All You Need to Know about Edge Computing

Tripti Rai, Appinventive IoT is crafting a new future of communication. By pushing the dumb objects to the Internet and enabling them to talk to each other, the technology is taking the digital transformation to the newer level. Despite the proliferation of this technology, the business leaders and app development are facing various challenges in IoT app development. One of the issues arose with the growing momentum of the technology is - how to deal with data? Currently, the data is collected from all the interconnected devices and sent to the central cloud where it is processed and shared later. Since terabytes of data have been processed, it consumes more time to transfer and process the data from interconnected devices to cloud and vice-versa. This interrupts the normal functioning of the IoT solutions and devices that require instant and real-time data. Besides, transmission of a large amount of data over the Internet increases the risk of data hacking. To solve these issues, the Edge computing technology came into existence.

Edge Computing
Edge computing is a network technology that optimizes the cloud data processing mechanism by executing the processing at the edge of the network, instead of taking it to the cloud.
This approach has various benefits to the overall processing of the IoT devices, some of which are:

. Less Time Consumption: Since the data is not transferred to the centre of the cloud for processing, the time-consumed for the processing is reduced.

. Lower Cost: Only the useful data is transmitted to the middle of the cloud network, which means lesser load on the networks and ultimately, lesser cost of networking.

. Higher Data accessibility: The business leaders and IoT app developers need not wait for the data to reach the center of the cloud and get processed; they can easily get useful data before it reaches the center of the cloud. This makes it easier to make decisions based on real-time data and enhance the IoT app development services.

. Better Performance: Again, since the load to the network is cut down to nearly a half, the response time is also reduced to some
milliseconds, which ultimately means higher performance at a lesser cost.

. Privacy and Security: Traditionally, the whole data has been transferred over a public Internet, which make it exposed to data breach circumstances. The data transmission done via IoT solutions leave the critical information vulnerable, which prompt the hackers to use it in harmful ways. However, now only a part of the information is exchanged at the core of the cloud, which prevents the sensitive information gathered and accumulated at the device-end from getting hacked and misused.

. Besides, the edge computing technology is drifting the processing power closer to the end users, which is boosting customer experience.

The AR edge computing framework boost offload the concerned AR algorithms over the local network to the considered IoT connected device, which means the data is targeted at the user’s point of interest.

Use Cases of Edge Computing in IoT development
The Edge computing technology is still in its nascent stage. It is expected to bring advancements in the following technological efforts:

. Drones: Drones are becoming the new vehicle for delivering goods and information (as in case of Amazon). These devices, earlier, were sharing data to the center of the network to get a command from the human based on the data. But, now they can review, evaluate, and respond in real-time - without human intervention. This is extremely helpful, especially in emergency situations where a delay of few minutes could bring drastic outcomes.

. AR: The major challenge with a comprehensive deployment of AR mobile apps is that they still depend on the devices for computational and graphical performance. But, with the advent of Cloud edge computing, this issue can be resolved which marks the next milestone in the era of Augmented Reality. The AR edge computing framework boost offload the concerned AR algorithms over the local network to the considered IoT connected device, which means the data is targeted at the user’s point of interest. Thus, better AR services. The overwhelming example of this is AR Remote Live Support mobile application. Such applications, with the help of Edge computing technology, implements right tracking algorithm in real-time and provide better results to the end users. However, the process of offloading is possible only when the available network/WiFi employs standard compression techniques, including but not restricting to JPEG.

. Self-driving Cars: Edge computing is supposed to play a significant role in the functioning of automated cars. The technology will enable the self-driving vehicles to operate and transfer crucial data to other vehicles and systems in real-time, which might lessen the chances of automobile accidents.

. Edge computing is fueling the IoT ecosystem with its unleashing potential and benefits. The technology, by bringing processing closer to the devices, is making the devices appear and act more powerful and intelligent - adding value to the concept of IoT and its future growth. It is expected that over 5.6 billion IoT devices will be connected to one another via edge computing architecture by 2020. This signifies the necessity to know and adopt the technology in the IoT app development.