If we can solve problems for humanity with smart solutions, those solutions need to be sustainable. There is no point in solving a City's traffic problems and reducing pollution if the answer is not sustainable. If the solution relies on third-party systems or utilizes unfixed pricing computing, smart solutions are destined to become burdens for the cities and other installations.
Did you know?
Sustainable Computing considers the total cost of ownership, the full impact, and the real benefit of technology systems. With Internet of Everything Corp's embedded system solutions, we can save more energy than they consume, amounting to substantial net water savings and eliminating gigatons of CO2 emissions.
So sustainable computing is not just about code practices and code design but about understanding the entire footprint of the solution.
Let us start with raw computing. In computing, we have two choices of how we can run our code: compiled and interpreted. We use a compiler that produces a binary of machine code with compiled code. The binary is then run directly on the hardware through the OS. Examples of compiled code include C, C++, and Rust. Interpreting code is very different because the code is not compiled. Instead, it is interpreted as being a virtual machine that, on the fly, creates the machine code, and this virtual step needs a lot more CPU loops to execute the same task as compiled code. Python and JavaScript are two examples of interpreting code.
As one of the goals of sustainable computing is to lower wasteful energy use, interpreting code should not be used.
At Internet of Everything Corp, we use Rust, https://www.rust-lang.org/; Rust is fast, low-resource, and as it is compiled, it is cross-platform.
Let's look at the hardware; what can be done if servers lose one-third of their power from the heat? We need those servers, right? Well, no, no, we don't. The benefit of embedded tech installations is that we can access computing power at the installation. By clustering Internet of Things (IoT) devices to compute clusters, heat generation can be limited as computing is balanced over the devices. As the devices in an embedded system installation are spread out, it is not generated in one room. The compute load can be balanced so that none of the devices run hot, using power-aware compute clusters.
If not correctly planned, AI and computing can be extremely heavy and wasteful of CPU resources. For total sustainability thinking, even algorithms and methods should be evaluated. Using floating windows for pattern mining in data streams is more energy-efficient than processing all the data. Instead, as a pattern is identified, computing kicks in; this is especially efficient in embedded systems. The data generated that needs to be refined into information is not constant but bursting. For example, an intersection is often empty but has short periods of intense rushes; constantly using full computing is automatically wasteful.
IoE Eden is a green and sustainable Cloud of Things, enabling resource-sharing edge computing.
The Eden Platform is much more than some simple data pre-processing, which takes advantage of only a tiny portion of the possible computing on edge.
Eden creates Private Online Gardens with meaningful Edge Computing.
With an Eden, data can be stored and processed on the devices directly (the so-called edge). Useful and refined Information is then available for services to access and use, tremendously reducing the networking traffic and computing power used in data centers while also utilizing the computing resources of devices already in use.
This dramatically reduces the bandwidth and energy required by data centers. On top, edge computing also provides the flexibility to operate independently from an Internet connection, enables fast real-time response rates, and cuts cloud costs.
Eden reduces network traffic and data center usage. With Eden, the amount of data traversing the network can be significantly reduced, freeing up bandwidth. Bandwidth measures the quantity/size of data a network can transfer in a given time frame. Bandwidth is shared among users. Accordingly, the more data is supposed to be sent via the network at a given moment, the slower the network speed. Data on the edge is more likely to be helpful in the context of its environment. Instead of constantly sending data streams to the cloud, it makes sense to work with the data on the edge and make information available to services that can request it.
Clustered computing on Eden is typically more efficient than cloud data centers. As described above, resources on edge devices are restricted. Therefore, edge devices do not scale horizontally as opposed to cloud infrastructure. That is why every piece of the edge tech stack is - typically and ideally - highly optimized for resource efficiency. Any computing done more efficiently helps reduce energy consumption.
Giving a safe place to harvest the data to information and begin to perform changes in cities toward reducing carbon emissions. Another significant benefit that makes our Eden System a better option is scalability, as there is no need to deploy all the city's necessities in the initial stages. Making the technology cost-efficient because the economic investment doesn't have to be massive.
There is a realm of edge devices already deployed that is currently underused. Many existing devices are capable of data persistence, and some even for reasonably complex computing. Instead, when these devices send all of their data to the cloud, an opportunity is lost.
Eden enables companies to use existing hardware and infrastructure (retrofitting), utilizing the available computing power. If these devices continue to be underused, we will need to build bigger and bigger central data centers, burden existing network infrastructure, and reduce bandwidth for senselessly sending everything to the cloud.
Today, most projects are built based on cloud computing. Especially in prototypes or pilots, cloud computing offers an easy and fast start. However, cloud computing often becomes expensive, slow, and unreliable with scale. In a typical cloud and embedded system setup, data is gathered on edge devices and forwarded to the cloud for computation and storage.
Often a computed result is sent back. In this design, the edge devices are dumb devices dependent upon a working internet connection and a working cloud server; they do not have any intelligence or logic of their own. In a smart home example, data would be sent from devices in the home, e.g., a thermostat, the door, the TV, etc., to the cloud, saved, and used. As the user would want to make changes via a cloud-based mobile app when in the house, the changes would be sent to the cloud, changed there, and then sent to the devices. When the Internet connection is down or the server is not working, the application will not work; this is unacceptable for critical functions such as opening the door or alerting an emergency.
With Eden and clustered computing, data stays where it is produced, used, and belongs - without unnecessarily traversing the network. This way, cloud infrastructure needs are reduced in three ways: Firstly, less network traffic; secondly, less central storage and third, less computational power. Instead, clustered edge computing uses all the capable hardware available in the cluster. E.g., in a smart home, all the data could stay within the house and be used on-site. Only a small part of the data needed to be accessible from anywhere would be synchronized externally.
For example, a thermostat in such a home setting might produce 1000s of temperature data points per minute. However, minimal changes typically do not matter, and data updates aren't necessary every millisecond. On top, you do not need all this data in the cloud, accessible from anywhere. With clustered edge computing, this data can stay in the cluster and will be used within the smart home as needed. Clustered edge computing enables the intelligent home to work fast, efficiently, and autonomously from a working internet connection. In addition, intelligent homeowners can keep their private data to themselves and are less vulnerable to cyberattacks.
The benefits of the cloud are broad and robust, especially for complex web services such as webshops and subscription management. However, there are costs and places where this technology is a bad fit.
The Eden platform with clustered edge computing helps resolve the unseen costs of cloud computing. With Eden, we can reduce the unnecessary use of bandwidth and server capacity (which comes down to infrastructure, electricity, and physical space) while simultaneously taking advantage of intelligent device resources. Eden amplifies these benefits with high performance on small devices and efficient data synchronization - making clustered edge computing an even more sustainable solution.
*https://www.researchgate.net/publication/320225452_Total_Consumer_Power_Consumption_Forecast.html
