Contemplating that the biggest trends in computing, chances are you may think of this cloud, Artificial intelligence, in addition to the Web of things. Virtually everybody knows about the cloud but this technology is not stagnant, it is evolving which has resulted in the growth of a new computing model — Edge computing (EC.) Thus, new scenarios are being composed motivated by these four technologies as foundational to the optimization of data handling processes.

From Cloud into Edge — back to the roots

The bigger the heaps of information which will have to be operated on, the better. In the context of the rise of the Internet technologies the IoT is tripping, this upward trend required and has been demanding changes in the computing system. This is how Cloud computing (CC) happened to dominate the global IoT market recently.

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Since isolated embedded systems provide applications with the comparatively little data volumes, they have given way to cloud-based solutions, systems, and solutions. Sooner or later, Cloud computing has shifted the sort of IT discourse. As both revolutionizing technologies, IoT and the cloud turned out to match each other perfectly — you may find platforms that are provided with substance  to be created on. Thus, using the metaphor of a cloud, we, as single clients and supervisors or employees of big and smaller companies, have storage and processing tasks offloaded. Fortunately, there’s a whole variety of platforms that permit the mixture of CC and IoT. To put it in summary, the advantages of Intelligence in Cloud for IoT could be introduced as follows:

  • remote control of data
  • the merging of data from several devices
  • infinite storage that let AI tools improve their calculations

We seem to hold all the cards in our hands, yet that is just for now and, in actuality, a person should look ahead. This form of computing functions nicely with PCstablets, and tablets, while the quantity of IoT apparatus is, in turn, expected to triple by 2025 rising to alarming 75.44 billion. More devices mean there will be more information to process. Despite the fact that the cloud serves as a relatively reliable intermediate layer between smart objects and applications, its scope needs to be broadened with the load development. The shift in the computing paradigm was needed badly.

Why Edge Computing?

Though we’ve emphasized the connection of calculating to IoT particularly, Edge is not all about it. The principal motivation behind using Edge touched a broad question of efficient data collection and management. In the course of time, the new type of computing was demonstrated to be the perfect place for the realization of these purposes and started becoming anchored in the corporate programs. But why and how?


IoT belongs to numerous verticals and is characterized by interactivity as user-centric support. It indicates the need for a particular proximity of the processing to the origin. With CC, however, there is just one distant large data center (in rare cases, there might be several of them ) that functions as cloud storage, which is highly inconvenient when the interaction of users with their apparatus need to be prompt. Consequently, Edge computing continues to be an alternate way of eliminating space and time and a perfect solution for accelerating and enhancing the performance of the cloud for customers introducing the Upcoming enormous improvements:

  • Latency reduction.  Experiencing boosts in data volumes might be more comfortable when residing at the border. Instead of network latency caused by nonstop moving data back and forth between devices and clouds, the boundary enables this interaction to be lively offering the manners of hyper-interactivity implementation. The border doesn’t just replace clouds, it decreases the latency. By means of example, if consumer bases are dispersed, clouds can be replicated remotely by installing intermediary data centers or servers. Physical proximity affects not only users’ confidence but also the latency. Due to this, end users who, figuratively speaking, live in Tier-2 cities far from big data centers have a opportunity to experience a lot better UX.
  • Advanced security management.  Another reason to consider EC is the pressing safety issues. Data privacy in IoT must be a focus of attention. Now that systems are related to the cloud and to the net, there is a threat not just to information but to what is happening in real life also. The aforementioned time and distance elimination can reduce the risk. The simple logical network elements — boundary nodes — are being designed and organized in hierarchical sequence to maximize the whole architecture. Lying between the cloud and the IoT apparatus they operate, the nodes contribute to enhancing the safety. The closer they are located into the sensors, the shorter the information flow distances would be the bigger the attack is.
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Edge Computing: How is it different from the Fog?

