We are running the Nano-Net 2008 Conference and Workshop on Nanosensors: Self-Organization and Swarm Robotics. Nano-Net 2008 runs from Sept. 14-16 in Boston this year. This will be an interactive event with some of the top researchers in the field in attendance. We will use this blog to extend discussions on the topic beyond the conference.
We are looking for relevant questions for discussions during the conference and the workshop. Conference attendees can use the free Wi-Fi in the conference facility to post questions, but we welcome questions from members who are unable to participate locally. We also hope that this discussion will continue after the conference ends.
Please respond to this posting a comment using the form at the bottom of this post. Answers to the questions posted here will be summarized and posted on the blog. You can direct your questions to specific individuals on the conference/workshop program as well. The programs can be accessed at:
http://www.albany.edu/selforganization
Conference/Workshop Theme: Nanosensors are slated to revolutionize several fields including medicine, harsh environment sensing and chip fabrication. Nanosensors however are small, weak, and fragile and lack the power to work independently due to limited power and communication range. However, by self-assembling into larger nano-structures or complex systems, they have the ability to exhibit sophisticated behavior. Nature exhibits several instances where seemingly simple organisms self-organize to exhibit sophisticated emergent behavior, also called swarm intelligence. For instance, an ant is quite a simple animal whose behavioral repertoire is limited from 10 to 40 elementary behaviors. However, in groups, they can exhibit sophisticated collective behavior where there are clear divisions of labor. Some ants collect food while others take care of the eggs, repair the nest, or protect the anthill against threats, while the queen lays the eggs. None of the animals grasp the big picture, but the entire colony collectively contributes to its success. It is necessary to understand such self-organization in the context of nanosensors to take advantage of the wide spectrum of applications where nanosensors can be deployed. These advancements will lead to realization of the concept of distributed self-organized colonies (swarms) of robots that can perform complex tasks that humans have difficulty in performing. This year’s workshop brings together the expertise of researchers from the fields of nano-robotics and swarm intelligence for the purposes of sharing and generating ideas that can bring together advances in these fields to improve nanosensor network research. The workshop will have specific deliverables.
~Sanjay Goel & Stephen Bush
CIFA Global Research 
This question is directed to the entire nano-sensors workshop:
What publicly available platforms exist for accurately simulating nanoscale systems?
This question is also directed to the entire nano-sensors workshop:
What is the current state of nano-scale wireless communications?
This question is also directed to the entire nano-sensors workshop:
What is the most efficient form of nanoscale communication?
This question is directed to the Model and Standards Session (Session 4):
What standards (e.g. IEEE) currently exist for nano-scale and quantum networking?
Here is my set of questions for the workshop/conference participants.
1. Self-organization is inherent in several complex systems with applications in social networking, sensor communication, social behavior of animals, etc. Is there a common theory that transcends different applications?
2. What can we learn from self-organization in other fields that can be applied to nanosensor self-organization?
Thanks,
Sanjay
This question is directed to the entire nano-sensors workshop:
To my knowledge most practical nanoscale fabrication falls into one of two camps -“on substrate” processing (such as used in fabricating MEMS sensors) and “in solution” processing (such as used in forming colloidal quantum dots used as biotags).
The “on substrate” approach is usually good for integrating with CMOS or other technology capable of providing some degree of “intelligence” but may lack the capability to form robotic structures on the nanoscale due to stiction and lithography limitations.
The “in solution” approach is good for engineering nanoscale particles and biostructures but may lack a methodology to add any form of intelligence to the manufactured nanostructures.
Which of these approaches are seen to more likely lead to the creation of “swarm robotics” (or is there a third alternative?)
This question is directed to the I paper of Session 1. In biologically inspired molecular communication system, can we at all decide and direct the direction of communication or by nature it will remain probabilistic or random? If it is expected to be random how with the given velocity parameters can we find the communication delay at this level?
This is also a related question to Network layers for molecular communication(Paper-2 or session -1, September 15, 2008). Do we have any proposed or studied models for noise and error injection into molecular communication? How the errors are detected (if at all) in biological systems and then corrected? Also in general do we look for point to point communication or switched communication requiring routing/switching?
A couple of questions for Paper – 3 “Hitting time analysis for stochastic communication”.
1. In what way the router switching fabric shall be affected while working in stochastic communication? How do we model them for simulation?
2. In a situation when we will have multiple data streams competing to get the links will emanate from different src-dst pairs, there may be a lot of replication of the flits and consequent power waste and also buffer occupancy. Will it be providing sufficiently attractive solution in such situations?
3. What are the environment parameters of the particles (n, alpha, pi, k)?
In answer to post no.5, as far as I know no noise models exist for such biochemical communication channels.
However, some recent works do address information capacity, namely Andrew Eckford’s work on nano-communication with brownian motion (https://wiki.cse.yorku.ca/user/aeckford/publications:start) and Tom Schneider’s work on infomration capacity of molecular machines (http://www-lecb.ncifcrf.gov/~toms/).
I also think that a switching function is achievable, such as the technique described in the paper, particularly if membrane nanotubes are used in these networks.
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Greetings
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New here. Wanted to say hello.
Thanks,
Andrew McFaul
Andy McFaul
Great information 🙂