What is Edge Computing? And why is it essential?

The number of physical devices in the IoT network has been rising exponentially during the past decade. All these are generating and sharing some data in one form or the other, But where does the computation and processing of this colossal data take place? Is there any limit to the computational capabilities of this source? How can we overcome this if the number of devices and data goes on increasing?

Where and How is the Data Generated and Computed?

Data is generated by our interactions with the equipment that we use and from that equipment itself. Any device in the IoT(Internet of Things) network generates data. The main place where all this data ends up going where it can be further processed and used is the Cloud. The Major public cloud providers include Amazon, Microsoft, Google, and IBM. Tasks like Trend analysis, aggregate analytic take place in the cloud.

What is Edge Computing And why is it required?

Edge in the word ‘Edge Computing’ refers to the origin of data where the data is being generated namely the devices which are a part of IoT. So as the name suggests Edge Computing refers to bringing the computation of data near the edge itself where it is generated. Most of the new generation devices belonging to IOT have very good computational capabilities. Moreover, the amount of data constantly being generated at the edge is growing exponentially faster than the ability of the networks to process it. So not processing the data at the edge can be considered as a waste of that processing power and at last edge computing is inevitable looking at the current scenarios of growth rate in the IoT network.

Benefits of Edge Computing:

Edge computing has numerous amount of benefits here are some to name a few:

1. Reduced Latency and Speed: Limiting the data processing to the edge itself eliminates the latency, this leads to faster response time. Now, most of the processing is done at your device only, hence you don’t have to wait for the cloud to reply to your queries this also ensures complete utilization of your device’s processing power.
2. Cost Saving: This might not come naturally but think about it, now you are doing most of the work on your device itself hence you are not sending very little data to the cloud compared to earlier, keeping most of this data at the edge, first of all, reduces the bandwidth usage for transfer of data which directly reduces the cost required for connection. Moreover, when some data is generated at the edge it must be stored at least temporarily on your device, now if you send this data to the cloud for processing the same data must also be stored there again, this creates levels of redundancy preventing this reduces the redundant cost required.
3. Prioritizing Data: Edge computing helps companies in prioritizing data, this helps them focus on critical data that needs to be analyzed, processed, and stored urgently. This reduces the signal-to-noise ratio. An example would help, let’s say you manufacture cars and you have added sensors in the cars you make, now if this sensor keeps on sending the message that it’s in a good state this would generate a lot of noise. An event when this sensor sends that it is not in a working state is more important to a monitoring company than its counterpart. Edge computing helps in solving this issue.
4. Reliability: Edge computing offers great reliability as most of the time edge computing does not rely on an internet connection hence offers uninterruptible service. Users don't need to worry about network failures or slow internet connections. Therefore edge computing can be really useful in remote location areas where there is no reliable network connection.
5. Scalability: Cloud Computing architecture requires data to be sent to centralized data centers for processing. Expanding and Modifying these datacenters is costly and has its limits. However, with edge computing, the edge can be used to scale our own IoT network without worrying much about the storage requirements.

Some Drawbacks of Edge Computing:

Listing out some disadvantages of Edge computing after talking about its benefits is inevitable :(

1. Security: One of the biggest drawbacks faced by edge computing is the amount of security it offers. Edge computing has a distributed environment, ensuring their security can be challenging at times. Threats like identity theft, cybersecurity breaches always remain a challenge to edge computing.
2. Loss of Data: Edge computing only processes and analyzes partial sets of information. The rest of the data is just discarded. Therefore the data must be prioritized before operations.
3. Investment Cost: It can be complex and expensive to implement a good edge infrastructure. This is due to their complexity which requires more infrastructure and resources. Edge computing offers an overall much better efficiency however a substantial investment is required.
4. Maintenance: Edge computing is a distributed system, which means that there is an increased number of various network combinations with several computing nodes. This requires a higher maintenance cost than a centralized infrastructure like cloud computing.

Edge Computing and 5G:

5G is one of the main drivers of edge computing as it allows for the increased number of data sources and processing points that can be interconnected, this implies an exponential increase in the volume of data to be processed. This is too tolling for the existing cloud architecture and therefore data processing needs to be much closer to the source. A key component of 5G is reduced latency, this requires processing power to be made available closer to where the data is generated.

Future expectations of Edge Computing:

The future of edge computing is going to be bright. Edge will converge with the use of data through artificial intelligence and machine learning to turn insight into actions that benefit all scales of businesses and their customers. It will eventually be viewed just like any other location where applications can be placed seamlessly with consistency and without compromise.