Category Archives: Networks

WaPo: MIT team wins DARPA network challenge

Monica Hesse at the Washington Post reports that a team from MIT has won a DARPA prize for solving a distributed problem with a team/network that was partly ad hoc. TheDARPA Network Challengerequired teams to locate 10 weather balloons located around the country. From Hesse’s article, “Spy vs. spy on Facebook:”

In DARPA’s Network Challenge, tied to the 40-year anniversary of the Internet, the Department of Defense’s research arm placed 10 weather balloons in public places around the country. The first team to locate and submit the balloons’ correct geographic coordinates would get the cash prize. Ready, set, Twitter!

More than 4,000 teams participated. More than a few interesting things were revealed about the human psyche.

“It’s a huge game-theory simulation,” says Norman Whitaker of DARPA’s Transformational Convergence Technology Office. The only way to win the hunt was to find the location of every balloon, but a savvy participant would withhold his sighting until he’d amassed the other nine locations, or disseminated false information to throw others off the trail.

The winning team was spearheaded by Riley Crane, a postdoctoral research fellow at MIT’s Media Lab. MIT’s team set up an elaborate information-gathering pyramid. Each balloon was allotted $4,000. The first person to spot one would be awarded $2,000, while the people who referred them to the team would get smaller amounts based on where they fell on the info chain. Any leftover money, after payment to spotters and their friends, will be donated to charity.

Crane says that the team’s decision to spread the wealth was instrumental to its success, as it gave people an incentive to share good information, and a feeling of investment in the process. He was less interested in the monetary prize than in the potential for social research.

More articles by Monica Hesse here.

See also

our earlier post, “How to Break Networks”

(about Lt. Col. John Graham, then of the West Point faculty)

NB: It’s not clear how the Washington Post is archiving this article – it bears the html alternate title  MIT wins Defense Department balloon hunt, a test of social networking savvy. A minor example of the difficulties that come with technological change.

"How to Break a Network"

How to Break a Network –    about the work of Lieutenant Colonel John Graham studying insurgent (and other networks),was published by David Axe in 2007 – it’s no less relevant now:

this morning during presentations at the Association of the U.S. Army show in Fort Lauderdale, Florida, I was jolted out of a depressed stupor when an Army officer slapped a slide up on the projection screen that showed seemingly random points connected by lines: a classic representation of an international terrorist network or insurgent bombmaking cell. “Networks are hard to break,” Lieutenant Colonel John Graham announced. Then he smiled and said he was going to show us how.

Graham is a professor at West Point, where he teaches future officers the very thing he was showing us. The slide, he explained, was in fact a representation of his department: its instructors, students and partners in the Army. ”What I have,” he joked, “is a network at West Point working on networks.”And what have they learned since network studies got serious in the wake of 9/11? That there are three major vulnerabilities in networks:

1) Density nodes: people with many immediate connections, e.g. leaders

2) Centrality nodes: people with fewer immediate connections but who serve as crossroads in many relationships, e.g. financiers

3) Boundary spanners: people with few (maybe just two) connections but who span long gaps between chunks of the network, e.g. liaisons or messengers

Assuming your resources for attacking a network are limited — and in the real world, they always are — who do you hit? Graham asked. Using his own department as an example, he advocated killing just three of the dozens of members. Suprisingly, none were examples of density or centrality, since those were all situated in the meaty middle of the network. The network had enough redundant connections to quickly repair itself after their demise. What Graham wanted to do was hit the network where there were no redundancies, so all of his targets were boundary spanners. By taking out three spanners, Graham showed how you could isolate relatively homogenous chunks of the network, rendering it stupider and less adaptive than before.

Funny thing is, the spanners in Graham’s department’s network were mostly low-ranking members such as cadets. Just goes to show, when attacking networks, the most obvious targets aren’t always the most important.

From David Axe at War is Boring.

Addendum, June 23:

In covering the same conference for Government Computer News, Patience Wait reported in Network science is about more than computer systems

:

Government researchers in fields as diverse as biotechnology, ecosystems and behavioral science are looking for common patterns in the systems they study, to see if they can be applied to the development of robust complex networks, whether for computer systems or organizational structures.

A panel convened at the Association of the United States Army winter symposium yesterday discussed some of the parallels between biological systems, such as the circulatory, respiratory and central nervous systems in fish, the behaviors of proteins in bacteria and the organization of an airline’s flight routes, to show how their behaviors may be mirrored in the performance of networks.

Understanding biological, molecular and economic networks is necessary to design large, complex networks whose behaviors can be predicted in advance, said Jagadeesh Pamulapati, deputy director for laboratory management and assistant Army secretary for acquisition, logistics and technology.

