Use Cases

Cloud computing is becoming increasingly popular, and it is for sure an essential tool of the present and future. It allows us to save massive amounts of data and gives big amounts of computing power which can be used for data analysis or video rendering for instance.

These services are however very expensive. For big organisations this might not be an issue, as the service provided is worth the price. However, for smaller companies or individual users the prices are prohibitive.

Distributed computing will allow everyone to get access to the current cloud computing solutions, as it will offer the same services at a significantly reduced price. And more importantly: with an increased capacity and scalability.

The aim with distributed computing is not to move away from cloud computing into something completely different; rather, distributed computing is an extension of cloud computing. By adding more computing power to the network, and by extending the server network into the users, users will be able to make a profit by contributing with their own machines and costs will greatly reduce.

How can this be achieved? Is it too far-fetched or futuristic? The answer to both of these questions is no, and we can prove that by example. Cryptocurrencies seem to be establishing in the market. Even if in their current form do not work, they are proving that a global network of computers working together is already possible. Using the existing cryptocurrency networks in a clever way would already be an extremely powerful distributed computing network, able to at least compete with Amazon or Google’s one.

Merging distributed computing with blockchain technology offers many other advantages. For instance, while ensuring security and privacy, it would facilitate the use and creation of new applications. Creating this platform that everyone uses and contributes to would also close the gap between industry and academia, which would be extremely beneficial for our society.

The Applications of Distributed Computing

Cloud computing is becoming increasingly popular. Many public and private enterprises are shifting their IT models to adapt to this new and improved technology. At a high level, the forecast for Infrastructure as a Service (Iaas) is $160 billion for 2019.

Amazon Web Services (AWS), which pioneered cloud computing and is now the leading cloud provider with 40% of the market share, seems to be exponentially increasing the revenue obtained with these services. In 2014 it was estimated that AWS alone had two million servers around the world.

From there it can be inferred that at the end of 2018 there were in total around 20 million servers around the world dedicated to cloud services. With the rapid increase in popularity of these services, this number could go up to 40 million by 2020.

This will force AWS and all its competitors to constantly build new server and data centers to keep up with the demand. These costly efforts will not be translated into great price reductions, and so cloud services will stay available only to a select few organisations. What’s more, all these computing servers are extremely costly for the environment, in terms of maintenance, energy consumption and electronic waste.

Distributed computing offers a solution to all these issues. There are over a billion PC’s currently active in the world, and over two billion smartphones. If we add to that tablets, routers and any other electronic devices that could potentially play a role in distributed computing, we have an extremely powerful network that is already existing and waiting to be enabled to its full potential.

By incorporating into the network edge and user devices the need for massive data centers will be reduced, and the ecological impact along with it. Distributed computing will also greatly improve the power and capacity of the network, which will translate into a drastic reduction of the prices and thus into the mass adoption of the services.

Our society’s mindset is already shifting towards this picture, as cryptocurrencies are proving. Bitcoin alone has 30 million users, so by combining their power they would already create a very powerful distributed computing network. Just like companies are specialising in creating specific hardware for mining, even better and more secure investment opportunities would arise thanks to distributed computing, as everyone would be incentivised and rewarded for their contribution to the network.

Below we present some initial use cases that show the exceptional potential of the distributed computing technology.

Medical data

When we go to a different center, or to a doctor in a different country, we would like these health professionals to have access to all our data, in order to make faster and better informed decisions. This however does not happen, as data communication between different health centers is still very inefficient.

Cloud computing facilitates this, and also allows to gain insights on the data by facilitating its analysis and management. However, this is confined within each healthcare organisation, and the networks and systems of each center may be completely different or even non-existent.

Distributed computing’s benefits extend way beyond the computing realm. By creating a network that contains all our health information, it would allow any healthcare professionals to have access to our data. Not only would we receive better treatment, but the doctors would make better decisions and spend less time enquiring and investigating about our health.

Distributed computing would ensure this data flexibility, while being completely private and secure.

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Medical modelling

Interdisciplinary collaborations and research are on the rise, as academics are discovering the potential and opportunities to share knowledge and collaborate on a wide range of projects. Mathematical modelling is quickly becoming an essential tool for biomedical, life sciences and environmental research, as well as for everyday decision-making in health centers.

Cloud computing providers are currently offering big data solutions for the healthcare industry, as well as medical imaging, machine learning for decision making and more. However, these services are not cheap, and even if in the long term they translate into cost reductions, many centers are not considering the adoption of cloud services.

Distributed computing, in addition to lowering the costs of these services, would reward health centers with additional revenue for their contribution to the network. It is well known that many health and life sciences research centers are on a very tight budget. Distributed computing would allow them to increase their revenue while giving them easy access to the current cloud services.

Additionally, by sharing the network while ensuring security and privacy researchers from different institutions would be able to collaborate in a more efficient way. They would also be able to easily collaborate with health centers, sharing and deploying their insights and discoveries in a simplified way as well.

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Machine Learning

Machine learning and neural networks are game-changing tools in prediction and decision making processes. In recent years Artificial Intelligence (AI) has been able to beat the best chess engines, and for the first time allowed a computer to win a Go game against the best human players.

Such a powerful tool is a key element for many businesses to greatly increase their revenue. From personalised product recommendations to image detection in videos, AI can be used in a wide range of applications.

Using these methods is not a straightforward task though, and there are a lot of factors that need to be learned and taken into account. The current cloud providers offer specialised, pre-trained AI solutions that greatly simplify these tasks for the users, but there are considerable costs involved that cannot be covered by most people nor by most researchers.

Distributed computing will offer these same AI solutions but up to 10x more cost-effective, allowing many new industry sectors and researchers to gain access to these tools. Libraries like TensorFlow will be already implemented in the network, facilitating model-building within the network.

Therefore, whether you are an experienced AI user or an inexperienced one, distributed computing will offer you solutions to your AI tasks. From simply providing computing power to run your custom-made algorithms to creating and partitioning data to run in template models provided by the embedded AI solutions of the network, you will be able to easily run the models you need with a simple few clicks.

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Rendering

Visual effects have greatly improved over the last few years, both in video games and in the film industry. Video rendering has become a field on itself, and all computers now have GPUs, which are specific hardware components used to create images.

However, video rendering is an incredibly GPU-consuming task, and thus professional rendering on a normal computer is not an option. Distributed computing will give a solution to this, similar to what the current cloud service providers offer but at a more competitive price.

In addition to providing rendering tools to make the process easier, using the distributing computing network will allow you to quickly render videos at a professional level, granting you the computing power of potentially thousands of GPUs.

By using existing GPU cryptocurrency mining rigs, as well as gaming PCs, the distributed computing network will have the capacity to render videos on demand, while rewarding GPU owners for the hardware provided. Therefore, both industry-leading companies and individual users will benefit from a cost-effective solution to render their videos, while earning money by contributing to the network.

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