Next Edge in computational power: Edge Computing!

If you have ever tried accessing metaverse platforms thru laptops or mobile phones, you would have faced two situations. First rapid depletion of battery power and secondly, tremendous heating up of your devices. Both situations are not conducive to a seamless virtual experience. You might also find Virtual spaces/Avatars taking a lot of time to load. Additionally, avatars many times get knocked off the platforms suddenly. While your system capabilities and internet capacity might be a contributing factor there is more at play here. 

Now here is the thing, the volume and speed of computations required in today’s world is unimaginably high. That is why when millions of instant rapid computations take place back and forth from the cloud, collecting, processing and delivering data in near real time there is an overload faced by the systems. If we continue with the example of Metaverse Platforms rendering smooth experiences, continuous predictable and unpredictable movements, dynamic 3D worlds, graphics and so on causes systems to heat up and burn battery power rapidly among other issues.

Similarly, organizations in various other industries too face issues such as cloud and computational latency due to centralized and outdated systems (caused by back and forth of data movement). Then there is the concern of huge burden on bandwidth due to massive processing requirements.

Hope organizations realize the heightened security risks because of constant data transmissions creating exposure to cyber threats. Additionally, there is the tremendous cost involved with so much data transfer, storage and processing requirements.

It was also found that dependence on centralized systems reduces reliability and no wonder then that scalability is tough with an already challenged system.

Data studies have shown that there is increased power consumption due to continuous data processing also causing Network congestion due to heightened data transfer.

Most importantly what businesses should fear is the dependence on a central system increasing the possibility of a single point of failure!

The above is not an exhaustive list but just a few issues to give you an idea. A technological solution to these concerns was sought and the indigenous human mind found one right at the edge of the computational network. It brought computing to where the data was being generated rather than causing the systems to go wild with the mad rush of bouncing data transfer! Yes, the solution came in the form of ‘Edge Computing’!

In simple terms ‘Edge computing’ is sitting at the point between the physical and the digital.

It is a distributed computing paradigm forming an IT architecture which utilizes IoT and/or other devices like edge servers, gateways, routers, smart sensors, operating systems and containerization platforms (e.g., docker) to name a few. These devices collect data as near to the source as possible and process it there itself bringing computing to the edge of the enterprise’s network systems. This includes all variants of data, that which is collected like the unpredictable user generated data in the metaverse spaces or specified organizational data, including the metadata and every other data which requires computation or storage. 

The dependence on centralized systems is removed. Instead of exposing data to external threats all the time, edge distributed organizations can now store and send the data to the central cloud when desired or at specific times aiding in robust security.

It provides speed, resilience, scalability, efficacy and cost saving along with security.

If we think about businesses, unimaginable amount of data is being generated in branch offices, retail outlets, oil and gas rigs, manufacturing units, millions of locations globally and even by satellites. This data is only going to multiply exponentially!

A central system is outdated to manage it all.

Distributing the computation is the natural and smart solution.

Organizations which want to scale their AI applications including generative AI will need to employ edge technology so that AI can be trained on data collected at the edge and analysed for local patterns in real time. Will this not help in making training models simpler? Application of edge computing in this way helps improve the performance of all business applications.The cloud is lighter, AI is smarter, scaling is easy and the enterprise runs faster and smoother.

Thanks to the genius of Edge computing many organizations are utilizing edge computing in varying capacities. Be it IoT devices, Healthcare, Transportation, retail, manufacturing, gaming or any other field, edge computing provides much required support to advanced systems.

Suppose you have a large manufacturing unit, or a pharmaceutical lab. You have sensors which collect data and compute faults on the site. No need to wait for the data to be sent at the center and later analyzed following which rectifications are made. There are millions of such processes going on in the manufacturing unit at lightening speeds. A company will have similar manufacturing units spread across the nation or globally. Data is being generated at staggering speeds! In such a case then will it not help that company if local faults could be found and fixed at the local source itself? Without waiting for a central directive? This is how edge computing saves resources, time and increases efficiency.

