Hear the Chain topology of a musical performance network.
First things first, this is an absolutely strange network to try and disassemble and reassemble for evaluation purpose. The social nuances behind musical performance, not to mention the tonal and rhythmic networks are rich enough to become someone’s area of dissertation. For this reason, I will not be describing every nuance of this network. However, most of my predictions were based around how the music changes as you switch around nodes and hubs of the live performance framework.
One thing that completely escaped my thoughts in the initial setup of this network is the logistics of a nodes comprised of people. Unlike computers, which are only somewhat reliable, humans operate not by procedure alone, but have a multitude of threads and other thoughts tangled in with their solitary task given by me to be a node.
For this reason, there were a variety of shortcomings and interesting outcomes that I did not anticipate directly, from the nodes as well as in the protocol of the network itself.
Here I will be amending to the description of my initial network I explained here.
Protocols
This particular area of my network was problematic, particularily because the protocol could not be enforced to the level I expected, for a variety of reasons. From the aspect of nodes, they (as human beings) were unreliable in terms of their ability to perform the actions specifically as the network was designed. Some of the nodes were even unable to be apart of the network at all, or were unwilling to be fully part of the network. This isn’t an attack on those nodes as much as a weakness in the network as a whole, and candidly a large part of the social dynamics of any musical group. The transport layer was problematic in a variety of ways, which I will describe below.
Transport
In the chain network topology, the physical network I put in place was insufficient for many reasons: mixers and audio equipment are not designed to chain musical instruments to many individuals. This is not common practice and therefore required a large amount of extra/wasteful equipment. If this network were to be made efficient, new tools would have to be developed specifically for this purpose. Also, transport was inefficient because the nodes needed to be completely isolated from each other except for their solitary source node and their connection to the node they were sourcing. Because of the lack of physical space as well as lack of transport in the form of long cables, there was a spill over the network, and nodes heard other information than they were designed to hear.
Contents
Contents even had issues, particularily the common issue in musical situations. Musicians could not hear the other musicians. Not only were they a random assortment of nodes that had never played together before, but their skill level was very diverse as well. Some of the instruments were not even hearable to the musician who was playing them, but only to the next person in the chain. This ability for call and response inside a singular node was an overseen problem that was not addressed with a few of the nodes. The results here are very interesting.
First of all, because certain nodes were without vital information, they simply attempted to mimic the node before them in the chain. For this reason, their information was intercepted by the next node in the chain as duplicate “spilled” information. The result was a section of the topology which cloned itself rather than producing new content. Other variations of this chain issue are explained below as I dig deeper.
Discussion
As I began explaining above, there were considerable holes in the physical and data transmission parts of this network, as well as problems within each individual nodes that lead to interesting results. The ability for each musician to hear him or herself is paramount, and some instruments did not have this feedback initially in place. Now, whether or not this is part of the network schema is arguable, but in this case, the network actually stole that feedback loop from the user, where the network itself could have providing that feedback loop but did not do so. The interesting effects that resulted from that, like the cloning of patterns for example, were worth it in the context of experimentation, but would frustrate a musician in a real performance situation.
Secondly, because the network’s physical layer was not air tight, it made it difficult for people to really isolate themselves and riff off each other. In conjunction with this issue, these musicians did not know each others styles and therefore didn’t have a reference predetermined in which to base their improvisation. For me, this is a hugely overlooked part of the network I intended to design. My initial thought revolved around the idea that random musicians, of any skill level and without context of each others abilities, would be able to perform better in a chain environment by only listening to one person rather than listening (and just as importantly, being listened to). This, in fact was flip-flopped in reality.
Less confident musicians, rather than hiding in the middle of a chain of musicians, would rather hide in a swarm of musicians, where instead of definetely being heard by one person, would less likely be heard if a part of a larger group that was blending and combining tone and rhythm.
Also, and lastly, the group was largely driven by the initial player in the chain. Not only did he set the pace continuously throughout the chain, but his node was conveniently first in the chain. He was resistant to changing his patterns much when the loop came back around to him. For this reason, he drove much of the group at the same pace throughout, rather than the overall chain of sound altering dynamically. An interesting potential side effect resolved from this. The person directly next in the chain to him eventually kept playing even though everyone else in the chain had stopped.
