

ativ

e D

aily

Wo

rkin

g S

et

Ove

rlap

vs.

Pre

vio

us

Day

(%

)

Trembling Phenomenon

Publish APublish BRetire APublish XRetire BPublish YRetire XPublish ARetire YPublish BRetire APublish URetire BPublish VRetire UPublish ARetire VPublish B

Publish APublish B

File Access Sequence: ABXYABUVAB

Publish APublish BPublish XPublish YRetire XPublish URetire YPublish V

Publish window size =4 Publish window size =2

0

1000

2000

3000

4000

5000

6000

7000

20 100 200 300 400 500 600 700

Publish Window Size (# of files)

Num

ber o

f Pub

lish

Req

uest

s

Trembling for Trace 3

Trembling for Trace 4

5000

7000

9000

11000

13000

15000

17000

19000

21000

23000

25000

20 100 200 300 400 500 600 700

Publish Window Size (number of files)

Nu

mb

er o

f P

ub

lish

Req

ues

t

0102030405060708090

100

0 60 120 180

File Access Interval (Seconds)

Acc

umul

ativ

e Pe

rcen

tage

of I

nter

-re

fere

nce

Inte

rval

(%)

Trace 2Trace 3

Trace 5

Trace 1

Trace 4

Inter Access Interval

0

1000

2000

3000

4000

5000

6000

7000

20 30 40 50 60 70 80 90 100

Publish Window Size (number of files)

Num

ber

of P

ublis

h R

eque

sts

No Delay

Delay 3min

Log Optimization for trace 3

0

5000

10000

15000

20000

25000

20 30 40 50 60 70 80 90 100

Publish Window Size

Nu

mb

er

of

Pu

bli

sh

Re

qu

es

ts Nodelay

Dealy 3min

Log Optimization for trace 4

Incremental Update/Hoarding Design

Method

F-MEM

Versioned File Manager

Server End

M-MEM

Versioned File Manager

Mobile Host

Client FS Network

1. Version control2. Versioned File Archive

M-MEM + NistNETFMEM + NistNET D-Link Router

Experiment Environment

Workload

Redhat 7.1 Distribution RedHat 7.2 Distribution

Version Size (Bytes)

Number of files

Version Size (Bytes)

Number of files

Apache 1.3.19 8.9M 752 1.3.20 9.3M 773

Bash 2.04 8.2M 731 2.05 8.5M 761

Glade 0.5.9 8.9M 549 0.6.2 10.8M 598

Groff 1.16.1 7.7M 668 1.17.2 7.9M 654

GNU Spell 32.6 6.3M 446 33.7 7.4M 507

Workload Introduction

0

5

10

15

20

25

30

35

Apache Bash Glade Groff Spell AvgPer

cen

tag

e o

f Net

wo

rk T

raff

ic

Rel

ativ

e to

Val

ue

Sh

ipp

ing

Network Traffic

300

600

900

1200

1500

4KB 5KB 6KB 7KB 8KB 9KB 10KB

Bandwidth (1KB=1024 Bytes)

ReI

nte

gra

tio

n T

ime

(Sec

on

ds)

Value ShippingIncremental

Apache

Bash

300

600

900

1200

1500



ReI

nte

gra

tio

n T

ime

(Sec

on

ds)


600

900

1200

1500

1800

2100

2400



ReI

nte

gra

tio

n T

ime

(Sec

on

ds)


Glade

Groff

300

600

900

1200

1500



ReI

nte

gra

tio

n T

ime

(Sec

on

ds)


GNU Spell

600

900

1200

1500

1800

2100



ReI

nte

gra

tio

n T

ime

(Sec

on

ds)


Outline• Introduction



• Data Management & Consistency



• Summary

Summary• A New Architecture & Implementation

– Linux & Windows

– Xindice Native XML DB

– Libxml XML Parser

– C/C++/STL, ~20K Lines

• Filtering Mechanism & a New Hybrid Priority-based Algorithm

• XML-based Protocol

• Asynchronous Consistency Model

• Network Log Optimization

• Incremental-based Weak Connection Adaptation

• Simulation-based & Live Experiment Validation

Questions

?

Documents

Double Middleware-based Mobile Data Service Jinsuo Zhang CISE Department University of Florida April 2002