On “Свой – Чужой” (Friend – Foe) paradigm and can we do as good as Nature?

I recently discovered that there is no accurate linguistic translation of the words “Свой” and “Чужой” from Russian to English. A purely semantical translation of “Свой” as “Friend” and  “Чужой” as “Foe” will only be correct in this particular paired context of “Свой – Чужой” as “Friend – Foe”, which sometimes delivers the same idea as “Us – Them”. I am sure there are many idioms that are also translated as the “whole dish” rather than by ingredients.

Anyway, I am not going to discuss here linguistic deficiencies of languages.

I’d rather talk about the concept or paradigm of “Свой – Чужой”, or equally “Friend – Foe”, that we can observe in Nature as a way of enabling living organisms to survive as species through many generations. WHY, for example, one particular species does not produce off-spring as a result of mating with another species? I am sure geneticists would have some “unquestionable’’ answers to this question. But, probably those answers will either be too trivial that they wouldn’t trigger any further interesting technological ideas, or too involved that they’d require studying this subject at length before seeing any connections with non-genetic engineering.  Can we hypothesize about this “Big WHY” by looking at the analogies in technology?

Of course another question crops up as why that particular WHY is interesting and maybe of some use to us engineers.

Well, one particular form of usefulness can be in trying to imitate this “Friend – Foe” paradigm in information processing systems to make them more secure. Basically, what we want to achieve is that if a particular activity has a certain “unique stamp of a kind’’ it can only interact safely and produce meaningful results with another activity of the same kind. As activities or their products lead to other activities we can think of some form of inheritance of the kind, as well as evolution in the form of creating a new kind with another “unique stamp of that kind”.

Look at this process as the physical process driven by energy. Energy enables the production of the offspring actions/data from the actions/data of the similar kind (Friends leading to Friends) or of the new kind, which is again protected from intrusion by the actions/data of others or Foes.

My conjecture is that the DNA mechanisms in Nature underpin this “Friend – Foe” paradigm by applying unique identifiers or DNA keys. In the world of information systems we generate keys (by prime generators and filters to separate them from the already used primes) and use encryption mechanisms. I guess that the future of electronic trading, if we want it to be survivable, is in making available energy flows generate masses of such unique keys and stamp our actions/data in their propagation.

Blockchains are probably already using this “Свой – Чужой” paradigm, do they? I am curious how mother Nature manages to generate these new DNA keys and not run out of energy. Probably there is a hidden reuse there? There should be balance between complexity and productivity somewhere.

IoT Technology Market 2017-2022 Prognosis

Quoting the recent Research and Markets store:

“Internet of Things Technology Market by Node Component (Processor, Sensor, Connectivity IC, Memory Device, and Logic Device), Network Infrastructure, Software Solution, Platform, Service, End-use Application and Geography – Global Forecast to 2022”

https://www.researchandmarkets.com/research/hld477/internet_of

IoT technology market expected to grow at a CAGR of 25.1% during the forecast period”

“The IoT technology market is expected to be valued at USD 639.74 billion by 2022, growing at a CAGR of 25.1% from 2017 to 2022. The growth of the IoT technology market can be attributed to the growing market of connected devices and increasing investments in the IoT industry. However, the lack of common communication protocols and communication standards across platforms, and high-power consumption by connected devices are hindering the growth of the IoT technology market.”

Our paper on Performance-Energy-Reliability interplay in Multi-core Scaling

Fei Xia, Ashur Rafiev, Ali Aalsaud, Mohammed Al-Hayanni, James Davis, Joshua Levine, Andrey Mokhov, Alexander Romanovsky, Rishad Shafik, Alex Yakovlev, Sheng Yang,  “Voltage, Throughput, Power, Reliability, and Multicore Scaling”, Computer, vol. 50, no. , pp. 34-45, August 2017, doi:10.1109/MC.2017.3001246

http://publications.computer.org/computer-magazine/2017/08/08/voltage-throughput-power-reliability-and-multicore-scaling/

This article studies the interplay between the performance, energy, and reliability (PER) of parallel-computing systems. It describes methods supporting the meaningful cross-platform analysis of this interplay. These methods lead to the PER software tool, which helps designers analyze, compare, and explore these properties. The web extra at https://youtu.be/aijVMM3Klfc illustrates the PER (performance, energy, and reliability) tool, expanding on the main engineering principles described in the article.

The PER tool can be found here:

www.async.org.uk/prime/PER/per.html

Open access paper version is here:

http://eprint.ncl.ac.uk/file_store/production/231220/F814D1A8-84ED-4996-A2C1-6BD3763E6456.pdf