phd defense

A Framework for Web Object Self-Preservation

A Ph.D. Defense

Chuck Cartledge30 May 2014

A warning from Jeff Rothenberg

“Digital Information Lasts Forever—Or Five Years, Whichever Comes First.”

Jeff Rothenberg, Ensuring the Longevity of Digital Information, Scientific American 272 (1995), 42 - 47.

A warning from William Arms

“Tomorrow we could see the National Library of Medicine abolished by Congress, Elsevier dismantled by a corporate raider, the Royal Society declared bankrupt, or the University of Michigan Press destroyed by a meteor. All are highly unlikely, but over a long period of time unlikely events will happen."

William Y. Arms, Preservation of Scientific Serials: Three Current Examples, Journal of Electronic Publishing 5 (1999), no. 2.

Overview

• Warnings• Preservation context• Research questions• Background and related work• Unsupervised Small-World– Emergent behavior– Graph theory– Preservation

• Demonstration• Questions and answers

Preservation in an analog age

• Benign neglect– Don’t touch– Keep away from sunshine– Keep away from moisture– Keep away from insects

• Last for hundreds of years

Josie McClure picture taken Feb 30, 1907 at Poteau, I.T. Fifteen years of age When this was taken weighed 140 lbs.

Preservation in a digital age

• Constant use– Use often– Exposure to lots of things– Make lots of copies– Monitor the integrity

• Last for ??? unknown years

• This is a Brave New World

Google image search, 31 March 2014, about 91,700,000 results (0.84 seconds)

Everything has a lifespan

• Exponential growth of digital artifacts

• Representing increasing portion of personal and cultural heritage

• Short human lifetime to manage data

• Potentially, short institutional life time

• Need to preserve artifacts beyond human lifespan and institutions that create and house artifacts

Dissertation, section 1.3

Research questions

• Can web objects (WOs) be constructed to outlive the people and institutions that created them?

• Can we leverage aspects of naturally occurring networks and group behavior for preservation?

A WO is a digital object that lives on the Web. A WO is a fundamental element in this dissertation.

Unsupervised Small-World (USW) is at the nexus of multiple disciplines

Mathematical structures used to

model pairwise relations between

objects

Ensuring that digital information

of continuing value remains accessible and

usable

Movement of the inanimate

Shifting gears

Focusing on emergent behavior

Emergent behavior: model• Craig Reynolds – basis of herd

and flock behavior in computer animations– 3 rules

• Collision avoidance• Velocity matching• Flock centering

– No central control, everything based on local knowledge only

• Simple rules– Complex behavior– Emergent behavior Craig W. Reynolds, Computer Animation with Scripts and

Actors, ACM SIGGRAPH, vol. 16, ACM, 1982, pp. 289 - 296. Images http://www.red3d.com/cwr/boids/ Flock centering

Velocity matching

Collision avoidance

Emergent behavior: communication

• Need to know what my neighbors are doing

• Need to tell neighbors what I am doing

• A school of fish do not have a Dagon that controls them

Shifting gears

Focusing on preservation

Preservation: primitives

William Y. Arms, Digital Libraries, The MIT Press, December 1999

png png pngReplication Emulation

tiff eps bmpMigration

Preservation: OAIS model• Provides standard

model and terminology for archival systems

• Terms of interest– Submission

Information Package

– Ingest– Data

Management– Archival Storage– Access– Dissemination

Information Package Council of the Consultative Committee for Space Data Systems (CCSDS), Reference Model for an Open

Archival Information System (OAIS), Tech. report, Consultive Committee for Space Data Systems 650.0-M-2, Magenta Book, 2012.

Carl Lagoze, Herbert Van de Sompel, Pete Johnston, Michael Nelson, Robert Sanderson, and Simeon Warner, ORE User Guide - Resource Map Implementation in Atom, Tech. report, Open Archives Initiative, 2004.

