There are so many brands with so many models of routers that it is becoming harder and harder to choose. The boxes advertise feature after feature with no clear explanation of what they mean. Here are some points to note when buying a new router or access point:

Antennas

Do not be fooled by routers and other devices with several large antennas protruding from all sides. None of those make any difference to the signal strength of the device. Look at the technical specifications and see how many antennas are inside the device. Usually, three or more high gain antennas are what we want in a wireless device.

OS

Most vendors ship their devices with their OS. The problem with vendor specific software is that they rarely update them. Some vendors use open source operating systems like DD-WRT or OPEN-WRT. Such operating systems are feature rich and are maintained by the community.

Features

When it comes to routers, we want more than just internet connectivity and wireless. Features that most families find useful will include parental controls, bandwidth controls, device specific blocks and even a mini-firewall. More is not always better, but look out for features that you will find useful.

Build

Lastly, look at the build quality of the device. Cheap plastic construction will not last long and eventually become brittle over time. A good sturdy router will likely have quality components inside, which should last well beyond the warranty period.


robot women in technology background

robot women in technology background

Just a few years ago, artificial intelligence was the subject of science fiction. Now, not a single day goes by without some AI or machine learning driven advance. To be clear, when we talk about AI today, we refer to machine learning. It is using artificial intelligence to teach computers without any actual programming. Even in such a short span of time, it is already changing the way we do things.

Let us look at a few examples of machine learning implementation:

Sales – Platforms like salesforce.com are using machine learning to help sales teams target leads. Using data gathered from years of sales, the system could flag which leads have a higher probability of translating into sales.

Imaging – The primary example is of Google using machine learning to teach a computer how to upscale an image. The training used several thousand images. First, it analyzed the full-size image and then an image about a quarter of its size. It was then able to take any smaller image and produce a larger version with as much or more detail.

Language – Google also uses machine learning extensively on languages. The primary use so far has been in translation. For that to work, however, it required training on understanding the languages and then translating.

This is a small sample of how AI is becoming the next big thing in tech. So far, Google is in the lead with IBM not so far behind. Apple, Amazon, and Microsoft are all building out machine learning capability.

 


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The smart home and internet of things are the only things anyone can talk about these days. The tech press believes that it is going to be the future when in fact you can already have a fully connected home today. Although it is not a cheap conversion, it is now more affordable than a few years ago and can be started for a few hundred dollars.

The first step is to look at what you want to be able to do. Here are a few use cases that you might want to use:

Security


Smart home devices can also be used for security. The primary devices used here, in addition to a hub would be door and windows sensors, proximity sensors and lights. All doors and windows can have sensors that can trigger alarms. There are even sirens that can be connected and triggered. Proximity sensors can trigger external lights on motion and cameras.

Safety

Another use case is night time safety. Proximity sensors in corridors can be set to switch lights on when activated at night. The same goes for a trip the toilet at night, open the door and the lights will come automatically. These same sensors can also switch the lights off after a period of inactivity.

Future Home

The final and most attractive use case is for a fully connected future home experience. The lights come on when you are close by. The air conditioning comes on at specific temperatures close to when you will enter the house. Too cold? The heater comes and keeps the house at a nice toasty temperature. This and so much more is possible with today’s technology.

 


Systems administrators spend a lot of their time attending to periodic tasks. These tasks range from preventative maintenance to simple report generation. None of this is a problem until there is a critical issue that needs attention. The time spent on resolving any issues is the time that cannot be spent attending to these periodic tasks. The simplest and most efficient way is to automate as much of the regular tasks as possible. Here are two options for automating system administration tasks:

PowerShell

In a mostly Windows environment, PowerShell is a powerful scripting language that will allow most common tasks. There are modules that add support for Active Directory, Windows Server Backup, DHCP, DNS, and almost every service provided by Microsoft. The version of PowerShell varies depending on the version of Windows, although upgrades are available for older systems.

Python

Python is a popular programming language among systems administrators. There are courses specific to systems and network automation, which will teach you what you need specifically for those environments. Many systems have built-in API’s (application programming interfaces). You can use these API’s to extract data from the system without any human intervention. This way you can combine data from several systems to produce reports or dashboards.

These are the two most common languages used when it comes to automating systems tasks. It is even possible to combine both. When set on a schedule, it is as simple as setting and forgetting, freeing up time for other more important tasks.


Summary: Network operation centers are designed to handle a variety of complex tasks that are meant for teams that are light years ahead of their time.

 

Today’s network operations centers are hardly what they were decades ago. Technology has advanced and evolved to the point where plenty of functionalities are now automated. The latest in visualization and communication technology has come together to create a center that’s calibrated to handle the most complex tasks.

 

Mission Critical Tasks for Everyday Use

 

Network operations centers, which were once reserved for the highest levels of government, military, and high-end businesses, are now considered standard infrastructure for a variety of different mission critical tasks such as: traffic control, telecommunications monitoring, communication networks, transportation traffic monitoring, and more. Furthermore, the network operations center video wall that’s usually integrated within the command center comes loaded with an abundance of features that are easily accessible to any specialist.

 

If you live in a medium-sized city, chances are your local law enforcement is utilizing some type of network operations center that can handle every task needed for the police to keep an eye out for crime and other misnomers. Moreover, these network operation centers are more capable than the original versions at NASA – which is quite a step up in regards to technological advancement.

 

Final Thoughts

 

If you’re looking to incorporate a command center or network operations center for your business – which is now more accessible than ever – it’s important that you understand the costs, issues, and other important factors that play a crucial role in the success of the center. You’ll want to consult with a professional integration company or a designer which specializes in creating custom command center furniture consoles and more. Otherwise, you’re throwing caution to the wind – which you know could be the biggest financial mistake that you could ever make.