What is

Edge Computing

edge-computing_introduction edge-computing_introduction

Enhanced speed,
reduced latency and bandwidth

Place applications out where critical devices and users are, so internet and transport latency aren’t a factor.

Improved Security

Compromised portions of the network can be cordoned off without shutting down everything.


Organizations can also leverage the additional processing power to improve their threat analysis data.

Use Case

Government Agency


case_01
case_01
case_01

A government agency in a European country integrated 70 SDX Pros into their teleconferencing kits for their officials. They leveraged the edge computing capabilities of the SDX Pro and installed Pexip, a video conferencing software, on KVM hosted on the Peplink router.

This keeps data at the edge and prevents data breaches for increased security.

Use Case

IoT Solution Provider


case_02
case_02
case_02

A US-based IoT solution provider develops real-time monitoring applications and uses Peplink in its solutions to ensure reliable connectivity. In one case, they use the HD2 MBX with edge computing for dual cellular.

Since not all of the real-time data needs to be streamed to the data center, only a few seconds of video captured at the time of trigger is stored and sent, greatly improving the efficiency.

Demonstrations


How to use Docker How to use KVM

Supported
Devices


* Maximum resource allocation is limited to half of the device’s processor count and memory for docker use. This value cannot be adjusted.
# Avoid over-allocating the processor and memory to the KVM as this may impact the overall performance of the router.
^ Available in firmware 8.3.2

For Docker usage, our firmware will allocate a maximum of only half of the processor count and memory for their usage. Please note that this allocation cannot be adjusted by the user.
For KVM usage, the user has control over the number of processors and memory allocated to it. However, it’s important to be mindful that over-allocating the processor and memory to the KVM can impact the performance of the router. To simplify, let’s use SDX Pro as an example. Docker usage is limited to a maximum of half the processor and memory, meaning that only up to 4 cores and 4GB of memory can be utilized. On the other hand, users are free to control the processor and memory allocation to the KVM. However, it’s crucial to be mindful of over-allocating, as this can negatively impact the performance of the router.
Model Architectures Processor Memory Internal
Storage Size		 Internal Storage External Storage via USB Port^
Applications Docker

*

 KVM

#

 Applications Docker

*

 KVM

#
MediaFast 500 X86 2 Cores @ 1.74GHz 4GB 500GB
MediaFast 750 X86 2 Cores @ 3.5GHz 8GB 1TB
SDX Pro X86 8 Cores @ 2.2GHz 8GB 500GB / 1TB / 2TB
Balance 2500 EC X86 8 Cores @ 3.3Ghz 16GB 1TB
EPX
with Expansion Module (EXM-LCDT)		 X86 4 Cores @ 2.1Ghz 16GB 1TB
MAX HD2/4 MBX
with MediaFast		 X86 4 Cores @1.6Ghz 8GB 120GB / 500GB
MAX BR2 Pro ARM 64 4 Cores @ 1.8Ghz 2GB 8GB
MAX Transit Duo Pro ARM 64 4 Cores @ 1.8Ghz 2GB 8GB
N/A
SDX X86 4 Cores @ 2.2GHz 4GB N/A N/A
MAX MBX Mini X86 4 Cores @1.5GHz 4GB
MAX HD2/4 MBX X86 2 Cores @ 1.3GHz 4GB
PDX X86 4 Cores @1.6Ghz 8GB
Balance 310X X86 2 Cores @ 1.3GHz 4GB
Balance 380X X86 2 Cores @ 1.5GHz 4GB
Balance 580X X86 2 Cores @ 1.5GHz 4GB
Balance 310 5G X86 2 Cores @ 1.5GHz 4GB
Balance 310 Fiber 5G X86 2 Cores @ 1.5GHz 4GB
Balance 710 X86 2 Cores @ 3.5GHz 2GB
Balance 1350 X86 2 Cores @ 3.5GHz 4GB
Balance 2500 X86 4 Cores @ 3.5GHz 8GB