Shifting gears

Focusing on graph theory

Graph theory: definitions

• Graph: G = (V,E)• Graph can be connected or

disconnected• Some graph metrics work only

with connected graphs and not with disconnected graphs– Clustering coefficient (C(G))– Average path length (L(G))– Degree distribution

Reka Albert and Albert-Laszlo Barabasi, Statistical Mechanics of Complex Networks, Reviews of Modern Physics 74 (2002), no. 1, 47.

Graph theory: Watts and Strogatz small-world

Duncan J. Watts and Steven H. Strogatz, Collective dynamics of `small world' networks, Nature 393 (1998), 440 - 442.

Stanley Milgram, The Small-World Problem, Psychology Today 2 (1967), no. 1, 60 - 67.

Small-world graphs are common

Actual Random graph

Nodes Edges C(G) L(G) C(G) L(G)WECC 4941 6594 0.0801 18.99 0.00054 8.7

C. elegans

248 511 0.21 2.87 0.05 2.62

Email 148 ~500,000 0.44 2.25 0.11 2.0

Ake J Holmgren, Using Graph Models to Analyze the Vulnerability of Electric Power Networks, Risk Analysis 26 (2006), no. 4, 955 - 969.

Lav R Varshney, Beth L Chen, Eric Paniagua, David H Hall, and Dmitri B Chklovskii, Structural Properties of the Caenorhabditis elegans Neuronal Network, PLoS computational biology 7 (2011), no. 2, e1001066.

Shinako Matsuyama and Takao Terano, Analyzing the ENRON Communication Network Using Agent-Based Simulation, Journal of Networks 3 (2008), no. 7.

West Elect. Coord. Council Enron

e-mail

Small-world: high C(G) and low L(G)

• The ubiquitous presence of small-world graphs points to something inherently “correct” and desirable about them.

Symbol Meaning

k Degree

n Order of the graph

Dissertation, section 5.2.3

USW is at the nexus of multiple disciplines

Creation of small-world

graphs that are robust and

resilient

Meet fundamental requirements of replication, migration, and

data management

WO’s use of emergent

behavior to create, monitor,

and optimize the USW system

Euclidean geometry• To draw a straight line from any point to

any point.• To produce [extend] a finite straight line

continuously in a straight line.• To describe a circle with any center and

distance [radius].• That all right angles are equal to one

another.• That, if a straight line falling on two straight

lines make the interior angles on the same side less than two right angles, the two straight lines, if produced indefinitely, meet on that side on which are the angles less than the two right angles.

The sum of angles A, B, and C is equal to 180 degrees

Euclid of Alexandria, The Elements, Alexandria, 300 BCE.

Non-Euclidean geometries• Non-Euclidean geometry

– To draw a straight line from any point to any point.

– To produce [extend] a finite straight line continuously in a straight line.

– To describe a circle with any center and distance [radius].

– That all right angles are equal to one another.– That, if a straight line falling on two straight

lines make the interior angles on the same side less than two right angles, the two straight lines, if produced indefinitely, meet on that side on which are the angles less than the two right angles.

• Spherical geometry– Two lines at right angles to the same line can

meet– Triangles can have 180 to 540 degrees– Circles are straight lines

Digital library world• Digital libraries

– The technical framework exists within a legal and social framework

– Understanding of digital library concepts is hampered by terminology

– The underlying architecture should be separate from the content stored in the library

– Names and identifiers are the basic building block for the digital library

– Digital library objects are more than collections of bits

– The digital library object that is used is different from the stored object

– Repositories must look after the information they hold

– Users want intellectual works, not digital objects

• Basic digital library tenets

Robert Kahn and Robert Wilensky, A Framework for Distributed Digital Object Services, International Journal on Digital Libraries 6 (2006), no. 2, 115 - 123.

William Y. Arms, Key Concepts in the Architecture of the Digital Library, D-Lib Magazine 1 (1995), no. 1.