Sometimes, both these notions are used interchangeably, but they actually convey different meanings. Much like border calculating, the fog is a mediator between end users and cloud data centres. However Cisco, that has introduced fog computing, asserts that the fog is the standard according to which the boundary is brought into action, not the boundary itself.

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Azure IoT Edge

Indeed, the notion of Edge computing is exciting but it means nothing without the real life examples of its application. Nevertheless in 2008, Microsoft raised the dilemma of the future of Cloud computing and following that, a decade later, in 2017, came up with the Azure IoT Edge Runtime.

The organization recognized the waves of innovation and acknowledged that Edge and IoT were fitting in these waves connecting two worlds using advanced AI systems. It was a brand new quality of Azuze, a cloud computing platform, that allowed doing EC. This higher-level intellect was sourced as a new scenario necessary because of:

  • reduced latency resulting in close real-time response
  • protocol translation as the best way to connect devices by default with no access to the Internet
  • data normalization as the best way to make it available for different systems and solutions
  • privacy and security of users’ data

Numerous internationally recognized companies that promote IoT are approaching Azure for their clients to have a better customer experience when on the net or even offline. These concepts Azure IoT Edge communicates are demonstrating why the solution is worthwhile and what sort of value it is attaching the UX generally and also to companies especially:

  • Edge Runtime.  It provides such standard services as connectivity and security management for smart devices otherwise isolated from the web, offline saving and forwarding.
  • Modules.  It is Edge Runtime where modules are handled. They are sometimes presented as links of a chain that perform various activities adding capabilities to the runtime to tackle an end to end situation. Whatever the case, custom modules can be earned by composing them in the language of the software engineers’ choice. For instance, modules can be applied to connect with an IoT apparatus that is not adapted to access the net and the cloud, thus, sending data to Azure.
  • Cloud offload.  We have previously mentioned jobs offloading. What should be noted here is that at Azure IoT Edge, analytics is done with ML involved.
  • Cloud configurability and monitoring.  The IoT hub is used to control device lifecycle, and to configure and monitor IoT devices.

Therefore, Azure IoT Edge as one of Microsoft’s solutions is now proving to be a successful platform for innovation acceleration and advanced IoT solutions building.

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Crosser Edge Computing Solution

Since EC is growing in popularity and evolving, companies that are focusing on the creation of the software solutions for the benefit exclusively are coming into the scene.

One of these companies is Crosser. They have engaged in the EC solutions development jobs for these reasons:

  • Factors of IT security.  Cleaning at the boundary (filtering out the relevant data, normalizing it from different sources, and aggregating to reduce its amount and get a blank  data collection ) allows anonymizing data before sending it in the cloud and transferring only the relevant and crucial data there.
  • Streaming analytics.  Moving the analytics into the border as opposed to sending it to the cloud or in an abysmal environment together with applying more advanced algorithms discovering data anomalies helps to create notifications about the maintenance procedures and security measures that are needed locally.
  • Available under any circumstances.  Poor connectivity to the cloud is not an obstacle anymore. EC introduces streaming of information to keep it then upload it in the cloud when the link is restored.
  • Reduced data storage costs.  Cloud providers usually charge the clients for the sum of connected devices and connections, amount of data sent, selected services in the cloud, and the frequency of calculating use. As a result, the system and the layout needs to be adjusted to optimize these costs, which can be readily achieved with the aid of computing.
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At that, Crosser is successfully fulfilling the objective of utilizing the aforementioned features applying the whole edge computing solution to the benefit of its clients.


1 way or another, the establishment of novel computing paradigms is a natural process in light of their continuing IT innovations.

Computing is found in a number of things forming our private and corporate everyday lives — that is exactly what the energy of IoT means. The full world of the connected computing devices in every shape, form, and size is coming together at the border. To people who know how revolutionizing the IoT is and have data to be managed correctly and with minimal risk, such platforms as Azure IoT Edge and Crosser IoT Edge may be quite beneficial. All it takes is to allow these computing platforms, empowered by the merits of this AI, to create smart edge solutions getting processes under complete control.

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