Edge computing and fog computing hardware resources are processed, and the capabilities allow data to be aggregated at the network-s edge, avoiding the network traffic previously required to transfer data to the cloud. Data aggregation is the process of gathering and representing information in an aggregate form for statistical analysis. Most data collection activity is performed at the edge of the network, and some data aggregation may be performed, for example, via Message Queue Telemetry Transport (MQTT), before the data is forwarded for processing and analysis.
In distributed edge computing, there are two schemes for data aggregation :
• Multidimensional and Multi-directional Data Aggregation (MMDA): MMDA can provide the IoT control center with more statistics for analysis and processing and uses batch verification technology to reduce authentication costs. MMDA enables edge devices to accumulate multidimensional data from IoT devices in two directions.
• Row aggregation
• Column aggregation
• Blockchain-based Secure Data Aggregation(BSDA): Blockchain-based Secure Data Aggregation is designed to accomplish secure data aggregation and harvest energy efficiency in data aggregation. To prevent privacy leaks, security badges, which consist of task security levels and task completion demands, are combined into the block header design so that task recipients can access tasks with appropriate security levels and task completion requirements. BSDA Enables deep exploration, improved stability, and accelerated convergence, enabling energy-efficient MDC routes.
• LPDA-EC: A lightweight privacy-preserving data aggregation scheme for edge computing.
• Privacy-preserving data aggregation scheme for mobile edge computing assisted IoT applications.
• Privacy‐preserving data aggregation scheme for edge computing supported vehicular ad hoc networks.
• Lightweight and fine-grained privacy-preserving data aggregation scheme in edge computing.