Digital library worlds of possibilities

• Digital libraries– The technical framework exists within a legal and

social framework– Understanding of digital library concepts is hampered

by terminology– The underlying architecture should be separate from

the content stored in the library– Names and identifiers are the basic building block for

the digital library– Digital library objects are more than collections of

bits– The digital library object that is used is different from

the stored object– Repositories must look after the information they

hold– Users want intellectual works, not digital objects

What if there were no repositories?

“No Repositories” → USW

• No global knowledge– No omnipotent

enforcer– No omnipresent

monitor• Opportunistic

preservation• Self-describing

Web Objects

USW contributions

USW WO “friendship” links • WOs have

“friendship” links to other WOs

• Different than HTML navigational links

Dissertation, Chapter 6

USW WO “families”

A family is a set of copies of the same WO

USW hosts Family members live on different hosts Host #1

Host #2

Host #3 Dissertation, Chapter 6

Shifting gears

Focus on emergent behavior

USW interpretation of flocking

Flock centering

Velocity matching

Collision avoidance

Craig Reynolds’ “boids” USW interpretation

Each WO has a unique URI

Matching number of copies/family members

Move with friends to new hosts

Building a USW graph

• Graph exploration ( )b

• Choosing connections

• Detecting loss

WOs wandering in the USW graph

• Wandering WO is “introduced” to an existing WO

• If a connection is not made, then an attempt is made to another existing WO

• Process is repeated until a connection is made

• No global knowledge– No omnipotent

enforcer– No omnipresent

monitor• No repositories

USW friend selection process

• Selection from possible sets– WOset: WOs connected to candidate WO– visitedSet: WOs that the wandering WO has explored– toBeVisitedSet: WOs that the wandering WO has

discovered• Selection approaches

– Random from visitedSetUtoBeVisitedSet – FIFO from visitedSetUtoBeVisitedSet – LIFO from visitedSetUtoBeVisitedSet – Preferentially attach to WOset then random for remaining

Dissertation section 6.7.5

Comparing USW to random graphs

Shifting gears

Focus on graph theory

Robustness of USW graphs

• Definition: able to continue when damaged

• Attack vs. failure– Intentional vs. random

• Component selection– Vertex– Edge

• Selection attribute– Degree– Betweeness

• Attribute value– High– Low

• Attack profile notation: A{D|E|V}{H|L}

Sample graph

Charles L. Cartledge and Michael L. Nelson, Connectivity Damage to a Graph by the Removal of an Edge or Vertex, Tech. report, arXiv 1103.3075, ODU CS Dept.

Different attack profiles selections

AEH AEL AVH

ADLAVL ADH

Four attacks using AEL profile

Deletion #1. Deletion #2.

Deletion #3. Deletion #4.

Our damage vs. Albert, Jeong, and Barabasi’s damage

s = Reka Albert, Hawoong Jeong, and Albert-Laszlo Barabasi, Error and Attack Tolerance of Complex Networks, Nature 406 (2000), no. 6794, 378 - 382.

50 … 5 20 … 20

16 … 1 10 … 10

Measuring damage

• Desired characteristics– Different framgentation cases result

in different values– Useful without additional graph

state information

Dissertation Appendix D

Local and global AE* damage

Global A{DV}H damage (100 nodes)

• 100 node graph• Execution time: ~36

hours• Attacker has total

knowledge of the graph

• Attacker has unrestricted resources to damage the graph

• Results:– Small-world the

most connected is not the most valuable

– Random and scale-free degreeness does not make a difference

Attack profile efficacy on sample graph

Attack profile Attacks efficacy

AEdge High The core of the graph 1.43

AEdge Low The periphery of the graph 1.00

AVertex High The core of the graph 1.42

AVertex Low The periphery of the graph 1.00

ADegree High The core of the graph 1.40

ADegree Low The periphery of the graph 1.00

• If the attacker's goal is to disconnect the graph by repeated use of the same attack profile, then the most effective profiles in order are: AEH , AVH , and ADH.

