| A fundamental challenge in the design of wireless sensor networks(WSNs)is to maximize their lifetime especially because they have a limited and nonexchangeable energy supply.One important mechanism to solve this bottleneck is the in-network data aggregation,which aims to eliminate redundant packet transmissions by filtering repeated and unnecessary data readings and thus cut down the energy used in communication.Generally speaking,an aggregation protocol should achieve two main objectives: optimizing the algorithm to decrease energy cost and privacy-preserving.Based on the previous study,the optimized data aggregation privacy-preserving algorithm in clustered Wireless Sensor Networks is mainly researched in this thesis.The main research work and contributions of this thesis are as follows:1.A source coding based privacy-preserving data aggregation algorithm is proposed for uniform cluster-based WSNs,which adopts a routing optimization scheme.At first,this scheme realizes hiding and compression of data by operating source coding to privacy data according to the correlation of them.Then the coded data is forwarded by adaptively selecting the most energy-efficient communication mode.The results of analysis and testing show that the proposed algorithm could preserve data privacy with lower communication assumption.2.Based on source coding technology,the recoverable data aggregation privacy-preserving scheme is proposed to solve the problem of unbalanced energy dissipation of in uneven clustering WSNs.Firstly,this scheme can balance node energy consume by a novel uneven cluster-based routing protocol.Secondly,the data collected by the sensor nodes are encoded to reduce the amount of data transmission.Thirdly,this scheme converts and concatenates the coded data so that the base station can recover all sensing data even these data has been aggregated.Experiment results demonstrate that the proposed scheme can protect data privacy as well as decrease redundantly transmitted data. |
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