The Network is the People
or
The People are the Network
(les gens sont le reseau)
Jon.Crowcroft@cl.cam.ac.uk
http://www.cl.cam.ac.uk/~jac22
Computer Laboratory
University of Cambridge & Thomson
Research Paris& LIP6
Dec 7, 2007
MSRC, Cambridge, UK
Social Networks and Mobility
are only just starting to be
combined.
• Two boring ways to do this are:
– offering social network access on mobile device
(merely a matter of coping with reduced network
capacity and screen real estate, and somewhat
different interaction paradigms);
– making location services that are somewhat socially
aware (what used to be called "contextual computing").
• Studies of human mobility patterns reveal that
one can extract rich social structural information
directly from contact (co-location) distributions.
Dec 7, 2007
MSRC, Cambridge, UK
This talk in outline
• Thomson Labs: combine so-called traditional
(legacy) social network structures (friends of
friends on facebook or linkedin etc) with new
mobility information (contact of contact in
bluetooth or wifi encounters).
• Two uses of the combined information:
– expanding and subtly altering one's social net
(allowing for the somewhat different nature of static
references in online communities, from face-to-face
encounters in Real Life);
– using the social network (a priori, and learned, contacts
and interests and tags) for efficient dissemination of
information in wireless ad hoc communities.
Dec 7, 2007
MSRC, Cambridge, UK
Social Structures Vs Network Structures
• Community structures
– Social communities, i.e. affiliations
– Topologically cohesive groups or modules
• Centralities
– Social hubs, celebrities and postmen
– Betweenness, closeness, inference power,
centrality
• 1. Look at Structure of Human Social
Mobility experimentally
Dec 7, 2007
MSRC, Cambridge, UK
Experimental setup
• iMotes
– ARM processor
– Bluetooth radio
– 64k flash memory
• Bluetooth Inquiries
– 5 seconds every 2 minutes
– Log contact tuples:
• {MAC address, start time, end time}
Dec 7, 2007
MSRC, Cambridge, UK
Experimental devices
Dec 7, 2007
MSRC, Cambridge, UK
So we did a lot of experiments
• Mix of ours and other research groups:
–
–
–
–
Infocom conferences 05 and 06 (miami, barcelona)
In Cambridge (with 1st & 2nd yr undergrds)
Hong Kong (with High School, and random [people on street)
Plus others’ data
• from crawdad dbase @dartmouth, ucsd, toronto
• From MIT Reality Mining dataset
• Typical data set involves:
– 54 iMotes distributed, Experiment duration: 3 days
– 41 yielded useful data
– 11 with battery or packaging problem, 2 not returned
Dec 7, 2007
MSRC, Cambridge, UK
What we measure
• For a given pairs of nodes:
– contact times and inter-contact times.
Duration of the experiment
an inter-contact
a contact time
t
Dec 7, 2007
MSRC, Cambridge, UK
What we measure (cont’d)
• Distribution per event.
≠ seen at a random instant in time.
• Plot log-log distributions.
• We aggregate the data of different pairs.
(see the following slides).
Dec 7, 2007
MSRC, Cambridge, UK
Example: a typical pair
α
cutoff
Dec 7, 2007
MSRC, Cambridge, UK
Examples : Other pairs
Dec 7, 2007
MSRC, Cambridge, UK
K-clique Community Definition
•
•
Union of k-cliques reachable through a series of
adjacent k-cliques [Palla et al]
Adjacent k-cliques share k-1 nodes
Members in a community reachable through wellconnected well subsets
Examples
•
•
Overlapping feature
Known Percolation threshold
•
•
Dec 7, 2007
– 2-clique (connected components)
– 3-clique (overlapping triangles)
MSRC, Cambridge, UK
K-clique Communities in
Infocom06 Dataset
Italian
Paris Group A (French)
Paris Group B (French)
Barcelona Group
(Spanish)
K=5
Dec 7, 2007
MSRC, Cambridge, UK
Visualisation – Evolution of Node Connectivity
http://www.cl.cam.ac.uk/~ey204/Haggle/Vis/mobility.html
Dec 7, 2007
MSRC, Cambridge, UK
Other Community Detection Methodologies
• Betweenness [Newman04]
• Modularity [Newman06]
• Information theory[Rosvall06]
– Most literature is in social anthropology
– Some in physics (AS level topology and web
interconnect topology)
– Future is to look at social net (myspace,
linkedin, orkut, yahoo groups, facebook)
– And user contributed tags (del.icio.us, etc)
Dec 7, 2007
MSRC, Cambridge, UK
Centrality in Temporal Network
• Simulate flooding over the temporal graph
• Uniform source/destination and temporal
traffic distribution
–Count number of times each node would be on
shortest delay deliveries
–Higher the count, more central node
–Analogue to Freeman centrality
• Need to threshold over lifespan of “link” in
temporal graph
Dec 7, 2007
MSRC, Cambridge, UK
In-Group Centrality (Reality)
Dec 7, 2007
Group A
Group B
Group C
Group D
MSRC, Cambridge, UK
2. And those online societies…
• There’s a lot – you probably are on 1
– Hey, maybe you left several too
• Anyone remember Usenet
– Rec.*, Alt.* etc
– The Well and Bboards
Dec 7, 2007
MSRC, Cambridge, UK
Lots of Social Networks
• High Functionality
– Facebook, Myspace
– Content and applications shared as well as
links and interests
• Pure Discovery
– Linkedin, Orkut
– Mainly useful for finding work, Q&A etc
Dec 7, 2007
MSRC, Cambridge, UK
Lots of Real Social Groups
•
•
•
•
•
•
Dec 7, 2007
Home, Family
Work, Activities, Progress, Results, Admin
Sport/Wellbeing
Health, doctors etc
Travel, Entertainment, shared interest
Financial (pension schemes, saving,
advice)
MSRC, Cambridge, UK
Internet Based Systems
• Are large – Facebook cites 100s millions
– Are connected
– Serve some useful functions
– Are differentiated (by functions, content)
• Revenue can come from
– advertisement
– Or from spinoff activities
– Or just bundled by ISP (remember AOL online
and MiniTel
Dec 7, 2007
MSRC, Cambridge, UK
My LinkedIn Stats…
Dec 7, 2007
MSRC, Cambridge, UK
See Locale and Industry for me:-
Dec 7, 2007
MSRC, Cambridge, UK
Note two net characteristics
• Very high node degree
– 150 – is well known in sociology to be social group size
• Very fast discovery
– Within 1 month of being in Paris, already shows my
network
• Note this is on infrastructure/email/web based
social net where I get about 1 join request per
day
– Mobile net would automate these joins – see next
Dec 7, 2007
MSRC, Cambridge, UK
Mobile Social Nets
• Mobile social net tools/systems abound since recently
• First generation
• dodgeball
– Nokia sensor, and others centered on cellular providers
• Newer, trying to get into dating etc
–
–
–
–
aka aki
mobiluck
meetmoi
imity
• Very new:- immediately useful (save phone state etc)
– Mocospace
– mig33
– zyb
Dec 7, 2007
MSRC, Cambridge, UK
But “sad” and geeky
Dec 7, 2007
MSRC, Cambridge, UK
What can we use to Hook?
