Network Models for VR Applications

Interesting. thinking how this would be useful.  ....

CACMmag (@Communications of the ACM) Tweeted: #Mathematicians at @UniversityRudn have proposed a model for calculating the optimal parameters of a #5GNetwork for #VirtualReality applications. 

Mathematicians Propose 5G Network Model for VR Applications

By Russian Foundation for Basic Research, December 28, 2021

Mathematicians at Peoples' Friendship University of Russia have proposed a model for calculating the optimal parameters of a 5G network for virtual reality applications. It is simpler than but performs similar to state-of-the-art algorithms, the researchers say. Their results are published in Future Internet.

The proposed model is based on the example of virtual reality applications in which both multicast and unicast transmission schemes are combined. It allows one to estimate how many basestations are needed for a given quality of services provided. The algorithm makes it possible to obtain estimates no worse than alternative options using simulation modelling, but at the same time it is simpler, the researchers say.

"Our work provides a simple yet efficient algorithm for estimating the density of basestations needed to support a given density of VR devices and certain service quality parameters," says Daria Ostrikova, deputy director at the university's Institute of Applied Mathematics & Communications Technology.

From Russian Foundation for Basic Research

Fill the Data Moats?

Had never experienced the idea formally,   But after reading the description here understand the caution.   In how many domains can you assure having the data that forms a moat?  Perhaps by having a transitional algorithm to create it.

In Andreesson Horowitz:

The Empty Promise of Data Moats   by Martin Casado and Peter Lauten

Data has long been lauded as a competitive moat for companies, and that narrative’s been further hyped with the recent wave of AI startups. Network effects have been similarly promoted as a defensible force in building software businesses. So of course, we constantly hear about the combination of the two: “data network effects” (heck, we’ve talked about them at length ourselves).

But for enterprise startups — which is where we focus — we now wonder if there’s practical evidence of data network effects at all. Moreover, we suspect that even the more straightforward data scale effect has limited value as a defensive strategy for many companies. This isn’t just an academic question: It has important implications for where founders invest their time and resources. If you’re a startup that assumes the data you’re collecting equals a durable moat, then you might underinvest in the other areas that actually do increase the defensibility of your business long term (verticalization, go-to-market dominance, post-sales account control, the winning brand, etc).  ... " 

Key Look at the Meaning and Value of Blockchain

A favorite commenter of mine talks about the Blockchain.  Who we worked with at IBM.   With some great additional references.  Recommended read and reference.

Irving Wladawsky-Berger

A collection of observations, news and resources on the changing nature of innovation, technology, leadership, and other subjects.

Blockchain - the Networked Ecosystem is the Business

A few weeks ago I attended two back-to-back blockchain events in Toronto, - the Blockchain Research Institute All-Member Summit followed by the inaugural Blockchain Revolution Global conference.  Both events included a number of excellent talks and panels.  One of the presentations I particularly enjoyed was Scaling Blockchain for the Enterprise: Emerging Business Models, by IBM’s Andrew Martin and Smitha Soman.  Their presentation was based on their recently published report Building your blockchain advantage.

Since it first came to light a decade ago as the public, distributed ledger for the Bitcoin cryptocurrency, people have struggled to understand what blockchain is all about and what it’s truly good for.  This is not unusual for potentially transformative technologies in their early stages, as was the case with the Internet, and is still the case with AI.  The key question is whether blockchain has the potential to become a truly transformative technology over time.  With few exceptions, the answer is positive.

The essence of blockchain, notes the report, is that the unit of competition is the networked ecosystem, no longer a single enterprise.  “As blockchain adoption continues to gather momentum, organizations must approach their blockchain strategies with the same rigor and commitment as any other new and transformative strategies.  They can’t just fall back on prototypes alone.  They need to build a robust business case for blockchain that includes a fair incentive model to attract all the partners required for the success of their networks.”

Based on the analysis of over 25 blockchain networks in various stages of production across multiple industries and geographies, the report recommends that a company’s blockchain journey should evolve along three distinct stages: in search of value, - establishing a minimum value ecosystem;  getting to scale - creating value for an overall industry; and designing for new markets, - creating entirely new markets and business models.  Let me briefly discuss each of these stages..... "

Wireless Networking for Everywhere

What are the implications for new infrastructure of Wifi Networking Everywhere?

