Optimizing Edge-Cloud Synergy for Big Data Analytics

High-computational complexity tasks benefit greatly in time requirements by offloading from edge nodes to cloud resources. In contrast, low-complexity tasks exhibit little competitive advantage from this edge-cloud synergy. By reformatting the offloading process to partition low-complexity Big Data tasks between one edge but multiple cloud centres up to 80% of the tasks can be served by cloud resources with major reductions in total task completion times; this is favoured by accessing 5G speeds in the Wireless Local Area Network to leverage the greater processing speeds of cloud resources. High-complexity tasks also are agnostic to queuing delays in cloud resources but low-complexity tasks are less robust and require the edge-cloud orchestration software embedded in edge nodes to be able to divert such tasks to optimal choices of cloud destinations with full awareness of Wide Area Network speeds, cloud processing advantages and minimal queueing options.