"Collaborative Business Models: Distributed Computing Business Model Modality"

(Area: Entrepreneurship, Innovation, Technology, Strategy, Collaboration)

(Reading Material "Advanced Collaboration Course: Collaborative Business Models and Strategy in the New Era", Hugo Céspedes A.)

Continuing with the "Collaborative Business Models" series, this time I will analyze the "Distributed Computing Collaborative Business Model modality".

Distributed Computing, or Distributed Processing, refers to the technique of linking multiple computer servers through a network in a cluster to share data and coordinate processing power. Such a cluster is known as a "Distributed System". Distributed Computing is a model for solving massive computing problems using a large number of organized computers embedded in a distributed telecommunications infrastructure. Distributed Computing is a computer model that allows large calculations to be made using thousands of "volunteer" computers (especially recommended when working with large volumes of data -Big Data-.

Distributed Computing offers advantages in terms of Scalability (through a "Scalable architecture"), Performance (through redundancy), and Profitability (through the use of low-cost commodity hardware).

As data volumes have skyrocketed and application performance demands have increased, Distributed Computing has become extremely common in Database and Application design. This is why it is especially valuable for "scaling" so that as data volumes grow, that additional load can be handled simply by adding more hardware to the system. Contrast this with traditional environments, which consist of powerful computing servers, where load growth must be handled by upgrading and replacing hardware.

"In Distributed Computing, multiple computer servers/computers are connected through a network to enable large workloads that take advantage of all available resources". This system is based on distributing the information through the internet through software, previously downloaded by the user to different computers, which solve the calculations and once they have the result, they send it to the server. This project, almost always in solidarity, distributes the information to be processed among thousands of volunteer computers in order to reach processing quotas that are often higher than those of super computers.

Within Distributed Computing, Cloud Computing, Grid Computing or Mesh Computing are usually considered as Distributed Computing modalities.

Cloud Computing uses Distributed Computing to provide customers with highly scalable and profitable infrastructure and platforms. Cloud providers typically offer capacity in the form of hosted services that can be accessed over the internet (Software as a Service -SaaS, Platform as a Service -PaaS-, Infrastructure as a Service -IaaS-).

For its part, Grid Computing is conceptually oriented towards the creation of a super computer with enormous computing power. However, computational tasks are not processed by one, but by many instances. Servers and personal computers can perform different tasks independently, so that resources can be accessed in a very flexible way. In general, participants make their computing skills available to a general project at night, when their technical infrastructure is used relatively little.

Distributed Computing in Cloud Computing.

The growth of Cloud Computing options and providers has made Distributed Computing even more accessible. While Cloud Computing instances themselves do not automatically enable Distributed Computing, there are many different types of Distributed Computing software that run in the cloud to take advantage of rapidly available computing resources.

In the past, organizations have relied on database administrators (DBAs) or technology providers to link computing resources across networks within and between data centers so that resources can be shared. Now, major cloud providers make it easy to add servers to a cluster for additional storage capacity or computing performance.

With the ease and speed with which new computing resources can be provisioned, Distributed Computing enables greater levels of agility when handling growing workloads. This enables "Elasticity", in which a group of computers can be easily expanded or contracted based on immediate workload requirements.

Distributed Computing versus Cloud Computing.

While Distributed Computing and Cloud Computing are used to process tasks, however, we must specify that Distributed Computing is used in Cloud Computing. Both involve massive computing infrastructures and their management. The concepts of Distributed Computing and Cloud Computing have been developed for the purpose of Distributed Computing, that is, "to compute an item over a large area, literally on computers that are separated by some means or another".

• Distributed Computing: It is a network in a computational model that has the ability to process large volumes of data with the help of a group of coordinated computers to solve a problem together. Computers are commonly linked using a WAN (wide area network that exists over a wide geographical area, where the modem sends and receives information from the internet through the WAN port). All systems can be connected to each other directly (peer-to-peer) or also use a scheduling system.
• Cloud Computing: Cloud Computing is a model for creating convenient, on-demand access via the Internet to a shared set of computing services (for example, networks, servers, storage, applications, and services), which can be quickly assigned and provisioned with a minimum of administrative management and supplier interaction. Therefore, Cloud Computing provides this facility which is flexible, easy to use with compatibility issues.

Types of Distributed Computing: a) Distributed Computing Systems and) Distributed Information Systems.

a) Distributed Computing Systems: Collection of physically separated computers connected to each other by a communications network, each machine has its hardware and software components.

b) Distributed Information Systems: Collection of physically separated and connected computers for data storage that can be together or distributed in different network machines.

Types of Cloud Computing Service: a) Private Cloud, b) Community Cloud, c) Public Cloud, d) Hybrid Cloud.

a) Private Cloud: The cloud infrastructure is operated solely by one organization. It can be managed by the organization itself or by a third party inside or outside the facilities.

b) Community Cloud: The cloud infrastructure is shared by various organizations and supports a specific community that shares certain affinities (for example, mission, security requirements, policies or objectives).

c) Public Cloud: The cloud infrastructure belongs to an organization that sells its services in the cloud, is available to the general public or to a large industrial group.

d) Hybrid Cloud: Cloud infrastructure is an aggregation of two or more types of clouds (private, community or public) which remain unique entities, but are united by standardized or proprietary technology.

