Why Both Cloud and Edge Computing Essential for IoT?


The use of Internet of Things (IoT) devices conveys huge support to both businesses & consumers. However, this rapid growth is putting a lot of stress on traditional data center infrastructure. To address this, edge computing is evolving more prevalent. As it enables processing power to be closer to the devices that generate or consume data.

This article will provide an introduction to the fundamentals of IoT, Cloud & edge computing & discuss the key reasons why they are a good fit.

What is Edge Computing?

Edge computing is a method of decentralizing IoT devices by operating cloud applications and services near the edge. The devices that are located near people & objects perform real−time data processing with minimal delay. By eliminating the need to send data to the cloud and wait for it to return it lowers network latency and congestion. Edge computing is a valuable approach to solving common problems faced by IoT devices.

What is Cloud Computing?

Cloud computing delivers services like servers, storage, databases, networking, software, analytics, & intelligence through the Internet. In cloud computing, the user can access these resources on demand and pay only for what they use without having to manage the underlying infrastructure.

Why are Both Cloud and Edge Computing Essential for IoT?

To harness the full potential of IoT, we need both cloud & edge computing. Here are some crucial points on why both cloud & edge computing is essential for IoT:

  • Cloud computing delivers a scalable & cost−effective method to process & store immense volumes of data developed by IoT devices.

  • Edge computing allows real−time data processing at the device level. It decreases the latency & enhancing responsiveness.

  • Edge computing also eases the load on the cloud by executing data filtering, aggregation, & research at the device level, decreasing network traffic & minimizing data transfer costs.

  • In addition, edge computing allows local decision−making & control, making IoT devices more autonomous & independent.

  • By combining cloud & edge computing, organizations can construct a hybrid architecture. It delivers the best of both worlds, leveraging scalability & costeffectiveness.

  • Security is a critical consideration for IoT. Both cloud & edge computing can play crucial roles in securing IoT devices and data. Edge computing can deliver security at the device level by executing access controls and encryption, while cloud computing can deliver robust security standards such as firewalls and intrusion detection.

  • Edge computing can allow faster data processing by conducting computations locally, which can be critical in scenarios such as industrial automation or self−driving cars.

  • Cloud computing can deliver centralized management & control of IoT devices, allowing organizations to monitor & control large numbers of gadgets from a single location.

  • Edge computing can allow independent decision−making by IoT devices by leveraging machine learning & artificial intelligence algorithms. By processing data locally, IoT devices can produce decisions in real−time without relying on the cloud, enhancing response times & easing the load on the cloud.

  • Finally, a hybrid cloud−edge architecture can deliver more significant flexibility & strength in the face of network disruptions or failures. By distributing processing between the cloud & edge, organizations can assure that critical operations can resume to operate even if one part of the architecture fails.

Benefits of Both Cloud and Edge Computing Working Together with IoT

  • Improved speed: Edge computing permits data processing closer to the source, leading to more rapid response times.

  • Reduced network latency: By using edge computing, data can be processed locally, decreasing the need for data to be transmitted back & forth to the cloud. It leads to decreased network latency & more dependable data processing.

  • Lower costs: By using edge computing, businesses can decrease the amount of data they require to transfer to the cloud, leading to lower bandwidth costs. It can be extremely profitable for businesses with large−scale IoT deployments.

  • Improved security: Edge computing can deliver an additional layer of security by processing sensitive data locally, rather than sending it to the cloud. It can be particularly crucial for applications such as healthcare, finance, or critical infrastructure.

  • Scalability: By using a combination of cloud & edge computing, businesses can scale their IoT deployments more effectively. It permits them to handle a large sum of devices & process data more efficiently without any expensive hardware upgrades.

  • Increased flexibility: By using both cloud & edge computing, businesses can select the most suitable processing location for each application. It permits them to optimize their resources & enhance overall efficiency.

Conclusion

To address this, edge computing has developed to allow processing power to be closer to the devices that generate or consume data. Benefits of both cloud & edge computing working together with IoT include improved speed, reduced network latency, lower costs, improved security, scalability, increased flexibility, and enhanced insights. Ultimately, leveraging both cloud and edge computing is essential for organizations to harness the full potential of IoT & to stay competitive in the fast−paced digital world.

Updated on: 29-Aug-2023

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