Issue link: https://www.e-digitaleditions.com/i/1219491
April/May/June 2020 I 33 necessary information across all stores in a consolidated area to provide advanced services to their customers. The client discovers glitches and errors due to the cur- rent edge being the central point of processing for each store independently which also requires a secondary pro- cess to have the stores share information. Network man- agers realize that in order to get latency to the desired level, they need to get even closer to the source. A decision is made to repurpose an existing piece of property in North Carolina and build out a new, wholly owned, regional EDC within a few miles of four nearby stores. The southern Virginia multi-tenant edge is still used as a fog data cen - ter for the critical data that can withstand the level of latency provided. A few years later, after losing hundreds of thousands of dollars in frozen food due to refrigeration and compres- sor failures, a decision is made to invest in machine learning equipment that listens to the equipment operate and detects patterns that suggest impending failures so that they can be preventatively avoided. At the same time, the client decides to implement a real-time auto - matic checkout system that when customers remove an item from the shelf and place it in the cart, the cart tallies the bill, and their credit cards are charged at check- out. These new systems have even more stringent latency and bandwidth requirements, especially the mission crit- ical machine learning failure detection system, and it is determined that even the round trip to the local edge is not good enough. They determine that the most cost efficient way to solve the problem without repurposing valuable retail space is to purchase an unassuming ship- ping container and within it a self-contained micro EDC that is placed on the side of the building. This provides the latency needed and allows the client to free up bandwidth to its edge and begin selling services to other businesses to utilize the excess capacity in its regional edge. To address the many concerns in the industry about security of an outdoor MDC, the unit could have been placed indoors had the supermarket had a small vacant office or closet that could be modified to include strict access control, especially since sensitive information, such as customer credit card accounts, would be at risk. "Rob Hirschfeld, CEO of data center consulting com - pany RackN, said that an unmanned mini data center for edge computing might make sense in parts of the US, but leaving $100,000 worth of computing equipment without some kind of guard is untenable in places like India." 5 ADDRESSING MDC CONCERNS Some members in the TIA Edge Data Center Working Group voice additional concerns about MDCs, which include physical security, vulnerability to sabotage, no on hand technical staff for troubleshooting resolution and to service hardware quickly, exposure to harsh condi- tions that may require hardened servers and switches, and natural disasters like severe storms and hurricanes that frequent the North Carolina coast in the supermarket example. Currently, the TIA working group is developing a list of edge use cases and analyzing effects on latency. A partial sample list follows: • LOWER LATENCY • Smart factory • AR/VR • REDUCE NETWORK COSTS • Local video processing for security and quality control • Local distribution of content • IMPROVE FORM FACTOR OF END DEVICES • Less compute and memory requirements in head gear (VR/AR), mobile cobots • SECURITY • Less access points, physical control • HIGHER RELIABILITY • Less failure points, less choking points • TELECOMMUNICATIONS/ICT NETWORK SITES • SDN infrastructure • VEHICLE TO INFRASTRUCTURE V2I RSU • Real-time traffic monitoring and alerts • HD real-time maps • V2V blind spot coverage • NETWORK FUNCTION VIRTUALIZATION • vRAN—Remote distributed unit (DU) and centralized unit (CU)