• HTTP/HTML does not support AE* attack profiles Dissertation, section 5.6.6

Detecting loss of family members

• Each “active maintainer” WO checks its family’s status– Check family member

accessibility– Check friend accessibility

• If family member is lost, use friends to select candidate host

• If too few candidate hosts, use friends to explore and discover new hosts

Shifting gears

Focus on preservation

When to make family members?

• What is a copy?• Who makes the copies?• How many to make? Answer:

defined by originating domain– 0 to start– Soft lower limit (csoft)

– Hard upper limit (chard) • Where to make them?

– Distributed across known hosts– Too many or too few hosts

• When to make them?

Norman Paskin, On Making and Identifying a Copy, D-Lib Magazine 9 (2003), no. 1. Henry M. Gladney and John L. Bennett, What Do We Mean by Authentic? What's the

Real McCoy?, D-Lib Magazine 9 (2003), no. 7/8.

USW preservation definitions• Hierarchy of family WOs

– Progenitor – initial WO– Copies – more recent WO copies– Each WO is timestamped with creation time

• WO roles– Active maintainer – eldest WO charged with

making copies and related housekeeping– Passive maintainer – all other WOs

• Order of precedence– If progenitor is accessible then it is the active

maintainer– If declared active maintainer is accessible then it is

the active maintainer– Otherwise, WO declares itself active maintainer

• If family is disconnected then multiple active maintainers are possible until reconnection then the eldest WO declares itself active maintainer

Progenitor

Copies

Dissertation, Appendix A

Active and passive maintenance activities

Active

Passive

Active Active

PassivePassive

• Active maintainer (the WO with earliest timestamp) – currently charged with making copies and related housekeeping

• Passive maintainer – all other WOs

XCopy declares

Itself a

ctive maintainer

ProgenitorIs lost

Progenitorreturns

Progenitordeclares

act. as copy.

Progenitor is lostActive

Passive

Active Active

PassivePassive

• Active maintainer – currently charged with making copies and related housekeeping

XCopy declares

Itself a

ctive maintainer

ProgenitorIs lost

Progenitorreturns

Progenitordeclares

act. as copy.

A new active maintainerActive

Passive

Active Active

PassivePassive

XCopy declares

Itself a

ctive maintainer

ProgenitorIs lost

Progenitorreturns

Progenitordeclares

act. as copy.

Progenitor returns and assumes active maintainer role

Active

Passive

Active Active

PassivePassive

XCopy declares

Itself a

ctive maintainer

ProgenitorIs lost

Progenitorreturns

Progenitordeclares

act. as copy.

Progenitor has made copies

Copydisconnected

Copydeclares

activeCopiescreated

Replacementcreated

Excess copies Excess deleted

A copy is disconnected from the family

Copydisconnected

Copydeclares

activeCopiescreated

Replacementcreated

Two active maintainers make copies

Copydisconnected

Copydeclares

activeCopiescreated

Replacementcreated

Disconnected copy is reconnected to the progenitor

Copydisconnected

Copydeclares

activeCopiescreated

Replacementcreated

Family has too many copies

Copydisconnected

Copydeclares

activeCopiescreated

Replacementcreated

• Copy management policies– Active: explicit removal– Passive: “natural attrition”

• Equivalent of Reynolds’ velocity matching, making and monitoring copies

USW copying policies

• Least aggressive – one at a time to chard

• Moderately aggressive – as quickly as possible to csoft and then one at a time chard

• Most aggressive – as quickly as possible to chard

• Different results59

WOs preservation status Hosts utilization statusNone

< Csoft

Csoft <= N < Chard

N == Chard

< 25% < 75%

< 50 % > 75%

Dissertation, section 6.7.4

Least aggressive (t = 1)

A full YouTube video is available at: http://youtu.be/sHJGYphqtK4

Least aggressive (final)• Results

– System stabilized

– Host capacity limited

– Some WOs without any copies

– Some hosts unused

• “Least aggressive” is not an effective policy

Which policy to choose?• Moderately aggressive results

in an additional 18% of WOs meeting their preservation goals and makes more efficient use of limited host resources sooner

• Most aggressive results in almost the same percentage of WOs meeting their goals, but places a strain on the host resources

Charles L. Cartledge and Michael L. Nelson, When Should I Make Preservation Copies of Myself?, arXiv preprint arXiv:1202.4185 (2012).

