Edge computing is the concept of the distributed paradigm. In order to improve the response time and to save the bandwidth, it brings the computation and the storage of the data closer to the location whenever it is needed. Edge computing is one of the very famous and blooming concept in today's era. It has been used in so many applications for various purposes. Edge computing can be defined as infrastructure of physical compute which is placed between the device and the cloud to support various application and which brings the cloud closer to the end user or end devices. In this chapter, the authors discuss the origin of the edge paradigm, introduction, benefits. These are some of the criteria to be elaborated in the chapter overview of edge paradigm.

Edge analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch, or other device instead of waiting for the data to be sent back to a centralized data store. Cloud computing has revolutionized how people store and use their data; however, there are some areas where cloud is limited; latency, bandwidth, security, and a lack of offline access can be problematic. To solve this problem, users need robust, secure, and intelligent on-premise infrastructure for edge computing. When data is physically located closer to the users who connected to it, information can be shared quickly, securely, and without latency. In financial services, gaming, healthcare, and retail, low levels of latency are vital for a great digital customer experience. To improve reliability and faster response times, combing cloud with edge infrastructure from APC by Schneider electrical is proposed.

Edge computing is the concept of the distributed paradigm. In order to improve the response time and to save the bandwidth, it brings the computation and the storage of the data closer to the location whenever it is needed. Edge computing is one of the very famous and blooming concept in today's era. It has been used in so many applications for various purposes. Edge computing can be defined as infrastructure of physical compute which is placed between the device and the cloud to support various application and which brings the cloud closer to the end user or end devices. In this chapter, the authors discuss the origin of the edge paradigm, introduction, benefits. These are some of the criteria to be elaborated in the chapter overview of edge paradigm.

Edge analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch, or other device instead of waiting for the data to be sent back to a centralized data store. Cloud computing has revolutionized how people store and use their data; however, there are some areas where cloud is limited; latency, bandwidth, security, and a lack of offline access can be problematic. To solve this problem, users need robust, secure, and intelligent on-premise infrastructure for edge computing. When data is physically located closer to the users who connected to it, information can be shared quickly, securely, and without latency. In financial services, gaming, healthcare, and retail, low levels of latency are vital for a great digital customer experience. To improve reliability and faster response times, combing cloud with edge infrastructure from APC by Schneider electrical is proposed.