INDUSTRY 4.0- EDGE DATA CENTERS

EDGE DATA CENTERS

In a time where everything, everywhere is being “digitized”, we continue to see technologies like IoT, machine learning, AI, robotics, virtual/augmented reality, and data/video analytics being deployed. Businesses need these technologies to maintain competitive advantages and to stay relevant in their industries. But with these technologies comes latency, bandwidth, autonomy, and regulatory/security requirements that a centralized data center architecture cannot support. As edge computing becomes a regular feature of today’s network strategies, many companies are turning to edge data centers to help implement these plans. The rising demand has caused data center providers to rethink how they position themselves in growing markets that stand to benefit the most from edge computing.

Edge data centers are somewhat difficult to define, but they are generally smaller facilities that extend the edge of the network to deliver cloud computing resources and cached streaming content to local end users. While Edge data centers will be providing an array of services independently, a more centralized data center can be backing them up with cloud services and analytics.

TYPES:

Local devices: Devices sized to accommodate a defined and specified purpose. Deployment is “immediate” and they are suitable for home or small office applications. Running the security system for the building (Intel SOC appliance) or storing local video content on a DVR are examples. Another example is a cloud storage gateway which is a local device and is usually a network appliance or server that translates cloud storage APIs such as SOAP or REST. Cloud storage gateways enable users to integrate cloud storage into applications without moving the applications into the cloud itself.

Localized (1-10 racks) data centers: These data centers provide significant processing and storage capabilities and are fast to deploy in existing environments. These data centers are often available as configure-to-order systems which are pre-engineered and then assembled on site. Single rack versions can leverage existing building, cooling, and power, thereby saving on CAPEX vs. having to build a new dedicated site. Installation requires picking the location in close proximity to the building power and fiber source. Multi-rack versions are more capable and flexible due to scale, but require more planning and installation time and need their own form of dedicated cooling. These 1-10 rack systems are suitable for a broad base of applications requiring low latency, and/or high bandwidth, and/or added security or availability.

Regional data centers: Data centers that have more than 10 racks and are located closer to the user and data source than centralized cloud data centers are called regional data centers. Due to their scale, they will have more processing and storage capabilities than localized 1-10 rack data centers. Even if they are prefabricated they will take longer to construct than localized data centers due to the likely need for construction, permitting, and local compliance issues. They will also need dedicated power and cooling sources. Latency will be dependent on the physical proximity to the users and data as well as the number of hops in between.

APPLICATIONS:

One of the most important initiatives rolled out by the government is the Smart Cities Mission which will be rolling out 100 Smart Cities in four phases in INDIA. These Smart Cities have given rise to the need for more data centers. Owing to some of these being present in Tier-2 and Tier-3 locations, Edge data centers will play a crucial role. Many Indian companies in the last three months have shown interest in the same and have explored the options of investing in data centers in India. As example, real estate major Hiranandani Group has announced plans to invest Rs 14,000 crore (almost USD$2 billion) in its data center projects.

In a retail store environment alone, we’ve identified many use-cases – from observing facial expressions of customers, to determining when queue lines will form, or even to eliminating the traditional “check out” process.

In a manufacturing facility such as an automotive plant or say it connected vehicles or autonomous vehicles, it’s being deployed for personal safety, for detecting production defects, and to streamline operations of vehicles on road.

In financial branches, to people count and identify demographics; and in a healthcare facility, to monitor patients and analyze when you need intervention. As technologies like this become a more integral part of the day-to-day business and/or customer experience, the edge compute sites that house the associated distributed IT equipment must be robust. The role of IT is no longer viewed as a cost center, rather it is tightly connected to the business strategy and to profit, making resiliency even more imperative.

A new wave of factory automation is underway and robots are entering new environments and creating new value for manufacturers. In part, this trend is driven by the availability of collaborative robots, or ‘cobots’, that are cheaper, more mobile and more flexible than their predecessors and that can work safely alongside human colleagues.

Oil & gas exploration is an example of this IIoT application. Multiple flying drones called “aerial data collection bots” examining job sites during oil exploration is generating large quantities of data in the form of high definition video. These job sites are difficult to coordinate with fleets of massive trucks, cranes, and rotary diggers. Legacy methods of traffic management have used manned helicopters for surveillance video. Self-piloted drones can photograph job sites 24 hours a day providing site managers an up-to-the-minute view of how their resources are deployed. Relying on edge computing allows the drones to transmit the data in real time and receive instructions in a timely fashion.

As we get deeper into the Industry 4.0 era, we’re going to see increased demand for industrial edge data centers. Some will be relatively large facilities housed inside manufacturing plants with IoT/smart sensors often depends on cloud network access to understand about both machine learning and complex programs, and here is where Edge computing is beneficial. Businesses in India and globally are increasingly exploring Edge data centers to minimize the operational costs as an IoT app is best suited to leverage Edge data centers.

CHALLENGES:

There have always been challenges related to selecting, configuring, deploying, and maintaining IT infrastructure at a given location. Those responsible for edge compute sites, however, often face the additional challenge of having to do this over multiple locations with little to no onsite staff. Working with the right ecosystem eliminates or mitigates the challenges described below. Selecting and configuring infrastructure components can be complex. One mistake can propagate to hundreds of installations if not identified early on. Infrastructure parts must be selected that not only support the intended application, but that are also compatible with each other and fit each local site’s conditions.

This complexity leads to common mistakes we have seen at the edge such as:

• UPS undersized or grossly oversized for the expected IT load.
• Not considering UPS redundancy or UPS bypass (allows UPS replacement without downtime).
• Not enough output receptacles (or wrong type) on rack PDU / UPS.
• Not enough U space in rack or spare space for expansion.
• Forgetting to order accessory parts kits needed to rack and cable everything.
• Not considering space constraints in rolling equipment into place Deploying all the parts to each site can be a major logistical and workforce challenge.

Some of the common problems we have seen include:

• Finding wall space to mount cabinets onto studs.
• Sites not being prepared for large amount of de-trashing required.
• Separate components not arriving on time for the install.
• Losing small parts during onsite assembly.
• Difficulty obtaining necessary number of IP addresses.
• Site electrical not ready for installation of the IT equipment.

**As our technology gets more and more advanced—the network that these devices are on needs to become more advanced as well. It seems as though Edge networking will certainly be a part of data management in the future. Edge brings the network closer to the users and eliminates latency issues. It will also help streamline the flow of traffic from smart devices within IoT systems. Although people once thought Edge would displace the Cloud—it is more likely they will work together to make our lives easier.