Make new family members on new hosts

• Spreading copies across hosts increases the WO’s preservation likelihood

• Learn about new hosts from friends

Dissertation, Appendix A

Reynolds’ flock

centering

Move with friends to new hosts

Crowd sourcing of family member creation

• “Everyone is a curator …”– Crowd sourced activity– Unscheduled– Willing to wait a long time

• Enlist humans in creation and maintenance – opposite of benign neglect

Frank McCown, Michael L. Nelson, and Herbert Van de Sompel, Everyone is a Curator: Human-Assisted Preservation for ORE Aggregations, Proceedings of the DigCCurr 2009 (2009).

USW simulation vs. implementation

USW Theory HTTP/HTML reality

Communications Instantaneous Asynchronous

Edges Bidirectional Directional

Temporal effects None Inconsistences

Some WO reference implementation details

Sawood Alam, HTTP Mailbox - Asynchronous RESTful Communication, Master's thesis, Old Dominion University, Norfolk, VA, 2013.

Carl Lagoze, Herbert Van de Sompel, Pete Johnston, Michael Nelson, Robert Sanderson, and Simeon Warner, ORE User Guide - Resource Map Implementation in Atom, Tech. report, Open Archives Initiative, 2004.

Sawood Alam, Charles L. Cartledge, and Michael L. Nelson, Support for Various HTTP Methods on the Web, Tech. Report arXiv:1405.2330 (2014).

WO memory: simulated via “edit” service

Direct WO to WO communication: simulated via the HTTP Mailbox

Demonstration of the reference implementation

1. Selection of a web page to be preserved2. Creation of a WO from the web page3. Adding the WO to an existing USW graph

a. Pages copied from flickr.com, arXiv.org, radiolab.org, and gutenburg.org

b. All pages instrumented to become USW WOs

4. Creating preservation copies5. Detecting that a copy was lost6. Creating a replacement copy

USW contributions

Expanded graph theory by creating an algorithm that creates small-world graphs based on locally collected data (chapter 6)

Developed a new way to quantify damage in connected and disconnected graphs (section 5.2)

Developed techniques to optimize when and where to create preservation copies (section 5.5)

Developed techniques to achieve emergent behavior in WOs (section 6.2)

Backup slides

Preserve Me Viz! with new connections

• New friend connections

• New copy locations

Preserve Me “Basic” on a copy• Differences between

active and passive maintainers.

• Active maintainer is responsible for making copies.

• Passive maintainer sends alerts to the active maintainer

• Passive maintainer may assume active maintainer role if active is not available.

A USW instrumented splash page

…<link rel="resourcemap" type="application/atom+xml;type=entry" href="http://arxiv.cs.odu.edu/rems/arxiv-0704-3647v1.xml" /><link rel="aggregation" href="http://arxiv.cs.odu.edu/rems/arxiv-0704-3647v1.xml#aggregation" /><script src="http://www.cs.odu.edu/~salam/wsdl/uswdo/work/preserveme.js"></script>…

USW algorithm popup• Written in

JavaScript• Relies on domain

services– Copy -> creates

copy of a WO– Edit -> update own

REM• Uses

communications mechanism based on Sawood Alam’s master’s thesis

USW Preservation: copies (1 of 2)

• WO copies are not bit by bit identical to the original WO

• REsource Map (REM) points to a resource– Point to the “essence” of the

original– Point to local copies of the

resources– Can be used to recreate the

“essence” of the original• Resource has two attributes:

– Size– Update frequency

USW Preservation: copies (2 of 2)

Watts Stogratz small-world growth

Graph theory: random graph

Graph theory: scale free graph

Graph theory: lattice graph

Graph theory: Watts and Strogatz small-world graph

Comparing graphs

• Small-world graphs occur in natural and man made systems

• Small-world graphs are robust• How to algorithmically and

incrementally create small-world graphs?