• Big Bug:
– contradiction between social people meet people in “reallife” (RL)
• and sad geeks, who inhabit virtual world:)
• Possible escape routes:
–
–
–
–
games (move from console to smart phone to console)
music (listen and create)
couch potatoe-able escape causes:
view sport via multiple viewpoints and discuss
• Other hooks (usefulness!):
– disasters (data loss, infrastructure down)
– cheap
– s/w distribution
Dec 7, 2007
MSRC, Cambridge, UK
Building Mobile Network
• Discover Common Locations (space)
– Familiar Strangers
• Fellow Commuters
– Use location service
• In network, or seperate
• Discover Common Friends by Activity (time)
– Friend of friend
• By exchange of address books
– Common interest
• subscription or del.icio.us tags in common
Dec 7, 2007
MSRC, Cambridge, UK
Content Distribution on Mobile
Network
• Use infrastructure
• GPRS/Edge/3G
– Or WiFi Hotspots
• Ad Hoc Networking
– MANET forward via others smart phones
• Delay Tolerant Networking
– Store, Carry, Forward
• In all these, need to know where humans
are and when
Dec 7, 2007
MSRC, Cambridge, UK
The people are the network
• The mobility of people is input to network design
– Either to place capacity for infrastructure,
– Or for setting up regular, or opportunistic forwarding
paths over users devices
– Need to distunguish between people who are social
butterflies (hub for idle chit chat/gossip)
• Meet lots of people
– and people who are central for forwarding a lot of
information
• Meet people and exchange a lot of data for them often
Dec 7, 2007
MSRC, Cambridge, UK
Problems
• Fear 
• Users fear:
– spam, loss of euros, loss of battery life, identity theft,
denial of service,
• Too many interrupts to life
– Too little privacy
• Does community (e.g. shared interest or locale)
help? …
Dec 7, 2007
MSRC, Cambridge, UK
What do we Trust
• Users trust members of their tribe a lot
more than strangers, but…
• To build a network, usually we want bidirectional “links”
• Are trust relationships associative,
commutative, transitive, reflexive?
• Not in social relationships, usually: 
Dec 7, 2007
MSRC, Cambridge, UK
Can we build incentives?
• Perhaps additional capacity (mutual
benefit) is enough?
– potential capacity for DTN use of multihop,
store-carry-forward much more than cellular 
– But delay highly unpredictable and possibly
hours or days (although we tolerate this for
email) 
– Can we enhance delay and trust with
infrastructure?
Dec 7, 2007
MSRC, Cambridge, UK
Use infrastructure to bootstrap
• Yes, infrastructure helps a lot 
– Can bootstrap social network from
infrastructure
– Can bootstrap payment and identity (SIM card
and cellular or WiFi contract) from
infrastructure
– Can use nodes with infrastructure access to
shortcut, and improve delay distributions
• Trade off against a cost
Dec 7, 2007
MSRC, Cambridge, UK
Could even monetize call time
• E.g. I swap carrying mp3s for you, for you
giving me minutes of voice call time on
(say) SFR or Vodafone
• I can ask infrastructure to help with
– Location service
– Channel/spectrum allocation for MANET/DTN
Users
– Proof of Identity
– Authenticating “currency” (a “mint”)
Dec 7, 2007
MSRC, Cambridge, UK
Thank you
• Merci pour votre attention
• Questions?
• Jon.Crowcroft@cl.cam.ac.uk
• Next slides show that we can build social networks in a
decentralized way
• Without any infrastructure –
• future work would include hybrid with infrastructure (to
boot, and to provide persistence) and garbage collection
Dec 7, 2007
MSRC, Cambridge, UK
More Future Work…
• Privacy and trust (including incentives
forwarding).
• Absolute location based, versus co-location
based forwarding
• Other layer social network based forwarding, e.g
• Content (url distance, or meta, e.g. del.icio.us
tag) based forwarding
• Myspace, Orkut, etc
Dec 7, 2007
MSRC, Cambridge, UK
Jon.Crowcroft@cl.cam.ac.uk
et merci a CNRS et Thomson
Dec 7, 2007
MSRC, Cambridge, UK