The search centers on finding the answer to, ‘What are the underlying rules in common?’ he said. Can a common language be used to describe all these systems? Is there a mathematical formula to describe their behaviors and relationships?

Jaques Reifman, chief scientist for advanced technology and telemedicine in the Army’s Medical Research and Materiel Command, said that modeling protein interactions inside e. coli and plague bacteria is a form of comparing networks to understand ‘why in two related viruses, sharing more than 50 percent of proteins, one’s more virulent, more deadly, than the other.’

Reifman offered the theory that proteins can be judged for ‘essentiality’ based on how many connections they make with other proteins, and these hub proteins are more likely to be centrally located within the network of interactions.

‘I study fish because it’s the data we can get,’ said Lt. Col. John Graham, assistant professor for behavior sciences and leadership at West Point. Humans are resistant to providing access to their e-mail traffic, for instance, to allow the generation of very large datasets for study. But the understanding of networks is critical, he said, because ‘the bad guys are getting good at network science.’

Terrible Problems with 911 Systems

9-1-1 Should Never Give Me A Busy Signal. By  Jason Kincaid at  TechCrunch.

Last night I got word that my parents had witnessed a tragic accident while driving in Northern California. I won’t get into the details, but suffice to say one person was killed and others were left bleeding, in various states of unconsciousness. Thank God my parents were not hurt in the accident, but they witnessed it first hand, as well as the disturbing aftermath.

Immediately after the accident, my parents and other witnesses began trying to dial 9-1-1. Attempt after attempt resulted in a busy signal. This isn’t unusual in the event of an emergency, as multiple dialers often tie up the lines to report the same incident. Except it seems that nobody managed to get through for far too long: emergency personal didn’t arrive for 20 minutes. The first officer to arrive at the scene said it took him two minutes to get there from the time he got the call. Which means that it took approximately 18 minutes for the news to reach him in the first place. Continue reading

Ekahau: Heat Mapper – free app for visualizing wifi networks

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Ekahau [pronounced eck-uh-how]Heat Mapper – freeware application from the Helsinki-founded but now multi-continental firm Ekahau – lets users visualize wi-fi coverage on a map or building diagram (which one needs – and which can be imported into Heat Mapper).What’s it useful for:

  • Visualize Wi-Fi networks
  • determine the physical reach of a given network
  • display access points -and analyze their combined coverage, and/or individual characteristics
  • identify security problems and open networks

Continue reading

Administration committed to rural connectivity

FDR with John Rankin (L) and George W. Norris (R), signing the Rural Electrification Act

Peter Pratt at Stimulating Broadband, persuasively places current Administration efforts in the historical context of the New Deal with respect to making sure that rural areas are not excluded or sold short in new communications technologies. Via Stimulating Broadband (excerpt):

USDA Releases Broadband Guidelines: Strong Hints at NOFA Terms

In a short 2 page document issued internally to its field offices 3 days ago, on June 9, the Rural Utilities Service of the US Department of Agriculture (RUS) has given several important hints at the structure and substance of the all-important federal broadband funding guidelines expected by July 1.

Critically, in one key area of procedural information, the document contradicts officially stated public information from both RUS and the National Information and Telecommunications Administration (NTIA) previously reported here at StimulatingBroadband.com.

The document, released to this publication late in the day yesterday, June 11, by a federal employee in advance of its posting on the RUS website is available via our posting to our open access document site (Scribd .PDF).

In defining the “Strategy” of the $2.5 billion broadband program to be administered by RUS, the document states, “RUS will offer grants, direct loans and loan / grant combo.” This confirms verbal information received by StimulatingBroadband.com from a RUS representative within the past week that the agency is attempting to gain the greatest leverage possible via the combination of grants and loans to the same applicants, where possible.

Policy Points Affirmed

“We are now clearly seeing strong indications of what RUS will be setting down in its first NOFA, due out by the first of July,” commented our colleague Liz Zucco, President of rural telecom grant consultancy MarketSYS USA of Canton, Georgia. Ms. Zucco refers to the much anticipated Notice(s) of Funding Availability which will be promulgated by NTIA and RUS, reportedly prior to July 1.

Link to full article

Dr. Nicholas Christakis on Social Networks

Excerpted from “Social Networks ,” by Nicholas Christakis on The Situationist Blog, which is a blog maintained by The Project on Law and Mind Sciences at Harvard Law School. The excerpt is long, but well worth reading. Let me first posit this question – why do some communities develop disaster-resilient networks and organizations – and others not?

In social networks, there is an interdigitation between the higher order structure and the lower order structure, which is remarkable, and which has been animating our research for the last five or ten years. I started by studying very simple dyadic networks. A pair of individuals is the simplest type of network one can imagine. And I became curious about networks and network effects in my capacity as a doctor who takes care of people who are terminally ill.

