When one thinks about the modern cloud environment, the first thing that comes to mind is speed and reliability. With centralized data analysis, a faster bandwidth connection, access of data is faster. Speed and accuracy is the need of the hour and the collection of data from the organization's environment is continuous and centralized.

But, Is it necessary for the data from all physical devices to be centralized?

For instance, imagine numerous devices scattered around an organization's physical IT environment. They may be used to carry out a range of tasks such as identification, counting, measurements and so on. Many of these are IoT devices, which pile up data over time as they are used. While IoT devices are labelled to be 'data rich', most of the continuous stream of data need not travel to the centralized repository of the cloud.

What does this mean for cloud computing? Is there an optimal way of reducing the paths traversed by data building up over time? That is exactly what edge computing technology is used for, to collect, process and filter the data "in place" or near the network edge.

What is edge computing?

The cloud architecture is suited for the tasks of the modern IT workspace. However, given the abundance of physical devices used in the IT environment today, edge computing has emerged as a modern, and more feasible and important architecture. Rather than having all the data allocated at the cloud, edge computing helps deploy storage resources closer to the physical location of the device.

So, how is this helpful? Given the number of interactions we have with physical devices, this reduces the need for data to traverse all the way until the central repository. Edge computing puts compute and storage at the same point and the data source at the network edge. It helps deploy computing and storage resources at the location where data is produced.

How does edge computing work?

In simple terms, edge computing is all about having the data processing, right at the data source. Edge computing takes infrastructure into account, and focuses on data being near the infrastructure, rather than a central data hub. Given the current amount of data generation, the volume of data being produced may be too much for traditional data centers to accommodate over time.

Hence, with edge computing technology one can shift the focus to keeping the data where the resources are. The idea of edge computing is as similar as having hardware as a data collection platform, right beside the device. This is applicable in resources where it is more efficient to have the data collection right at the computing source rather than have it at a centralized location.

1. Cloud computing

To get started with understanding the basics of edge computing vs cloud computing, focusing on the common theme helps. Cloud computing is a huge, scalable process that offers network access to a pool of shared resources. It is a centralised system of data storage where the data from different physical infrastructure is located. Although this is the main idea, it is offered in various models that best suits business requirements.

Businesses are steadily adopting cloud services to keep up with the generation's demand for data influx. Not only is cloud computing a more dynamic way of managing your data, it is safer, increases accessibility and is easy to set up.

Even though cloud computing is the most preferred platform when it comes to IoT devices, with respect to data collection, the nearest regional cloud facility may not be at a closer distance to the actual physical infrastructure. The need of a higher bandwidth is a must have, due to the distance that is travelled by the data collected. It is still possible to get the cloud source at a closer distance to the physical device, but never at the network edge.

2. Edge computing

Edge computing does not stray far away from the main theme of cloud computing, but is a rather decentralized form of management of data. Edge computing technology focuses on the physical location of the data and the infrastructure. When the storage resource is ideally closer to the data source, in some cases it can greatly benefit businesses and their customer retention strategies.

Edge computing basics can be carried out through a special computing unit called an edge device or through specialized software which may be on a virtual or physical server that is closer to the device that captures or creates the data. These computing services can help capture, store and analyse data to make real time decisions.

To understand edge computing basics better, imagine a retail store that has a continuous monitoring system of the customers that go in and out throughout the day. The business can derive analytics such as timing of greater activity, average hours spent by a consumer, ads that propel customers to different sections and so on. When this data can be combined with the physical evidence of visuals, it can help the business come up with a better customer targeting strategy.

However, this form of edge computing examples that showcase decentralization can also be challenging. It does offer a solution to emerging network problems such as latency and bandwidth issues, the amount of data generated and the use case according to industry.

With the advent and implementation of 5G, the issues of lower bandwidth and latency in cloud computing is slowly coming to an end. However, instead of using it to enhance their data collection in the cloud, some businesses are using the concept of edge computing to provide faster response time and real time processing. The advent of faster data speeds will not only increase the amount of data being collected, but also the number of devices used.