Advantages of Distributed Computing: 1) Distributed Computing helps to distribute and divide the work in multiple computers; 2) When a fault occurs, the task does not stop, since another computer will take over the task, making this system more reliable; 3) There is full access to data and applications, since the system is located in the user's facilities; 4) Information can be worked on in storage systems created by the user; 5) An internal network can be created to access data in case of internet failure.

Advantages of Cloud Computing: 1) Cloud can be easily accessed from anywhere in the world. You just need to have internet connectivity; 2) It is cost effective and has fast data backup and restore. It also has automatic software updates; 3) It does not require a large initial investment; 4) You pay for the resources to be used, if you want more computing capacity, you pay only for what is used and the configurations do not have to be do users.

Key Advantages of Distributed Computing.

Distributed Computing makes all the computers in the cluster work together as if they were a single computer. The benefit of Distributed Computing is that "it can be assigned to the location or locations where possible, do it more efficiently". We can take as an example, Distributed Computing in a company, each office can organize and manipulate data to meet specific needs, as well as share the product with the rest of the organization. It also allows us to optimize equipment and improves the balance of processing within an application. The latter is of great importance, since in some applications there is simply not one machine that is capable of performing all the processing.

While there is some complexity to this multi-computer model, there are greater benefits around:

• Scalability: Distributed Computing clusters are easy to scale through a "scale-out architecture" in which higher loads can be handled simply by adding new hardware (instead of replacing existing hardware).
• Performance: Through parallelism in which each computer in the cluster simultaneously handles a subset of an overall task, the cluster can achieve high levels of performance through a divide-and-conquer approach.
• Resilience: Distributed Computing clusters typically copy or "replicate" data across all compute servers to ensure there is no single point of failure. If a computer fails, copies of the data on that computer are stored elsewhere so no data is lost.
• Profitability: Distributed Computing typically takes advantage of low-cost commodity hardware, making initial deployments and cluster expansions very inexpensive.

For those who wish to delve deeper into the topic of Distributed Computing (in a more technical way), I recommend the following video that lasts about 15 minutes on Youtube: "Distributed Systems | Distributed Computing Explained".

Applications and Examples of Distributed Computing.

SETI Project: The SETI Project was a pioneer in the field of Distributed Computing (it set the standards in the field of Distributed Computing as Voluntary Computing, in the field since 1999). Its objective was to search for extraterrestrial life by detecting their communications technology, looking for patterns that show intelligence in radio waves from space. The global power of all participating terminals has been enormous; specifically, a cumulative total of two million years of CPU time, around 50Terabytes -TB- of data and five million users have been obtained.

It was one of the first initiatives to offer a Distributed Computing client (which worked as a screen saver) that allowed the analysis of radio waves coming from the universe in search of Extraterrestrial Intelligence. The system basically worked by dividing the group of information, the data that was analyzed in the remote computer, and returned to the central computer, all over the internet. The files did not weigh more than 300 kb and with current internet connections, that occasional up-down traffic had no real impact on the user. The central computer recomposed all the pieces of the puzzle to complete the data and pass it on to the higher analysis unit. Thus, during the years of transition between Mac OS9 and Mac OSX, it was common to see the SETI screen saver on Mac desktops, either because of the geekiness inherent in SETI or because of the romance of the matter. A special feature of this project was the "resource saving strategy", where the evaluation software was only used in periods when users' computers were idle. After analyzing the signal, the results were sent to the headquarters in Berkeley (Open Infrastructure for Network Computing -BONIC-), today an initiative with similar objectives. There are now compatible projects in other universities and institutes around the world.

Globus Toolkit: In recent years, the grid has achieved the commitment of firms such as IBM, Platform Computing, Sun, SAS, Oracle, CA, EMC, NeApp and HP, which are adapting their offer to support the technology through their own developments and alliances. An example is the software licensing agreement between IBM and Univa, an open source grid software startup. Univa was founded in December 2004 by Steve Tuecke, Ian Foster and Carl Kesselman, the 1995 creators of the Globus Project (later renamed the Globus Alliance), from which the Globus Toolkit emerged.

The company's offer, which was preparing the launch of what would be its first commercial product (Univa Globus Enterprise), is based on commercial implementations of the kit, which includes software libraries and services to monitor, discover and manage resources, as well as data management, files and security. This grid computing model bears certain parallels with the development of Linux, with Globus Toolkit playing the role of open source operating system and Univa playing the role of distribution companies such as Red Hat or Novell's SuSE to create commercial solutions aimed at the world of the company.

However, after two decades of running the Globus Toolkit, it is no longer available as a distributed IT toolkit of Do-It-Yourself thinking, but its spirit lives on in a mature, full-featured, easy-to-use service. to use for research data management like Globus.org.

United Devices: Stands out in the world of Proprietary Code, one of the pioneer companies in grid products and services. Its objective is to develop programs that cover all kinds of areas of interest for companies and users, such as financial and biotechnology applications, and establish business models in which the computing power of other users is bought in order to solve different problems. ConGrid MP is much easier to adapt applications to the grid than using the Globus Toolkit, in addition to offering much more powerful services, although it has the disadvantage that it is not Open Source and therefore it is necessary to purchase the product.

