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Top 5 Factors to Consider for Deploying Reliable Edge Computing

  • By Content Desk
  • May 15, 2019
  • 4 minutes read
Reading Time: 4 minutes

The Internet of Things (IoT) is quickly becoming the backbone of today’s digital infrastructure of many modern enterprises. Billions of Internet connected devices are increasing each year, resulting in  more data generation from each device.

However, managing and analyzing large amount of real-time data from various sources brings complexity in successful IoT implementation. To simplify the process, entrepreneurs have realized the need for a decentralized approach to address digital business infrastructure requirements.

“Since the volume and velocity of data increases, the demand for real-time and efficient processing and communication between distributed endpoints also increases.”

Most of this new data generates at the Edge of the Network. 

Most of this new data generates at the Edge of the Network.

Cisco Global Cloud Index (GCI) estimates that “nearly 850 Zettabytes of data will be generated by humans and machines taken together by 2021.”

Many companies now concentrate their efforts to gradually shift their infrastructure to a centralized Cloud center. This push began with the vision of reducing time to market new applications while achieving lower total cost of ownership (TCO).

However, the volume of data collected at the edge has increased. So we need to analyze and prune this data close to the point of collection. In consequence, a new technology is driving a trend that shifts the function of centralized cloud computing to edge devices of networks – “Edge Computing“.

The agility of Cloud Computing is abundant – yet alone is not enough to handle the heavy weight of the data. Many people need to interact with their digital assets in real-time, which requires a powerful processing and data storage capability.  Edge Computing will work in tandem with Cloud Computing complementing each other.

Why do we need Edge Computing?

Edge Computing is a distributed architecture, which takes computing process away from the cloud to the nearest location at the edge of the network and close to the end user.

The development of new and exciting applications like IoT with smart cities, drones, autonomous vehicles, Augmented and Virtual Reality applications have upsurged the need of Edge Computing.

To understand the need of Edge Computing in a better way, consider the following scenarios.

For example, a driverless car is waiting for a few milliseconds to talk to a distant data center in order to decide whether to run over a pedestrian crossing the road or stop just in time—the result could be disastrous.

Another example, what happens if a heart monitoring system cannot keep a consistent connection with the devices to measures and records heart’s activity continuously, will the patient be stable or in distress? 

Or imagine a WAN connection to a retail chain store goes down, can the point of sale still process card transactions? 

Likewise, If the gas wellheads leaks methane gas and the LTE connection is not available, how much pollution goes untracked?

These critical situations motivate us to move towards an Edge Computing approach that facilitates the processing of device data closer to the source; speeding up the analysis process and allowing businesses to act on insights more quickly.

By shortening the distance between devices and the Cloud resources, Edge Computing mitigates the latency and bandwidth constraints of today’s Internet. This means improvement in the performance and reliability of applications and services.

Gartner Group suggests: “Around 75% of enterprise-generated data will be created and processed outside a traditional centralized data center or cloud by 2022.”

Moving towards Edge Computing may have a thoughtful impact on an organization’s current IT infrastructure and might require an IT overhaul to build the Edge Computing infrastructure.

Every Industry leader or CIO should focus on the following 5 areas before deploying Edge Computing.

5 Factors To Consider Before Deploying Edge Computing:

1. Cyber and Physical Security:

For any organization, security is the most challenging factor in Edge Computing architecture and deployments. On the other hand, data collected near the sensors or devices where it is created and used may also be vulnerable to cyber-attacks. Hence, building a strong end-to-end security and extending it all the way from remote devices, edge of the network to the data center is important to avoid security threats.

2. Interoperability between Edge Deployments

Organizations must ensure the level of compatibility and interoperability between different Edge deployments while actually putting things into implementation. Various devices across the different network layers must be synchronized. In a nutshell, organizations will need an Edge Computing provider who offers end-to-end solution which can help the implementation of sensors network plugins to secure Cloud connection as well as huge gateways to seamlessly carry out remote operations whether on the server or virtualized.

3. Support and Maintenance

Many organizations manage IT infrastructure maintenance themselves. However, increase in the number of edge data center across a wider geographic area makes the performance of inhouse maintenance difficult.

All management systems that support Edge Computing need to be  advanced, highly automated and orchestrated. Doing so, will help in dynamically assigning, configuring and monitoring of various resources and software packages.

4. Network Architecture Planning

It is necessary to develop a network architecture and element partitioning to fulfill the requirement of users and applications. As an enterprise leader, it is important for you to understand which portion of the system can run in the Cloud and which can be executed at the edge. While partitioning can help distribute the application across the multiple peer nodes sharing the load, it is recommended to take guidance from technology consultants like Cygnet Infotech who are also expert cloud service providers to improve your network architectural models.

5. Selecting Modular Components

Different applications require different hardware components to equip on the edge nodes. Different components have different ability to perform based on their specific characteristics such as performance, programming algorithm, and memory storage level at the edge. Installing application-specific hardware components increases the interoperability between various modular components.

Planning to get the edge over your competition? Get in touch with Edge Computing experts at Cygnet Infotech at +1-609-245-0971 or to help you maximize revenue and productivity.

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