Enterprise Networks in Cisco Blog
Next Generation Wireless Infrastructure for Intent-based Networking Everywhere   By Anand Oswal

We’ve come to expect that our mobile devices are always connected to our favorite applications and data sources via Wi-Fi and LTE. As enterprises move more resources to multiple domains—data center, campus, branch edge, and mobile cellular—always-available wireless connectivity for devices is not just a convenience, it’s essential for keeping business operations running. With many business processes dependent on cloud data storage and processing, there is no tolerance for network latency, congestion, or down-time from maintenance upgrades. Waiting for applications to respond because of overloaded Access Points (APs) hinders employee productivity and degrades customers’ experience. The explosive growth of IoT devices is adding yet another layer of complexity for ubiquitous Wi-Fi connectivity at a scale that will only grow over time.

To meet the demand for always-available connectivity for business and personal applications—especially those using rich, visual content—organizations will rely on the new Wi-Fi 6 standard for campus and intra-branch connectivity and LTE/5G for mobile and field connections to enterprise resources. The new technologies and improvements in Wi-Fi 6 are one reason we re-engineered Cisco Aironet Access Points, creating the new Catalyst 9100ax AP and the Catalyst 9800 series wireless controllers with augmented Wi-Fi 6 capabilities to provide always-available wireless connectivity coupled with always on-guard security for a multi-domain world of data and applications. ... " 

Game Theory and Society

A favorite topic is how game theory can be made practical   We tried that and got little out of it beyond descriptive rather than prescriptive models.   Is this new approach useful beyond that?  Note especially regarding networks and social dynamics.

What game theory tells us about politics and society
Economist Alexander Wolitzky uses game theory to model institutions, networks, and social dynamics.   By Peter Dizikes | MIT News Office

Rubber Duckies for Disaster

Clever idea, disposable drop-in sensors being used to creat networks, understand and communicate ad-hoc in disaster conditions:

IBM is funding a fleet of rubber ducky-inspired gadgets to help disaster response   In Fast Company

The classic rubber ducky has many attributes. It’s cute, tough, and super buoyant. For one team of coders, those kid-friendly, bath-time qualities inspired something more: a disaster response startup that just won $200,000 and the chance for worldwide implementation through IBM’s inaugural Call for Code competition. Project Owl–an acronym that stands for “organization, whereabouts, and logistics”–will air-drop (likely via drone) their plucky “Clusterduck” armada into a disaster area ... 

The devices are small, hexagonal rubber balls that are waterproof, durable, and house mini-Wi-Fi relays, which can work together to create an ad hoc mobile network.

Each individual “ducklink” has a transmission range of about 400 meters. These signals overlap and connect to “Mamaducks,” larger long-range, low-power transmitters that knit all that coverage together. Smartphone and laptop users who join the Project Owl network will receive a pop-up allowing them to report to rescue workers their location, condition, and make clear what exactly they need to survive (that’s about as much data as the limited network will allow).

The data the network collects can then be used to create a dashboard that will allow first responders to better understand the scope of any scenario. This IBM Cloud-based system relies heavily on IBM’s Watson Studio and related Cloud APIs, along with data from the Weather Company, its forecasting service. When combined, the idea is to map and display many aspects of devastation, from where group resources might already be deployed, to ongoing and projected weather patterns. .... " 

Network of Brains

Voluntarily, I hope.  If this works trying to think the implications.

Technical reference:    Ref: arxiv.org/abs/1809.08632: BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains

The first “social network” of brains lets three people transmit thoughts to each other’s heads

BrainNet allows collaborative problem-solving using direct brain-to-brain communication.   by Emerging Technology from the arXiv    in TechnologyReview

The ability to send thoughts directly to another person’s brain is the stuff of science fiction. At least, it used to be.

These tools include electroencephalograms (EEGs) that record electrical activity in the brain and transcranial magnetic stimulation (TMS), which can transmit information into the brain.