United Devices Inc. would later be acquired by Univa (which would later be acquired by Altair)

Ethereum (Blockchain): Blockchain (or Distributed Accounting), is the technology that allows the reliable and safe realization of any type of transaction between two or more people without the need for intermediaries, through the Internet. Its introduction to the world was through the Bitcoin cryptocurrency, the first blockchain platform. Bitcoin was originally created as an electronic peer-to-peer payment system, which is why it is known as "digital money". Well, Ethereum works in a decentralized way through a virtual machine called Ethereum Virtual Machine (EVM). This machine executes intermediate code or bytecode which is a mixture of LISP, assembler and Bitcoin script. Ethereum uses Ether as its internal currency, the underlying decentralized cryptocurrency at the same time that it serves to execute its smart contracts. In this respect, Ethereum is not like most of the existing cryptocurrencies, since it is not only a network for reflecting monetary value transactions, but it is a network for feeding Ethereum-based contracts. These open source contracts can be used to securely run a wide variety of services from crowdfunding, intellectual property, and autonomous decentralized organizations. Finally, it is worth mentioning that Ethereum is very interesting, since it was developed to increase and improve Bitcoin, and the expansion of its capabilities. It has been developed to feature prominently in Smart Contracts, decentralized, self-executing agreements that are encoded in the blockchain network itself.

As a last example, I recommend you to watch the following video on Youtube called "Distributed Applications", which basically refers to Dapps or applications that are executed in a distributed network with the information of the participants protected in a secure way and the operations they run are decentrally on a network of nodes.

Dapps use open source code, they work autonomously with data and records cryptographically stored on a blockchain. Here Steemit, OpenBazaar, Storj.io, to name a few, are named as examples.

OPenBazaar is an Open Source project, like Bitcoin, that created a decentralized P2P trading network using BTC (Bitcoin) and without additional charges or restrictions of any kind. This means that right now the power in an exchange between buyers and sellers would no longer reside in a centralized service that communicates with them. It is the users themselves who connect directly. Without the requirement of any other third party. However, OpenBazaar announced in 2021 that it was suspending its Bitcoin trading service because they were unable to generate a business model that could cover their operating costs. They did not meet the same fate as their Amazon Purse.io competitor.

For its part, another example that the video shows is Storj.io, which is a decentralized storage application in the cloud, similar to Dropbox, but with the difference that Storj is based on blockchain technology and Peer-to-Peer protocols, thus delivering Private security.

The app incentivizes storage providers and connects them with those that require their files to be securely stored encrypted on the app's nodes in a distributed fashion until their users are ready to use them again. The keys remain in the possession of the data owners, who are not accessible by a centralized cloud.

Another decentralized application is Steemit, which is a social network that combines content creation, interaction with users, and the use of a blockchain with a cryptocurrency called STEEM.

The way it works is similar to web pages like Reddit. The only difference is that all text content is recorded forever in a Blockchain.

Users or members can upvote the content they want and depending on how many votes they get, they will get a reward in the form of Steem, Steem power or Steem dollars. The fact of voting content also earns rewards in the form of Steem. This is what they call Curation Rewards. Even comments can be voted on and thus become monetized.

PS: I go deeper into the subject in my "Advanced Collaboration Course".

Conclusions.

As you can see, we could be talking for days about Collaborative Business Models in the Distributed Computing Modality.

Clearly Distributed Computing, added to emerging technologies (Internet of Things -IoT-, Artificial Intelligence -IA or AI-, Blockchain, ....) are generating disruption in our lives today and in the future.

Distributed Computing, from its origins, considering the evolution it has had over time, has helped us as a civilization in two fundamental aspects: Time and Scalability. Instead of having one computer doing all the work, Why not combine the processing power of multiple computers? Distributed Computing offers us clusters of computers that do one or many different tasks simultaneously. In this way, Distributed Computing allows us to have our own Super Computer by uniting the power of all our devices. What used to take us 30 minutes now takes us 5 minutes, and we didn't have to spend money buying new equipment, or paying a third party to create better software. If we add to this the power of smartphones and tablets in your organization (even the smart refrigerator in your office or home), that's Time and Scalability.

Imagine what our future will be like in the medium and long term thanks to this technology!

PS: For those students of the course, go back to the course and follow the instructions to assimilate the knowledge delivered.

Source: "Distributed Computed", Hazelcast; "Computación Distribuida", Wikipedia; "Computación en la Nube versus Computación Distribuida", Conogasi; "Distributed Computing: Computación Distribuida para Infraestructuras Digitales Eficientes", Ionos; "Grid Irrumpe en la Empresa", Ramón Millán y Francisco Sánchez; "Ethereum, Plataforma de Computación Distribuida", Sistemas Distribuidos Foro Activo; "Qué es Computación Distribuida y por qué la Necesitas para Optimizar tu Negocio", Rodrigo Inostroza (Motivus); "Distributed Applications", System Innovations (Youtube).