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What are edge computing challenges for the network?

Edge computing can reduce processing times and improve application performance, but the technology has its issues. Here are six challenges edge computing creates for the network.

In the ongoing back and forth between centralized and decentralized IT, we are beginning to see the limitations of a centralized IT that relies on hundreds or thousands of industry standard servers running a host of applications in consolidated data centers. New types of workloads, distributed computing and the advent of IoT have fueled the rise of edge computing.

Instead of trying to run everything within the data center, companies are finding that processing at the edge brings compute closer to data accumulation -- but it also brings a new set of challenges to the network.

Here are six edge computing challenges companies should keep in mind.

1. Network bandwidth. As more data is stored at the edge and more compute happens at the edge, network bandwidth will shift. Traditionally, enterprises allocate higher bandwidth to data centers and lower bandwidth to the endpoints. Now, a challenge with edge computing is the need to balance more bandwidth across the network.

2. Distributed computing. Businesses will need to take location into consideration as an additional aspect of compute. Consolidated compute models are dissipating; computing now needs to include networking as a key element, with a greater focus on east-west traffic.

3. Latency. By locating compute at the edge -- where compute is closer to the data that is collected -- application latency is reduced along with decision-making latency. Less back-and-forth movement from the edge to the core means faster answers and faster action.

Edge computing challenges for networking
Watch out for these six edge computing challenges in the network.

But with compute located at both the core and the edge, application data traverses the network in each direction, sharing data and dealing with access rights. This means data transfer is no longer a simple one-way process.

4. Security. When compute resources and applications are centralized in a data center, enterprises can standardize both technical security and physical security. It's possible to build a wall around the resources for easier security.

But edge computing forces businesses to grapple with enforcing the same network security models and the physical security parameters for more remote servers. The challenge is the security footprint and traffic patterns are all over the place.

5. Backup. The need for edge computing typically emerges because disparate locations are collecting large amounts of data. Enterprises need an overall data protection strategy that can comprehend all this data. Network bandwidth requirements will be just as critical as storage media considerations when deciding how to protect these assets, because backup over the network may not make sense.

6. Data accumulation. Data is a key business asset, and collecting it at the edge brings new challenges and can create liabilities if it's not handled in accordance with existing data handling rules. Data storage and access are critical, both of which will need to encompass the network as part of the data lifecycle.

Next Steps

Explore how edge computing could affect cloud computing

Learn more about edge computing architecture

This was last published in May 2019

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