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MSRC, Cambridge, UKDec 7, 2007
The Network is the Peopleor
The People are the Network(les gens sont le reseau)
[email protected]://www.cl.cam.ac.uk/
~jac22Computer Laboratory
University of Cambridge & Thomson Research Paris& LIP6
MSRC, Cambridge, UKDec 7, 2007
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.
MSRC, Cambridge, UKDec 7, 2007
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.
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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}
MSRC, Cambridge, UKDec 7, 2007
Experimental devices
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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).
MSRC, Cambridge, UKDec 7, 2007
Example: a typical pair
α
cutoff
MSRC, Cambridge, UKDec 7, 2007
Examples : Other pairs
MSRC, Cambridge, UKDec 7, 2007
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 well-connected well subsets
• Examples– 2-clique (connected components)– 3-clique (overlapping triangles)
• Overlapping feature
• Known Percolation threshold
MSRC, Cambridge, UKDec 7, 2007
K-clique Communities in Infocom06 Dataset
Barcelona Group (Spanish)
Paris Group A (French)
Paris Group B (French)Italian
K=5
MSRC, Cambridge, UKDec 7, 2007
Visualisation – Evolution of Node Connectivity http://www.cl.cam.ac.uk/~ey204/Haggle/Vis/mobility.html
MSRC, Cambridge, UKDec 7, 2007
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)
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
In-Group Centrality (Reality)
Group A
Group DGroup C
Group B
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
Lots of Real Social Groups
• Home, Family
• Work, Activities, Progress, Results, Admin
• Sport/Wellbeing
• Health, doctors etc
• Travel, Entertainment, shared interest
• Financial (pension schemes, saving, advice)
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
My LinkedIn Stats…
MSRC, Cambridge, UKDec 7, 2007
See Locale and Industry for me:-
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
But “sad” and geeky
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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? …
MSRC, Cambridge, UKDec 7, 2007
What do we Trust
• Users trust members of their tribe a lot more than strangers, but…
• To build a network, usually we want bi-directional “links”
• Are trust relationships associative, commutative, transitive, reflexive?
• Not in social relationships, usually:
MSRC, Cambridge, UKDec 7, 2007
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?
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
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”)
MSRC, Cambridge, UKDec 7, 2007
Thank you• Merci pour votre attention
• Questions?
• 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
MSRC, Cambridge, UKDec 7, 2007
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
MSRC, Cambridge, UKDec 7, 2007
et merci a CNRS et Thomson