Research On Data Aggregation Algorithm In Wireless Sensor Network

Sensing information processing in the Internet of Things (IoT) includes collecting, aggregating,transmitting and analyzing etc. In order to meet the requirements of privacy protection andreliability of decision-making and controlling, a low power consumption privacy-preservingaggregation algorithm is needed to ensure the security in aggregation process and the adaptability ofWireless sensor networks (WSNs).In the recent years, some algorithms about security and privacy-preserving of WSNs have beenpublished, which can be classified into two categories. The first uses homomorphic encryption. Itmakes nodes aggregate data effectively without using decryption. But it cannot provide any privacy-preserving in terms of QS(Query Server). The second is based on information exchange betweennodes to prevent private data exposing, the shortcomings of which are large communicationoverhead and bad data-loss resilience.This thesis focuses on how to design a more effective privacy-preserving aggregationmechanism for WSNs. We propose an energy-saving privacy-preserving aggregation algorithm:ESPART, which uses characteristic of the data aggregation tree structure to reduce unnecessarycommunication overhead in SMART, assigns the random time slot to nodes to avoid collision, andlimits the scope of collusion data to reinforce data-loss resilience. The theoretical analysis andsimulation results show that the ESPART algorithm has better performance in terms ofcommunicationoverhead and aggregationaccuracy thanthat of the SMART and CPDA.