Gartner predicted that by 2025, 75% of enterprise generated data will be created outside centralized data centers. For different companies, the idea of using and modifying cloud technologies may vary. Some benefits of edge computing technology that helps understand its usage better include,

1. Minimal set up and faster data processing

If you are an organization that levies on real time analytics and data processing, edge computing basics may be beneficial. It requires minimal gear to operate on the remote LAN to collect and process data nearer to the physical device. Unlike the cloud where there is no physical protection of the main data segregation platform, this edge computing setup may need additional physical protection from extreme temperatures, moisture and so on.

2. Works on lesser bandwidth and avoids network congestion

The current models of data collection and analysis are never a 'one glove fits all' form of model. According to the industry, there are modifications made in the data collection infrastructure. While most places have the ability to obtain a good bandwidth there are remote locations that may not have the same privilege.

In locations such as oil rigs and ships where the connectivity may not be stable, edge computing technology does the work required. As all the actions are performed at the site of the physical device, the need to connect to the central data location is not required at every moment. Edge computing ensures proper data backup and recovery when bandwidth is available, while also offering on spot, independent, functionality.

3. Management of data laws and security

The amount of data collected in this generation has led to the emergence of governance laws on privacy and security. If an organization operates in multiple locations across the globe, it is necessary to comply with the data privacy regulations of the country. In cases such as these, it is often better to use edge computing to localise data obtained and comply better with the restrictions of the region.

In terms of security, enterprises have always trusted cloud providers due to the services offered. The number of devices used grows by the day and as every device grows, a new gateway is created for opportunities to disrupt the network. Edge computing technology helps layer an additional seal of security by encrypting the data that leaves the edge device and travels to the cloud. Apart from this, the edge deployment device can itself be used to harden security against malignant attacks. This forms an additional layer of security as IoT devices remain unarmed and susceptible to attacks.

4. Reduced WAN costs

One of the features of edge computing basics is that It allows businesses to categorise data, based on what is to be stored locally, and what is to be sent to the cloud. While the overall collection of data cannot be modified or divided this way, retaining data in the edge computing device reduces WAN bandwidth costs. This temporary storage of data until it can be sent to the cloud for storage again is a beneficial factor as it improves data redundancy.

Although edge computing seems like a viable alternative instead of jumping on a much larger solution like cloud computing for your business, there are barriers present, like any other form of technology. Before implementing the idea of edge computing for your business it is necessary to understand the challenges and how they can affect your business strategy.

1. No selection of short term and long term data

The usage of IoT devices brings about an influx of data, of which a part is used for analytical purposes and the rest is just noise. For instance, a constant monitoring device would pick up all the data that is programmed to, throughout the day, but the requirements may include only a part of the data and not the complete data.

Most of the data involved in real time analytics is short term data and it is left to the business to decide the allocation of the rest of the data. Regardless, in many edge computing examples, this is an issue that rises with most data collection devices and it is important to ensure that the data that is retained, is according to the regulatory policies of the region.

2. Connectivity

While edge devices do perform at lower bandwidths, it is not completely foolproof as it does require a certain amount of bandwidth for backups to the main cloud. Regardless of how the bandwidth may be, it is necessary to design an edge computing framework that works on lower bandwidth. Planning is required to work on issues such as connectivity loss, and erratic connections at the edge device.

3. Emphasis on security

With cloud infrastructure, it is a given that the provider ensures security of the data and storage. However, with edge computing it is necessary to emphasize proper device management, regular security updates, attention to encryption and so on as each IoT device may form a gateway for any malicious attack. Even though providers of IoT devices may ensure secure connections, it is vital in edge computing to provide an additional layer of security.

Implementation of edge computing: does your company need it?

Edge computing is often a situation specific design as of today, with most companies rooted in cloud computing technologies. Enterprises such as AWS and Verizon have understood the impending effects of better 5g and wireless technologies and have partnered to provide the next generation of edge computing with the required automation capabilities.

But as you explore the potential of edge computing technology, it is essential to keep in mind that implementation ultimately depends on your organization's needs and resources. Does your organization have a need for analysing data at the spot? Can real time analytics impact your business function? Does your organization have the need for a low latency, lesser bandwidth service? Having an assessment of qualities as well as edge computing providers can help you decide on the implementation of edge computing for your organization.