Symbol Meaning

K Degree

<k> Average degree

N Order of the graph

Quantifying damage

• All graph components are not equally valuable

• How to identify most valuable

• Greedy repair is the obverse of identifying the most damaging component by identifying where to place the most beneficial component

Global normalized A{DV}H damage (40 - 750 nodes)

• Arithmetic series of possible solutions

• Early attacks are most effective, later attacks are incrementally effective

Long term growth analysis of USW graph

Based on the idea of a game

– Create the graph– Attack the graph using AVH

profile to remove 10% of the WOs

– Repair the graph, every surviving WO gets 2 opportunities (may be unsuccessful in repair attempts)

– Repeat until steady state

Possible paths in attack/repair game

Dissertation section 6.9

USW copies: famine to feast

Final states for copying policies and named conditions

Dissertation, Appendix H

Host capacity and WO desires

Famine FeastStraddle

Dissertation, Appendix H

Man-made small-world graph: Western Electricity Coordinating Council

Western Electricity Coordinating Council

Actual Random graph

Nodes Edges C(G) L(G) C(G) L(G)4941 6594 0.0801 18.99 0.00054 8.7

Ake J Holmgren, Using Graph Models to Analyze the Vulnerability of Electric Power Networks, Risk Analysis 26 (2006), no. 4, 955 - 969.

Naturally occurring small-world graph: C. elegans nematode

Caenorhabditis elegans

Actual Random graph

Nodes Edges C(G) L(G) C(G) L(G)248 511 0.21 2.87 0.05 2.62

Lav R Varshney, Beth L Chen, Eric Paniagua, David H Hall, and Dmitri B Chklovskii, Structural Properties of the Caenorhabditis elegans Neuronal Network, PLoS computational biology 7 (2011), no. 2, e1001066.

Organic small-world graph: Enron e-mail

Enron e-mail

Actual Random graph

Nodes Edges C(G) L(G) C(G) L(G)148 ~500,000 0.44 2.25 0.11 2.0

Shinako Matsuyama and Takao Terano, Analyzing the ENRON Communication Network Using Agent-Based Simulation, Journal of Networks 3 (2008), no. 7.

USW WO determines number of friends

• Number of connections

Symbol Meaning

ln, log2 Natural and base 2 logarithms

n Order of the discovered USW graph

g Simple scalar

Wandering activities

Dissertation, Appendix B

Active maintenance activities

Passive maintenance activities

Video URLs• USW video

– http://youtu.be/JnCMenp73YQ• Least Aggressive

– http://youtu.be/sHJGYphqtK4• Moderately Aggressive

– https://www.youtube.com/watch?v=pVI-VhPh7KQ• Most Aggressive

– https://www.youtube.com/watch?v=eIXz8Njh-QM• “Death Star” message histogram

– https://www.youtube.com/watch?v=X3EShyjFoc4• “Traditional” message histogram

– https://www.youtube.com/watch?v=9CcCup3Td-Q

Useful URIs• Flickr

– https://www.flickr.com/• Flickr on cs.odu.edu

– http://flickr.cs.odu.edu/• Adding image

– http://ws-dl-02.cs.odu.edu:10102/rem/generate/0.8/0.95/• Preseve Me! Viz

– http://www.cs.odu.edu/~salam/preserveme/viz.html• Delete REM

– http://ws-dl-02.cs.odu.edu:10102/rem/remove/http://flickr.cs.odu.edu/rems/flickr-24791103-N07-6661587389.xml

• Sawood on flickr– https://www.flickr.com/photos/122128913@N05

• Chuck on flickr– https://www.flickr.com/photos/24791103@N07/

• Court de Tomas De Torquemada on flickr– https://www.flickr.com/photos/24791103@N07/12867674403/

phd defense

flock behavior

group behavior

digital age

digital object

years of age

hundreds of years

unknown years

web object

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