In 2015, Andrea Stocco and his colleagues at the University of Washington in Seattle used this gear to connect two people via a brain-to-brain interface. The people then played a 20 questions–type game.

An obvious next step is to allow several people to join such a conversation, and today Stocco and his colleagues announced they have achieved this using a world-first brain-to-brain network. The network, which they call BrainNet, allows a small group to play a collaborative Tetris-like game. “Our results raise the possibility of future brain-to-brain interfaces that enable cooperative problem-solving by humans using a ‘social network’ of connected brains,” they say. .... "

Cisco Talks Network Assurance with AI

Specific term was new to me.  But I do like the link to the business, the process, the goals.  Are the intents the same as in a simulation model of the business process?   Risks?  Reading more. 

Machine Learning for Analytics and Assurance
By Duval Yeager in Cisco Blog.  Network operation based in the intent of the business.  Goals?  Intriguing.

We are hearing amazing stories from our Cisco customers as they roll out intelligent analytics and assurance solutions in the form of Cisco DNA Center, Meraki insight, and Network Assurance Engine (NAE). The comments are on the accuracy and complexity of the analytical models that we have built, based on 30 years of Cisco networking leadership. You can read my blog post on how analytics works here. But, the back story to this is the approach of Machine Learning. When we add advanced machine learning algorithms to these products, the intelligence and system flexibility will be even more exciting. Let me explain…

Assurance in IP networking uses an analytics engine to verify that the network is operating based on the intents of the business. These intents are translated based on the network policies that IT configured when the system was set-up. The resulting model drives the decisions that an assurance solution makes to improve the network. This model is very good at network optimization, but every network is different, and network utilization is always changing as we change the way we use it  .... " 

Predicting Epidemics (Bioterror?) from Cell Data

If you have followed this blog for a long time, we looked at how to predict epidemics through OTC drug purchase data.  Here is a related idea that might be combined with earlier work.  Links to Bioterror detection?  See the tag links below.

Using Cell Phone Data to Predict the Next Epidemic    Insight Kellogg.
Who you call is linked to where you travel, which dictates how viruses spread.

Based on the research of Pierre Deville, Chaoming Song, Nathan Eagle, Albert-László Barabási and Dashun Wang  ... Can big data about whom we call be used to predict how a viral epidemic will spread?  .... " 

Uber, Big Data and a Process Controlling Things

How Uber uses Spark and Hadoop.  Good useful piece in Datanami. instructive as to what is possible, with a well understood business process plan.    Good example of the interaction of things and data that others with this problem should examine.

  " .... Uber has the envious position of sitting at the junction of the digital and physical worlds. It commands an army of more than 100,000 drivers who are tasked with moving people and their stuff within a city or a town. That’s a relatively simple problem. But as Uber’s Head of Data Aaron Schildkrout recently said, that simplicity of its business plan gives Uber a huge opportunity to use data to essentially perfect its processes.

“It’s fundamentally a data problem,” Schildkrout says in a recording of a talk that Uber did with Databricks recently. “Because it is so simple, we sort of get to the essence of what it means to automate an experience like this. In a sense we’re trying to bring intelligence, in an automated and basically real time way, to cars that all over the globe right now that are carrying people around, to make that happen at this tremendous scale.”  ... " 

NASA Knowledge Discovery with Graph Analytics

We looked at problems similar to this a number of times.  How do you construct a semantic net based on internal knowledge, then use it to find new, innovative connections?  Turns out this is hard to do.    Similarity to the Discovery Advisor, previously mentioned?   What does creativity look like in such a network?

From DSC:    " .... NASA is using big data to make complex knowledge more readily available. Learn how graph visualization can help turn large corpus of documents into concrete insights. .... A database of lessons learned .... Even in a mature and knowledge-driven organization like NASA, finding an answer to a common business issue can be frustrating. Past surveys at NASA have shown that most people have trouble finding the answers they need or don’t get results in an easily usable way. When internal knowledge tools and processes come up short, Google is the number one go to solution. But what to do when even Google fails? ... "