Currently, growing web users and rising implementation of digital services are propelling the growth of the market. Higher consummation of data services is likely to spur edge computing industry expansion with increasing adoption of edge computing as a service.

Edge computing helps users process data generated by IoT devices rather than transmitting data across long distant data centers or cloud servers for processing. Adoption of such a computing technique at close proximity to the network infrastructure allows organizations to analyze crucial data in real time. Edge computing performs various business processes such as accumulating, evaluating, and stacking real time data generated by IoT devices.

Growing focus on the reduction of cost and timely delivery, surging IoT data, need for automating business processes, and escalating business competitiveness are key drivers towards growth of the edge computing industry. The adoption of the edge commuting in business processes allows organizations to obtain real-time insights in improving the efficiency of decision-making algorithms to maximize profit margin. Hoiwever, data privacy and security issues are major deal breakers as they are hampering the market growth.

Edge computing relies on a mesh network consisting of micro data centers that are capable of processing vital data sets locally while transmitting rest of it to a centralized data center or cloud storage stations, which is located at a close proximity. The use of IoT technology in edge devices helps collect vast sets of data, while transmitting much smaller amounts of data transmission to the centralized data center for processing.

IoT devices transfer data to the micro data centers located nearby that are capable of performing sets of operations such as computation, storage and provide network accessibility. Processed data is transmitted from a micro data center to the central processing facility or storage repository in an Infrastructure as a service(IaaS) cloud.

Edge computing is considered a standard choice of technology under a variety of circumstances. Common reasons for the use of edge computing technology include poor connectivity of IoT devices with a central cloud unit and the substantial backhaul traffic required from the central data center.

Adoption of edge computing also solves issues related to the latency-sensitive processing of data. Numerous benefits of edge computing include decline in the volumes of data, decrease in the resulting traffic, and the reduced need for transmission of excess of data.

Other advantages include reduction in transmission cost, lower bandwidth, high level of performance and improved standard of service or QoS. Edge computing also removes a chief bottleneck or a possible single point of failure in the network.

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