December 10, 2024

Ashlyn Steppello

Wireless Connectivity

Edge Computing: Processing Data At Your Edge

Edge Computing: Processing Data At Your Edge

Introduction

The cloud and edge computing are two buzzwords that have been floating around for a few years now. But what do they mean exactly? And how do they relate to each other? Let’s start with the definition of both terms. The cloud is defined as “a large-scale computing environment where computer resources and information can be shared over the Internet.” Cloud refers to a service (and infrastructure) that resides outside of an organization’s internal network but can still be accessed by its users from anywhere with an internet connection. Edge computing refers to processing data at the edge versus in the cloud or on-premise servers.

Edge Computing: Processing Data At Your Edge

Edge Computing Definition

Edge computing is the process of processing data at the edge of a network. It’s a subset of cloud computing, and an alternative to it. In edge computing, you can run applications locally instead of sending them all the way back to your data center for processing. This means that you don’t need as much bandwidth or power in order to run those applications because they don’t have far to travel before being executed on an edge device (like an IoT device).

Edge computing isn’t just about saving money by reducing expenses; it also allows organizations more freedom when working with their data because they aren’t limited by distance constraints like they would be if everything had been sent off site beforehand

Edge Computing Use Cases

  • Autonomous vehicles
  • Machines
  • Robots
  • Smart cities, smart manufacturing, and smart agriculture. In these use cases, edge computing is used to process data at the source of collection or in close proximity to it. This can be accomplished using sensors placed on machines or objects in the field. For example:
  • An autonomous car collects information about its environment as it drives through traffic and sends this data back to a central processing center so that it can make decisions based on what it sees around itself (such as other cars).
  • A self-driving tractor uses sensors attached along its frame to monitor soil moisture levels across its field of crops–this allows farmers to have more precise control over irrigation schedules for optimal growth conditions for different types of plants based on factors such as sunlight exposure levels

Edge Computing Advantages

  • Reduce latency
  • Reduce costs
  • Increase security
  • Increase flexibility (e.g., support multiple applications)
  • Increase scalability

Edge Computing Challenges

While edge computing is an exciting new field, it also presents a number of challenges.

  • Data security: The edge is not always within your control and can be difficult to secure because of the distributed nature of the network. Edge devices are often located in public places or shared offices, which makes them more vulnerable than traditional data centers. Additionally, many IoT devices lack strong authentication capabilities and use weak passwords that can easily be cracked by hackers targeting a single device or group of devices (known as botnet attacks). In order to protect against these threats while still maintaining high performance levels, you need an advanced security solution that monitors all traffic between clients/servers and ensures trusted connections only occur over encrypted channels while preventing unauthorized access attempts through firewalls or intrusion detection systems (IDSs).
  • Bandwidth limitations: While backhaul connections may support high bandwidths today–upwards of 10 gigabytes per second–the last mile still lags behind with average speeds under 1 GBps for residential customers according to Akamai’s State Of Internet Report 2018 . This means companies will either have difficulty transmitting large files from their servers directly into homes without incurring substantial costs due to limited capacity; alternatively if they choose instead

to take advantage of cloud services such as Amazon Web Services’ Lambda@Edge platform then users could face latency issues when interacting with applications running locally since these services require constant connectivity from users’ computers before responding.”

Processing your data at the edge will enable you to improve your business processes and data flow.

When you process your data at the edge, it enables you to improve your business processes and data flow.

Conclusion

Edge computing is a game changer, one that will change how we use data and process it. It has many advantages over traditional methods of computing, but it also comes with some challenges that need to be addressed before it can be fully adopted by businesses. We believe that edge computing will become more popular as more people realize its potential and start using it in their everyday lives