The mobile phone has become such an essential part of our lives as we move towards more advanced stages of the “always on, always connected” model. Our phones provide instant access to data and communication mediums, and that access influences the decisions we make and ultimately, our behavior.
According to Cisco, global mobile networks will support more than 12 billion mobile devices and IoT connections by 2022.1 And these mobile devices will support a variety of functions. Already, our phones replace gadgets and enable services. Why carry around a wallet when your phone can provide Apple Pay, Google Pay or make an electronic payment? Who needs to carry car keys when your phone can unlock and start your car or open your garage door? Applications now also include live streaming services that enable VR/AR experiences and sharing in real time. While future services and applications seem unlimited to the imagination, they require next-generation data infrastructure to support and facilitate them.
The Need for Intelligence at the Edge
Network connectivity and traffic growth continue to increase as the rate of adoption of new data-intensive applications drive bandwidth requirements and a smarter infrastructure — an infrastructure that can, through intelligence, recognize specific application and infrastructure needs and deliver processing at the edge when necessary. While network speeds increase with advancements of multi-gigabit Ethernet and 400GE backbone connections, the bandwidth available with the latest 5G and Wi-Fi will continue to cause a bottleneck in the backhaul. Edge processing helps prevent the need for moving massive amounts of data across networks. This higher level of network intelligence allows the network to deliver complex software-defined infrastructure management without user intervention, manage inference engines, apply policies, and most importantly, deliver proactive application functionality. This enhances the user experience by offering a near real-time interactive platform with low latency, high reliability and secure infrastructure.
With bandwidth demand growing so much, how do we address it at scale? If we parallel the cloud data centers, we see that one way to scale out and handle the added bandwidth and number of nodes is to add processing to the edge of the network. This was accomplished in data centers through the use of smartNICs to offload complex processing tasks including packet processing, security and virtualization from the servers. A similar approach is being achieved in the carrier networks through the deployment of SD-WAN/uCPE/vCPE appliances placed at the edge to provide the intelligence alongside reduced connectivity costs. However, this approach becomes problematic in enterprise networks where a variety of end point capabilities are needed, and the first location of uniformity takes place at the network’s access layer.
Taking Advantage of Artificial Intelligence (AI)
Yet another challenge is created when legacy methods are used for deploying services in enterprise networks - such as centralized firewalls and authentication servers. With the expected increase in devices accessing the network and more bandwidth needed per device, these legacy constraints can result in bottlenecks. To address these issues, one must truly live on the network edge, pushing out the processing closer to the demand and making it more intelligent. Network OEMs, IT infrastructure owners and service providers will need to take advantage of the new generations of artificial intelligence (AI) and network function offloads at the access layer of the enterprise network.
TIPS to Living on the Network Edge
This is the first in a series providing TIPS about essential technologies that will be needed for the growing borderless campus as mobility and cloud applications proliferate and move networking functions from the core to the edge. Today, we discussed the trend toward expanded Network Intelligence. In Part 2, we will look at the Performance levels needed as we provide more insights and TIPS to Living on the Network Edge.