One person in the chain was eventually able to stop the entire chain, except for this musician and the person after him, who continued improvising off him. The only reason the chain did not begin again, was because of the musician who chose to stop playing and thereby stopped the chain from beginning again. This is an intriquing part of this network I’d like to explore in parallel systems.
WordPress database error: [Table 'grayfus_wordpress.wp_comments' doesn't exist]
SELECT COUNT(comment_ID) FROM wp_comments WHERE comment_post_ID = 18 AND comment_approved = '1';
October 20th, 2005
Proposal
Explore a network of musicians in live musical performace. Over the past two years, I’ve been exploring power structures in music. Executing successful live performance with other musicians is a rigorous, complex, and social network that has been in existence for hundreds of years. In typical applications of the past, a nested sub-nodal network has been the primary method for musical performance. The hierarchy of Composer, Conductor, Musician [, Sound Engineer], and Audience has been engrained in traditional music practice since before the founding of this country.
I am interested in how music as a network breaks down and can be reconfigured hierarchially. Although it’s ritual for musical performance to be structured hierarchially, how does this network work when the hierarchies are shifted? I would like to explore three potential network schemas, and explore their overall outcome in reference to each other.
Nested
This is the traditional topology from which musical performance is based. I will remove composers and conductors from the equation to simplify, yet this network is still strongly stacked. Strong rhythmic and harmonic instruments lead the charge, as other instruments follow along. There is a constant delivery of musical and non-musical information sent back and forth to make their content as coherent and connected as possible to each other.
This topology will be a control for comparison with the second and third performance structures.
Peer to Peer
A peer to peer system is somewhat visible in an elementary school band and/or choir practice. Each individual, still too innocent to realize the collective in which they are apart, does not consider the ramifications of playing at their own pace without strict rules and guidelines. In my exploration, I would give some additional rules to the musicians, making certain that rules and boundaries would need to be given so that they did not follow one dominant player or group of players.
Chain
This is the relationship I’m most interested in, and the concept of a network I was originally exploring in this context. What if each musician can hear only one other musician, and could only effectively be heard by one other musician, forming a chain of players?
The first player would effectively be the only dominant musician, having started an improvised piece of music that someone else chains off of. Eventually, at the end of the chain, the end musician would play content the first musician would then re-assemble their improvization to. The effect would be an infinite loop of content that is always evolving and changing.
Design and Description
8-10 musicians will be used in comparing these networks. Each musician will use one musical instrument throughout the process of exploring each of the three topologies, so exploration of overlap in content and repetition of data can be assessed.
Characteristics
The musicians will act as nodes in this network. Three potential protocols will be in place: spoken language, body language, and audio transfer through amplification. These protocols serve as the direct route of transport for the musicians as well. Contents of the network include musical information of broad scope, including meter, tonality, diatonic relevance, melodic and harmonic progression, phrasing and other compositional information, as well as visual or audible cueing and reference information. Musicians are given an logic address through their physical location in the network (ability to hear or see others) or through the timbre of their particular instrument. I will be exploring these characteristics in three different topologies: Nested (sub-node), Peer to Peer, and Chain.
Stack
Application: Musicians will send content through spoken or visual cues as well as through their particular instruments sound or lack thereof. Transmission: Primarily, this data will be sent over the visual and audible spectrum, but in certain topologies, musicians may be split up from each other, only able to hear one individual or small groups of individuals in closed context. Physical: Primarily, the transmission is sent directly from user to user over real-space, but in certain context will be delivered through audio amplification and distribution through line-level analog audio signal. This will consist of a small network of mixers or distribution amplifiers.
A view of the network schemas can be viewed here.
Predictions
My end goal is to effectively capture each of these scenarios and trace patterns from each, comparing and contrasting their strong and weak parts. My early hypothesis is based on my previous existence in this network.
