Study On Data Acquisition And Transmission Based On Participatory Sensing

Participatory sensing technology is a new paradigm put forward for information perception in recent years.Through participatory sensing,we can obtain detailed people-centric information of our daily city-life using mobile devices.This paper proposes Compressed-Sensing-Based and Social-relationship-aware Participatory Sensing Data Acquisition Algorithm(CSDA)and Data Transmission algorithm in Opportunistic network based on the Shortest-path(DTOS).CSDA algorithm samples original data based on the compressed sensing sampling rule,and transmits sampled data over the network.The receiver processes received data and estimate un-transmitted data with the help of nodes' social relationship,and recover the original data exploiting the compressed sensing reconstruction algorithm.When there are sufficient mobile nodes in the network,the CSDA algorithm can recover all data in the whole sensing area using a certain part of data.The experimental results show that CSDA can remarkably reduce the amount of data transmitted over the network without losing data fidelity,and hence decrease the network overhead.DTOS algorithm proposes a framework with fixed nodes in the opportunistic network,and then proposes a Breadth-First search based AP-Deployment algorithm(BFAD)to find an optimal scheme to distribute the Aps in the vertexes.At last,the Information Entropy based Weight-calculation algorithm(IEW)is proposed to measure the weight of each edge for the Dijkstra algorithm.The experimental results show that the DTOS algorithm can improve the data transmission stability and reduce transmission delay in opportunistic network.