Similarly, sensors and devices in healthcare can help in remote monitoring of patients. Imagine there is an emergency case in the ambulance. Luckily it has edge enabled sensors processing patient data in real-time and relaying it to the hospital. The hospital gets accurate information and hence is well prepared to save the patient when the ambulance reaches the hospital. Additionally, even during surgeries important patient vitals can be made visible to the doctors thru specialized glasses even as they perform the surgery without having the need to look around or be told by anyone else. The sensors send information and edge computers compute the information onto the glasses. This is not sci-fi but a true possible scenario.

When we talk about automation, Autonomous vehicles can never be ignored. Autonomous Vehicles and their route optimization require high computation speeds in real time. Edge computing along with AI are most suitable to give instant and fast optimal solutions. Tesla is an example we all are most familiar with.

Next if we look at retail, a lot of automation can be achieved on premises of retail outlets which does not require immediate center involvement. This can include inventory management or smart stores where everything is automatically managed including self-checkout stations. Here edge computing is an effective on the spot computing solution.

Interestingly in manufacturing Edge computing helps with predictive maintenance and quality control by instant computation of faults and assigning corrective actions locally. Time is saved as faults are fixed without requiring later inspections like car manufacturing units for example.

Many times, remote oil rigs lose network connection. However, by employing edge computing the work continues to be computed locally and later the data can be shared with the center

Edge computing can solve many problems of Gaming, Digital Twins and Metaverse platforms. Edge computing can reduce the load of the main servers helping keep systems cooler, processing faster and smoother because of localized computing power.

Despite the above advantages it is not always easy for every organization to quickly or easily adopt edge computing into their digital architecture. There are many roadblocks and challenges along the way.

First issue is the cost itself. Imagine the requirement of upgrading the entire digital architecture from base up and the cost involved with it. Secondly, finding adequately skilled professionals and vendors to be able to setup the entire system effectively and correctly. Third and most important roadblock comes from within the organization in the form of executive decisions. 

While everyone understands the importance of leveraging edge computing however, decisions vary on the scale of its adoption. Due to this some companies are using edge computing but driving everything centrally. The effectiveness of distributed edge network is lost in such a case as eventually everything is managed by a central cloud and, hence providing a weak solution. Let’s hope they understand this and think about wasted effort and reinvent.

Then there are companies are using edge computing in bits and pieces. Maybe in one or two projects of their organization. When other locations are left out scaling and standardization is lost. These enterprises should really rethink their strategy again.

However, there are some organizations which have built a strong edge deployment and are making tremendous use of its distributed network capabilities. They have employed edge computing technology effectively and stand to gain from their competitors due to this approach.

In any case the most successful organizations today are the ones using Edge computing at the very foundation/core of their digital architecture. They are leaps and bounds ahead of any competition as scalability at any time will be easy and achievable without requiring rebuilding the systems from scratch. 

In all the importance of edge computing is not lost on enterprises.

However, they must realize that time is of essence and it’s better to incur a cost now and level up rather than struggle for survival later.

Essentially, technology is all about constant change and regular upgrade! To reinvent in time is to stay relevant!

Therefore, it is no surprise then that top companies of the world like Accenture, IBM, Tesla including Indian companies like Tata Consultancy Services ( TCS ), Infosys and Wipro are investing in Edge Computing centered solutions. 

In India, Telecom operators like Jio, Airtel and Vodafone Idea are deploying edge computing for 5G networks and IoT applications. 

India’s Ministry of Electronics and IT (MeitY) recognizes a great future in this technology and has launched initiatives like ‘Digital India’ which includes Edge computing as a crucial component along with AI and quantum computing.

Smart cities can never be a success without application of Edge Computing.

It is a fair assessment then that the time has come for organizations to lead in edge computing adoption or risk becoming redundant. Challenges cannot be excuses; a proper edge computing strategy is vital for every organization. If we take the example of metaverse platforms maybe specially enabled routers with edge capabilities might help bring better user experience. 

Edge computing brings forth a powerful solution to the exponentially multiplying data processing requirements and is a technology to be looked at with interest and expectation. 

Human mind is forever inventing and reinventing. Maybe it is this entanglement with our own genius is what gives us the ‘Edge’ over other beings on this planet!

About Author

Shalini Verma is a Delhi based Entrepreneur consulting on digital transformation by leveraging emerging technologies like Enterprise blockchain, AI, Cloud Computing and Metaverse as a Marketing Platform.