* * *

For example, one day I met with a pretty typical scenario: a woman who was dying and her daughter who was caring for her. The mother had been sick for quite a while and she had dementia. The daughter was exhausted from years of caring for her, and in the course of caring, she became so exhausted that her husband also became sick from his wife’s preoccupation with her mother. One day I got a call from the husband’s best friend, with his permission, to ask me about him. So here we have the following cascade: parent to daughter, daughter to husband, and husband to friend. That is four people — a cascade of effects through the network. And I became sort of obsessed with the notion that these little dyads of people could agglomerate to form larger structures.

Continue reading

Distributed Social Networking as Disaster Preparedness tool

Distributed Social Networking has immense potential as a disaster preparedness tool.  Particularly so if wireless mesh networks are part of our emergency communications systems – and if we assume that any likely emergency system in the United States will be, in most places, community-based rather than government-based. (There are, no question, some state and local governments which have effective systems in place. But FEMA: res ipsa loquitur). In that context we mention DiSo – a distributed social networking project which I found on Chris Messina’s site.

We think the formula – large network + actual local preparedness + redundant, resilient comms systems = equals network able to prepare, lobby, allocate resources and respond as needed. And, inevitably, build community en route.

Google to track disease outbreaks

Alexis Madrigal of ABCNews reports that Google – and its nonprofit branch, Google.org, will start tracking disease outbreaks.

A new website, HealthMap, addresses that challenge by siphoning up text from Google News, the World Health Organization and online discussion groups, then filtering it and boiling it down into mapped data that researchers — and the public — can use to track new disease outbreaks, region by region.

“There is so much information on the web about disease outbreaks but it’s obscured by garbage and noise,” said John Brownstein, a professor at Harvard Medical School, and co-founder of HealthMap.org. “The idea of HealthMap is to get filtered, valuable information to the public and public health community in one freely available resource.”

The site’s free accessibility could be particularly important in the developing world, where poor public health infrastructure and lack of money has handicapped epidemiological efforts. That’s a problem because those regions are exactly where scientists predict new and dangerous diseases are likely to emerge.

HealthMap goes beyond the standard mashup and is more like a small-scale implementation of the long-awaited semantic web. The site, which the researchers describe in the latest issue of open access PLoS Medicine, creates machine-readable public health information from the text indexed by Google News, World Health Organization updates and online listserv discussions

Researchers Track Disease With Google News, Google.org Money

Hub and Spoke Networks – why they’re insufficient for disaster preparedness

Just read a remarkable piece on Network Weaving about hub-and-spoke networks. From Connected Customers:

[The author, Valdis Krebs, had discussed attending a professional conference at a hotel]. The only negative with the event was the conference hotel’s awful WiFi service — and their response to it.

Hotels are used to dealing with disconnected customers — hotel guests who do not know each other. They can tell these guests anything. Since most guests do not talk to each other, nothing is verified, no action is coordinated.  In terms of social network analysis: the hotel staff spans structural holes between the guests — occupying the power position in the network. Below is a network map of the situation. The centralized hotel staff are shown by the blue node in the middle, while hotel guests are represented by the green nodes. The green nodes only talk to the blue node and not to each other.

When INSNA arrived, the hotel guests were no longer disconnected — many people in INSNA know each other and after initial greetings started to talk.

The conversation soon went to the lack of connectivity in the hotel — no one could get a connection out of the hotel to the internet. Not only did everyone discover they were having the same bad experience, but they discovered they were receiving the same lie from the hotel staff — “everything is fine, no one else is complaining”. Being lied to made “being disconnected” all the more infuriating.

Soon “emergent clusters” of INSNA members went to the front desk as small groups and started demanding better service — after all we were being charged for WiFi. The front desk manager became overwhelmed by the coordinated action and soon went into hiding and refused to talk about the topic. A network illustration of the connected INSNA hotel guests looks different. Because the green nodes are talking to each other and coordinating a strategy, the big blue node is now more constrained in it’s response, and ability to act.

There are lots of differences between these two structures: the latter structure looks more like Paul Baran’s description of a resilient network: redundant, decentralized. The first structure is entirely vulnerable to attack of the central node – and, under the circumstances Krebs describes, was incapable both of self-diagnosis and self-repair.

My apologies for not having the Paul Baran citations at hand – perhaps I’ll get an update in later – but for the nonce, am happy to send interested readers to Network Weaving; the proprietors also run OrgNet

, and make InFlow network analysis software.

I wonder, if we did a network analysis of survivors of, say Katrina, what connectedness characteristics matter.