Which is to say the distributed network matters as much as the renewable sources. From Generate Electricity Everywhere:

Problem Establishing local-scale power near end users ranks high on everyone’s spec list for Grid 2.0. That’s one reason Obama’s stimulus plan contains a grant that will reimburse property owners for 30 percent of the cost of a solar energy system. But utilities—former monopolies, after all—are reluctant to give up control over their antique, accident-prone grid. And people with enough rooftop real estate to squeeze out serious juice balk at the hassle.

Solution Create a new class of energy service providers that act as middlemen between power companies and large commercial facilities with big rooftops. For instance, SunEdison builds and maintains solar plants on the rooftops of operations like Wal-Mart, Whole Foods, and Kohl’s in eight states. It’s a win-win arrangement: Electric companies get a trusted partner in power generation, and businesses get green energy at a fixed, competitive rate—without additional investment. The secret sauce isn’t photovoltaic panels; it’s the networking gear, sensors, and software that let a SunEdison control room in California manage hundreds of solar sites cost-effectively. And that means it’s suited for scaling up. Says Mark Culpepper, a veteran of Cisco Systems who is now CTO of SunEdison: “Generating power anywhere you can fit a panel totally changes the dynamic of the energy market.”

Zero Geography reports on a real-time game using GPS devices which has – for our purposes, interesting applications for coordinating SAR or other response efforts. From Zero Geography: GPS Real-World Gaming in Hybrid Space.

A real-time, multiplayer, GPS game for mobiles is being played out in the real-world. The game, played by groups of four or five people, uses a one kilometer radius around any point on Earth to delineate spatial extents in which three or four chasers try to capture one runner. Each one of the players is tracked via a GPS phone and their coordinates are mashed onto a map that they can all see. The only twist that that the runner is always allowed to view the map, whilst the chasers only have access to the map every six minutes. The game is a fascinating way to roll elements of the physical and virtual together into an adrenaline-pumped experience.

Zero Geography is a brilliant blog about matters geographic by a person, persons, or entity named Mark Graham, who is otherwise reticent about identity or contact information. Check it out.

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”

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.

For those unfamiliar with Manhattan geography, Manhattan is much longer on its roughly North-South axis than it is on its East-West axis, although the island is narrower at its southern edge. (And it turns out to be harder to quickly locate a map showing the entire island than one would think).

Map of Manhattan - via Mappery.com

The current (and possibly next, or mayor-for-life) Michael Bloomberg has proposed that we make the East-West bus routes free, as they don’t function particularly well, the streets get congested, and – people are then tempted to use taxis – which merely exacerbates the entire situation.

Subways? We’ve only got two streets – 42nd and 11rth – which have subway routes which go directly across.

Every major east-west street clogs regularly. So is this a good idea, or not?

It’s a good idea, no question, viewed in isolation. And, in fact, it’s probably one of the best “wedges” we can use to unclog traffic in Manhattan.

Here’s the problem: while there are certainly people who are not affluent who will avail themselves of this free service, many if not most of these routes also run into the most afluent areas not just of the city, but of the nation, and the world.

The median value of owner-occupied homes for the entire county is $1,000,001 (2008  estimate); the median household income (2007) was $63,704. Link to census data for New York County, New York (Manhattan).

The comparable national values are $119,600¹ as the value of owner-occupied housing, and the median household income (2007) $50,740. Link to Census Data here.

In other words, we’ve got bottlenecks – and service deficits – elsewhere in our transit – and other – systems. Why start with bus routes which pass the Metropolitan Museum, F.A.A. Schwarz, Bergdorf Goodman, Carnegie Hall, Lincoln Center, and the railway stations which serve our out-of-city commuters who, at present, pay no commuter’s tax (they use municipal services during the day, but pay no municipal income tax)?

At the least, we can say it’s an odd way to build consensus. Here are links to some of the coverage of this issues:

Bloomberg Calls for Free Crosstown Buses – City Room Blog …(New York Times City Room Blog)

Mayor Proposes Free Crosstown Buses – NYTimes.com

Streetsblog New York City » Bloomberg Tests Free-Transit Waters

WNYC – The Brian Lehrer Show: Free Crosstown BusProposal

Free Crosstown Buses Proposed By Bloomberg

(Huffington Post)

More Manhattan Maps from the brilliant site Mappery.com. Plus – they’ve got more here..

Cross-posted in slightly different form on Caton Avenue

1. The latest national number is for 2000, rather than 2008; we concede that this marginally weakens our argument

… 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.

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.’

of the Creative Synthesis Collaborative posted this on June 2nd:

Another reminder of how effective government can be once it’s decided to be vigilant:

A construction crew working on an office building in Virginia in 2000 severed a fiber optic cable that wasn’t on anyone’s map. Apparently it was a ‘black line’ used for carrying secret intelligence data, according to sources who spoke recently with the Washington Post.

Within minutes of cutting the cable, three black SUV’s pulled up carrying men in suits who complained that their line was severed.

“The construction manager was shocked,” a worker told the Washington Post. “He had never seen a line get cut and people show up within seconds. Usually you’ve got to figure out whose line it is. To garner that kind of response that quickly was amazing.”

Construction Crew Severs Secret ‘Black Line.’

Fiddler on the Roof hd

Hard-Boiled hd

The Forbidden Kingdom ipod

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.

Nowadays, most people have these very distinct visual images of networks because in the last ten years they have become almost a part of pop culture. But social networks were studied in this kind of way beginning in the 1950s . . . . But all these were still very small-scale networks; networks of three people or 30 people — that kind of ballpark. But we are of course connected to each other through vastly larger, more complex, more beautiful networks of people. Networks of thousands of individuals, in fact. These networks are in a way living, breathing entities that reproduce, and that have a kind of memory. Things flow through them and they have a purpose and can achieve different things from what their constituent individuals can. And they are very difficult to understand.

This is how I began to think about social networks about seven years ago. At the time when I was thinking about this, I moved from the University of Chicago to Harvard, and was introduced to my colleague James Fowler, another social scientist, who was also beginning to think about different kinds of network problems from the perspective of political science. He was interested in problems of collective action – how groups of people are organized, how the action of one individual can influence the actions of other individuals. He was also interested in basic problems like altruism. Why would I be altruistic toward somebody else? What purpose does altruism serve? In fact, I think that altruism is a key predicate to the formation of social networks because it serves to stabilize social ties. If I were constantly violent towards other people, or never reciprocated anything good, the network would disintegrate, all the ties would be cut. Some level of altruism is required for networks to emerge.

So we can begin to think about combining a broad variety of ideas. Some stretch back to Plato, and thinking about well-ordered societies, the origins of good and evil, how people form collectives, how a state might be organized. In fact, we can begin to revisit ideas engaged by Rousseau and other philosophers on man in a state of nature. How can we transcend anarchy? Anarchy can be conceived of as a kind of social network phenomenon, and society and social order can also be conceived of as a social network phenomenon.

And what happens when we set out to deliberately create networks, rather than merely letting them develop?

For a useful model of how to organize a network in your neighborhood, check out 3 Steps.

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.

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.