The nested network group will find a groove in which they improvise rather easily, and although certain content may be lost between certain nodes in the network, the primary instruments will offer redundancy that will keep the group as a whole working together to create some sort of musical framework
The peer to peer group will initially have problems. No clear leaders being present, everyone is left to theselves to find their context for the musical content they are creating. Over time, this network schema will find ways in which to be individuals while still relying on other musicians. However, I think those musicians they are listening to will change as other musicians change what they are improvising. This will keep the peer to peer group’s musical content flowing and evolving, but with unexpected or organic results.
The chain group will be the most interesting. Without redundancy in this network, if one person in the chain sends their content incorrectly or incoherently, it will cause a chain reaction throughout the network. This will be particularly interesting as musicians become fatigued and do not perform to their fullest expectations.
My overall expectation revolves around two concepts: originality and reliability. Most likely, the chain group will be the most original of the three, followed by the peer to peer group, with the nested group last. In contrast, I think we’ll see that the nested group is the most reliable, followed by the peer to peer group, with the chain group being somewhat unreliable. The musical content of the three is so dependent on the musicians and the chosen instruments, I can only speculate to their overall quality of sound. I’m sure I’ll enjoy it, one way or another!
WordPress database error: [Table 'grayfus_wordpress.wp_comments' doesn't exist]
SELECT COUNT(comment_ID) FROM wp_comments WHERE comment_post_ID = 16 AND comment_approved = '1';
October 11th, 2005
– download the PDF –
Networks are typically an under the hood mechanism. Even more so in a place and time where we are still uncovering the very nature of networks in our everyday life. They are complicated, dedicated, and inconspicuous systems that can expand, react and sometimes even destroy. There are so many, that to compare is at first an exciting, and then somewhat daunting task. After many ponderings, two seemingly unrelated networks are my focus: Grain Farming/Production vs. Internet Networking (primary focus in local area networks in a home).
90% of my day consists of food and information consumption, so why not compare these infrastructures. Lets see how they size up to each other. First off, there’s an obvious context issue to address. For many users in these networks, the flow of content between “nodes” is in the reverse order. Farmers are in the business of delivering their freshly cut grain out to the public (or other places which I will get into later), whereas the user I’m focusing on in internet networking is the person receiving the content, or at least receiving the content to a higher frequency than sending it. For the purposes of my comparison, I want to make aware that contrast first and foremost.
Now, the farmer, call him Joe. Why a network? Well, there are many farmers in any given area. Why grain? For the sake of this discussion, grain has unique storing problems, and you’ll see how that applies shortly. So there’s a farmer, and he wants his freshly grown wheat on the shelves of a supermarket in one form or another. Better yet, he wants payment for the months and months of unpayed labor he and his particular workers have undertaken over the past 10 months. *At this point, the farmer has options. He can either join a co-op of farmers, who share space for their grain, he can acquire his own silos, or he can become incorporated with a larger entity/business that manages the grain for him. In the same vein, switch to Jane, the internet user. She’s an avid computer user, and has three computers. One of them is a laptop that’s wirelessly connected to the local area network through a hub. She also has a regular desktop computer, which is wired into the local area network through a switch. *Third, Jane has another desktop with special connection outside of the local area network, that runs into a dedicated line out of her apartment. In terms of initial connection to the internet, Jane’s computers are very similar to Joe’s choices for the delivery of his grain. Joe can choose which distribution he wishes to use, and there are benefits and disadvantages for both (which is also true for Jane).
*note: additional choices are available in both scenarios,
but for the sake of comparison these three give a general overview.
Varied in their content, these two networks explore cost, convenience, and speed. This is a major factor to both Joe and Jane. Jane may spend fifty dollars for a fast wireless connection that is bound by physical space (considering we’re talking about her wireless connection at home, not a random connection she finds at a cafe or down the street), one hundred dollars for a a wired connection that is much faster (one hundred dollars accounting for the added cost of wires if she travels farther than wireless connections offer), or she can spend anywhere from five hundred to a thousand dollars for a dedicated connection (normally reserved for server use), which would be substainsially faster but perhaps too fast in relation to the cost. Joe, on the same token, has three options which tax the cost, speed, convenience variables as well. First, Joe can work with an entity/business at the regional or national level. While being more flexible in a variety of ways (accounting, logistics, large scale distribution), this resembles Jane’s direct connection example in many ways. Simple, versatile, and the choice of many a farmer out there. Unfortunetely, like a direct connection, there are some disadvantages. First, remotely simple tasks become difficult. The large company sends giant freight trucks to gather grain from the local farmers, because this is a large scale business model. This doesn’t compute well with most farmers, which have combines that must empty their loads frequently. Also, big corporations are not in touch with the individual needs of Joe the way more localized co-ops are. In the same way, Jane’s simple local needs on the network are much more difficult. She isn’t connected to the local area network her wireless and wired connections share in the apartment. Rather, she has to find ways to tap back into that local area network, even though those physical systems might be right next door. Its red tape that mimics the muck that large businesses can dump on small farming families.
