Edge data centers are generally smaller facilities that extend the edge of the network to deliver cloud computing resources and cached streaming content to local end-users. These data centers come with more efficient architecture for transferring and processing the data. The purpose of moving data processing to the edge of the network is to accelerate the response times by reducing latency. Smart cities will see more and more IoT sensors and devices being installed in the home and industrial settings. Edge data centers will be the backbone for the operations and sustainability of smart cities since these data centers are purpose-built for processing huge volumes of data that are too time-sensitive to be transmitted back to a centralized cloud server. This will be driven by the scenarios in which the reaction speed is decisive for the success and safety of service provision. Software-Defined Networking (SDN) and Network Function Virtualization (NFV) can make applications perform seamlessly, thereby enabling the users to save costs by replacing the specialized hardware, required otherwise.
The market for edge data centers is expected to grow by three times over the next five years. Pi edge data center can provide measurable results in demonstrating how do we enable our customers to deliver their content faster and at a significantly lower cost to the local consumers (end users). Pi is committed to bringing computation and data storage closer to the devices where it’s being gathered, rather than relying on a central location that can be thousands of miles away. This will ensure that the data, especially real-time data, do not suffer latency issues that can affect an application’s performance. In addition, enterprises can reduce costs on data transmission and experience better performance by bypassing data processing in a centralized or cloud-based location.
|Power||< 1 MW||> 20 MW|
|Location||Close to end users, machines, and processes that generate and use data||Remote locations where power, water and human resources are economical|
|Time||Deployment time < 10 days||Deployment time > 365 Days|
|Tasks||Real-time Data Processing, Basic Analytics, Data Caching, Buffering, Data Filtering & Optimization||Big Data Processing, Business Logic, Data Warehousing|
Turn Key Edge DC implementations
Consulting Services to orgs
Sq. ft. of Data Centers