So, there are issues on one side of the equation. What about on the other side of the spectrum? Likewise, Joe’s investment in personal silos and a small fleet of versatile trucks that can easily reach combines in the field present problems also. Joe will spend a considerable amount of money on silos, which may well be very nearby and convenient for quick delivery of grain, but also add personal upkeep, not to mention liability. Improperly cut grain (which is defined as grain with a poor ratio of grain to weeds, and/or damp grain) can cause considerable damage to the other grain in the silo, and may even cause spontaneous combustion in a silo, burning down the entire storage facility and precious resources that were involved in building such storage. Also, his new fleet of small grain trucks require maintenance as well as constant logistics in staffing. In the same way, Jane’s wireless internet has a higher rate of failure, even to the local area network, including the other computers in her network. Not only that, but as a user of wireless communication, there’s the chance her transmission can be picked up by someone ready to grab her content and do something harmful with it, leaving her individual needs and security out of question. Joe has too much responsibility, and Jane potentially has too much data spilling out into others hands. This side of the equation has the opposite effect, too much to worry about and not enough payoff.
As with most things, the middle ground is where most people find peace. Wireless internet and personal farming solutions are both finding ways to enhance that infrastructure, and in time it will become more common practice, as the security of both become more concrete and the payoff is more evident. Until then, Joe works with his neighbors. They create a co-op, or use one thats been in existence in a long line of other farmers. They share silos, which are conveniently maintained by shared resources, and they define a protocol for grain which can be stored in said storehouses. It must have a certain quality ratio of grain to “pollutants”, and must also be of a certain dryness. The farmer is also given payment upon delivery of each truck’s wheat, which is weighed in before and after dumping, based on the quality and weight. This allows the farmer to better manage their investments in real time rather than rely on their own calculations or a large businesses estimations. Likewise, Jane’s wired connection is stable. Unless someone cuts the cable, and her cable runs into a switch, its much more difficult for someone outside of her local area network to break in and steal her data. With a switch, the data is sent directly to her computer and her computer only from the router, which also improves security from within the local area network. They cannot just grab it out of the air like an unsecured wireless connection. Also, she has the ability to access the local area network much more easily than a dedicated line computer would. Jane can also achieve faster internet rates using gigabit quality cable and protocols, which wireless cannot yet reach. This is a good payoff in the cost to speed ratio. Both Joe and Jane have moderately great solutions for getting their content where it needs to go, and a stable vehicle which can get it to the next location it needs to travel.
Now, beyond the silos, and beyond the routers, there’s an intense amount of infrastructures for both of these networks, which is also intriguing, but also out of the initial contact of Joe and Jane. Jane doesn’t care much about Seattle’s “backbone” servers, and Joe doesn’t much care about Russia’s import regulations, they just want their favorite web blog and their grain sold at market value respectively. Now, if the Seattle mainframe goes down, or the grain market takes a hit in the stock market (which they both have occasion to do), suddenly these large networks are called into question. On a day to day basis, its not these big networks, but smaller local networks that bring about interesting relationships.
When it comes right down to it, everyday people in non-technology based environments share the same turmoil and strife under the virtual “hood” of their profession as web-crawling-pajama-wearing tech-heads. Exposing where those connections and choices collide and form new meaningful relationships is the common thread that binds the lentils with the subject line.
–
WordPress database error: [Table 'grayfus_wordpress.wp_comments' doesn't exist]
SELECT COUNT(comment_ID) FROM wp_comments WHERE comment_post_ID = 7 AND comment_approved = '1';
September 22nd, 2005
